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Publisher: Springer-Verlag   (Total: 2335 journals)

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Showing 1 - 200 of 2335 Journals sorted alphabetically
3D Research     Hybrid Journal   (Followers: 19, SJR: 0.214, h-index: 10)
4OR: A Quarterly J. of Operations Research     Hybrid Journal   (Followers: 9, SJR: 1.073, h-index: 25)
AAPS J.     Hybrid Journal   (Followers: 16, SJR: 1.192, h-index: 74)
AAPS PharmSciTech     Hybrid Journal   (Followers: 6, SJR: 0.718, h-index: 54)
Abdominal Imaging     Hybrid Journal   (Followers: 16, SJR: 0.723, h-index: 60)
Abhandlungen aus dem Mathematischen Seminar der Universitat Hamburg     Hybrid Journal   (Followers: 2, SJR: 0.447, h-index: 12)
Academic Psychiatry     Full-text available via subscription   (Followers: 22, SJR: 0.492, h-index: 32)
Academic Questions     Hybrid Journal   (Followers: 7, SJR: 0.135, h-index: 6)
Accreditation and Quality Assurance: J. for Quality, Comparability and Reliability in Chemical Measurement     Hybrid Journal   (Followers: 25, SJR: 0.378, h-index: 30)
Acoustical Physics     Hybrid Journal   (Followers: 10, SJR: 0.355, h-index: 20)
Acta Analytica     Hybrid Journal   (Followers: 7, SJR: 0.387, h-index: 6)
Acta Applicandae Mathematicae     Hybrid Journal   (Followers: 1, SJR: 0.624, h-index: 34)
Acta Biotheoretica     Hybrid Journal   (Followers: 5, SJR: 0.419, h-index: 25)
Acta Diabetologica     Hybrid Journal   (Followers: 14, SJR: 1.318, h-index: 46)
Acta Endoscopica     Hybrid Journal   (Followers: 1, SJR: 0.113, h-index: 8)
acta ethologica     Hybrid Journal   (Followers: 4, SJR: 0.465, h-index: 23)
Acta Geochimica     Hybrid Journal   (Followers: 3)
Acta Geodaetica et Geophysica     Hybrid Journal   (Followers: 1, SJR: 0.294, h-index: 13)
Acta Geotechnica     Hybrid Journal   (Followers: 6, SJR: 1.818, h-index: 22)
Acta Informatica     Hybrid Journal   (Followers: 5, SJR: 0.524, h-index: 32)
Acta Mathematica     Hybrid Journal   (Followers: 9, SJR: 8.021, h-index: 47)
Acta Mathematica Hungarica     Hybrid Journal   (Followers: 2, SJR: 0.53, h-index: 29)
Acta Mathematica Sinica, English Series     Hybrid Journal   (Followers: 5, SJR: 0.406, h-index: 30)
Acta Mathematica Vietnamica     Hybrid Journal   (SJR: 0.451, h-index: 5)
Acta Mathematicae Applicatae Sinica, English Series     Hybrid Journal   (SJR: 0.22, h-index: 20)
Acta Mechanica     Hybrid Journal   (Followers: 18, SJR: 0.898, h-index: 52)
Acta Mechanica Sinica     Hybrid Journal   (Followers: 4, SJR: 0.426, h-index: 29)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5, SJR: 0.525, h-index: 18)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 3, SJR: 0.524, h-index: 14)
Acta Neurochirurgica     Hybrid Journal   (Followers: 7, SJR: 0.833, h-index: 73)
Acta Neurologica Belgica     Hybrid Journal   (SJR: 0.348, h-index: 27)
Acta Neuropathologica     Hybrid Journal   (Followers: 3, SJR: 6.61, h-index: 117)
Acta Oceanologica Sinica     Hybrid Journal   (Followers: 3, SJR: 0.295, h-index: 17)
Acta Parasitologica     Hybrid Journal   (Followers: 9, SJR: 0.581, h-index: 28)
Acta Physiologiae Plantarum     Hybrid Journal   (Followers: 2, SJR: 0.551, h-index: 39)
Acta Politica     Hybrid Journal   (Followers: 13, SJR: 0.658, h-index: 20)
adhäsion KLEBEN & DICHTEN     Hybrid Journal   (Followers: 5, SJR: 0.103, h-index: 4)
ADHD Attention Deficit and Hyperactivity Disorders     Hybrid Journal   (Followers: 20, SJR: 0.871, h-index: 15)
Adhesion Adhesives & Sealants     Hybrid Journal   (Followers: 7)
Administration and Policy in Mental Health and Mental Health Services Research     Partially Free   (Followers: 15, SJR: 0.795, h-index: 40)
Adsorption     Hybrid Journal   (Followers: 4, SJR: 0.774, h-index: 52)
Advances in Applied Clifford Algebras     Hybrid Journal   (Followers: 3, SJR: 0.319, h-index: 15)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 34, SJR: 0.959, h-index: 44)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 15, SJR: 1.255, h-index: 44)
Advances in Contraception     Hybrid Journal   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 48, SJR: 1.113, h-index: 14)
Advances in Gerontology     Partially Free   (Followers: 7, SJR: 0.141, h-index: 3)
Advances in Health Sciences Education     Hybrid Journal   (Followers: 23, SJR: 1.397, h-index: 42)
Advances in Manufacturing     Hybrid Journal   (Followers: 3, SJR: 0.2, h-index: 4)
Advances in Polymer Science     Hybrid Journal   (Followers: 40, SJR: 0.637, h-index: 89)
Advances in Therapy     Hybrid Journal   (Followers: 6, SJR: 0.79, h-index: 44)
Aegean Review of the Law of the Sea and Maritime Law     Hybrid Journal   (Followers: 7)
Aequationes Mathematicae     Hybrid Journal   (Followers: 2, SJR: 0.882, h-index: 23)
Aerobiologia     Hybrid Journal   (Followers: 1, SJR: 0.511, h-index: 36)
Aesthetic Plastic Surgery     Hybrid Journal   (Followers: 8, SJR: 0.821, h-index: 49)
African Archaeological Review     Hybrid Journal   (Followers: 14, SJR: 0.612, h-index: 24)
Afrika Matematika     Hybrid Journal   (Followers: 1, SJR: 0.248, h-index: 6)
AGE     Hybrid Journal   (Followers: 7, SJR: 1.358, h-index: 33)
Ageing Intl.     Hybrid Journal   (Followers: 6, SJR: 0.337, h-index: 10)
Aggiornamenti CIO     Hybrid Journal   (Followers: 1)
Aging Clinical and Experimental Research     Hybrid Journal   (Followers: 3, SJR: 0.529, h-index: 55)
Agricultural Research     Hybrid Journal   (Followers: 3)
Agriculture and Human Values     Hybrid Journal   (Followers: 12, SJR: 1.197, h-index: 49)
Agroforestry Systems     Hybrid Journal   (Followers: 20, SJR: 0.64, h-index: 56)
Agronomy for Sustainable Development     Hybrid Journal   (Followers: 10, SJR: 1.732, h-index: 59)
AI & Society     Hybrid Journal   (Followers: 7, SJR: 0.171, h-index: 19)
AIDS and Behavior     Hybrid Journal   (Followers: 13, SJR: 2.006, h-index: 71)
Air Quality, Atmosphere & Health     Hybrid Journal   (Followers: 2, SJR: 0.706, h-index: 19)
Akupunktur & Aurikulomedizin     Full-text available via subscription   (Followers: 1)
Algebra and Logic     Hybrid Journal   (Followers: 2, SJR: 0.566, h-index: 18)
Algebra Universalis     Hybrid Journal   (Followers: 2, SJR: 0.388, h-index: 22)
Algebras and Representation Theory     Hybrid Journal   (SJR: 0.868, h-index: 20)
Algorithmica     Hybrid Journal   (Followers: 7, SJR: 0.898, h-index: 56)
Allergo J.     Full-text available via subscription   (Followers: 1, SJR: 0.183, h-index: 20)
Allergo J. Intl.     Hybrid Journal   (Followers: 2)
Alpine Botany     Hybrid Journal   (Followers: 3, SJR: 0.729, h-index: 20)
ALTEX : Alternatives to Animal Experimentation     Open Access   (Followers: 3, SJR: 1.392, h-index: 32)
AMBIO     Hybrid Journal   (Followers: 14, SJR: 1.094, h-index: 87)
American J. of Cardiovascular Drugs     Hybrid Journal   (Followers: 10, SJR: 0.864, h-index: 39)
American J. of Community Psychology     Hybrid Journal   (Followers: 24, SJR: 1.237, h-index: 83)
American J. of Criminal Justice     Hybrid Journal   (Followers: 5, SJR: 0.634, h-index: 13)
American J. of Cultural Sociology     Hybrid Journal   (Followers: 11, SJR: 0.283, h-index: 3)
American J. of Dance Therapy     Hybrid Journal   (Followers: 4, SJR: 0.175, h-index: 13)
American J. of Potato Research     Hybrid Journal   (Followers: 2, SJR: 0.558, h-index: 35)
American J. of Psychoanalysis     Hybrid Journal   (Followers: 20, SJR: 0.293, h-index: 13)
American Sociologist     Hybrid Journal   (Followers: 10, SJR: 0.18, h-index: 13)
Amino Acids     Hybrid Journal   (Followers: 8, SJR: 1.362, h-index: 83)
AMS Review     Partially Free   (Followers: 4)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 5, SJR: 0.21, h-index: 37)
Analysis and Mathematical Physics     Hybrid Journal   (Followers: 4, SJR: 0.665, h-index: 7)
Analysis in Theory and Applications     Hybrid Journal  
Analysis of Verbal Behavior     Hybrid Journal   (Followers: 4)
Analytical and Bioanalytical Chemistry     Hybrid Journal   (Followers: 32, SJR: 1.096, h-index: 123)
Anatomical Science Intl.     Hybrid Journal   (Followers: 2, SJR: 0.301, h-index: 26)
Angewandte Schmerztherapie und Palliativmedizin     Hybrid Journal  
Angiogenesis     Hybrid Journal   (Followers: 3, SJR: 2.212, h-index: 69)
Animal Cognition     Hybrid Journal   (Followers: 13, SJR: 1.122, h-index: 55)
Annales françaises de médecine d'urgence     Hybrid Journal   (Followers: 1, SJR: 0.156, h-index: 4)
Annales Henri Poincaré     Hybrid Journal   (Followers: 3, SJR: 1.377, h-index: 32)
Annales mathématiques du Québec     Hybrid Journal   (Followers: 4)
Annali dell'Universita di Ferrara     Hybrid Journal   (SJR: 0.504, h-index: 14)
Annali di Matematica Pura ed Applicata     Hybrid Journal   (Followers: 1, SJR: 1.167, h-index: 26)
Annals of Behavioral Medicine     Hybrid Journal   (Followers: 10, SJR: 2.112, h-index: 98)
Annals of Biomedical Engineering     Hybrid Journal   (Followers: 18, SJR: 1.182, h-index: 94)
Annals of Combinatorics     Hybrid Journal   (Followers: 3, SJR: 0.849, h-index: 15)
Annals of Data Science     Hybrid Journal   (Followers: 8)
Annals of Dyslexia     Hybrid Journal   (Followers: 9, SJR: 0.857, h-index: 40)
Annals of Finance     Hybrid Journal   (Followers: 26, SJR: 0.686, h-index: 14)
Annals of Forest Science     Hybrid Journal   (Followers: 4, SJR: 0.929, h-index: 57)
Annals of Global Analysis and Geometry     Hybrid Journal   (Followers: 1, SJR: 1.136, h-index: 23)
Annals of Hematology     Hybrid Journal   (Followers: 13, SJR: 1.117, h-index: 62)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 6, SJR: 0.593, h-index: 42)
Annals of Microbiology     Hybrid Journal   (Followers: 9, SJR: 0.402, h-index: 26)
Annals of Nuclear Medicine     Hybrid Journal   (Followers: 5, SJR: 0.68, h-index: 45)
Annals of Operations Research     Hybrid Journal   (Followers: 8, SJR: 1.186, h-index: 78)
Annals of Regional Science     Hybrid Journal   (Followers: 7, SJR: 0.405, h-index: 42)
Annals of Software Engineering     Hybrid Journal   (Followers: 12)
Annals of Solid and Structural Mechanics     Hybrid Journal   (Followers: 9, SJR: 0.553, h-index: 8)
Annals of Surgical Oncology     Hybrid Journal   (Followers: 11, SJR: 1.902, h-index: 127)
Annals of Telecommunications     Hybrid Journal   (Followers: 7, SJR: 0.315, h-index: 25)
Annals of the Institute of Statistical Mathematics     Hybrid Journal   (Followers: 1, SJR: 0.931, h-index: 31)
Antonie van Leeuwenhoek     Hybrid Journal   (Followers: 5, SJR: 0.992, h-index: 87)
Apidologie     Hybrid Journal   (Followers: 4, SJR: 1.14, h-index: 57)
APOPTOSIS     Hybrid Journal   (Followers: 7, SJR: 1.554, h-index: 87)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2, SJR: 0.354, h-index: 27)
Applications of Mathematics     Hybrid Journal   (Followers: 1, SJR: 0.274, h-index: 20)
Applied Biochemistry and Biotechnology     Hybrid Journal   (Followers: 45, SJR: 0.575, h-index: 80)
Applied Biochemistry and Microbiology     Hybrid Journal   (Followers: 17, SJR: 0.267, h-index: 26)
Applied Categorical Structures     Hybrid Journal   (Followers: 2, SJR: 0.361, h-index: 21)
Applied Composite Materials     Hybrid Journal   (Followers: 45, SJR: 0.705, h-index: 35)
Applied Entomology and Zoology     Partially Free   (Followers: 2, SJR: 0.554, h-index: 34)
Applied Geomatics     Hybrid Journal   (Followers: 3, SJR: 0.323, h-index: 9)
Applied Geophysics     Hybrid Journal   (Followers: 7, SJR: 0.541, h-index: 13)
Applied Intelligence     Hybrid Journal   (Followers: 13, SJR: 0.777, h-index: 43)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 3, SJR: 0.358, h-index: 34)
Applied Mathematics & Optimization     Hybrid Journal   (Followers: 4, SJR: 0.955, h-index: 33)
Applied Mathematics - A J. of Chinese Universities     Hybrid Journal   (SJR: 0.275, h-index: 8)
Applied Mathematics and Mechanics     Hybrid Journal   (Followers: 4, SJR: 0.37, h-index: 26)
Applied Microbiology and Biotechnology     Hybrid Journal   (Followers: 61, SJR: 1.262, h-index: 161)
Applied Physics A     Hybrid Journal   (Followers: 8, SJR: 0.535, h-index: 121)
Applied Physics B: Lasers and Optics     Hybrid Journal   (Followers: 22, SJR: 0.983, h-index: 104)
Applied Psychophysiology and Biofeedback     Hybrid Journal   (Followers: 5, SJR: 0.677, h-index: 47)
Applied Research in Quality of Life     Hybrid Journal   (Followers: 10, SJR: 0.288, h-index: 15)
Applied Solar Energy     Hybrid Journal   (Followers: 16, SJR: 0.251, h-index: 6)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4, SJR: 0.351, h-index: 9)
Aquaculture Intl.     Hybrid Journal   (Followers: 21, SJR: 0.613, h-index: 40)
Aquarium Sciences and Conservation     Hybrid Journal   (Followers: 1)
Aquatic Ecology     Hybrid Journal   (Followers: 31, SJR: 0.646, h-index: 44)
Aquatic Geochemistry     Hybrid Journal   (Followers: 3, SJR: 0.764, h-index: 39)
Aquatic Sciences     Hybrid Journal   (Followers: 12, SJR: 1.172, h-index: 53)
Arabian J. for Science and Engineering     Hybrid Journal   (Followers: 5, SJR: 0.345, h-index: 20)
Arabian J. of Geosciences     Hybrid Journal   (Followers: 1, SJR: 0.417, h-index: 16)
Archaeological and Anthropological Sciences     Hybrid Journal   (Followers: 21, SJR: 1.056, h-index: 15)
Archaeologies     Hybrid Journal   (Followers: 12, SJR: 0.397, h-index: 13)
Archiv der Mathematik     Hybrid Journal   (SJR: 0.597, h-index: 29)
Archival Science     Hybrid Journal   (Followers: 51, SJR: 0.804, h-index: 22)
Archive for History of Exact Sciences     Hybrid Journal   (Followers: 7, SJR: 0.28, h-index: 15)
Archive for Mathematical Logic     Hybrid Journal   (Followers: 1, SJR: 0.946, h-index: 23)
Archive for Rational Mechanics and Analysis     Hybrid Journal   (SJR: 4.091, h-index: 66)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 4, SJR: 0.865, h-index: 40)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4, SJR: 2.841, h-index: 40)
Archives of Dermatological Research     Hybrid Journal   (Followers: 6, SJR: 0.9, h-index: 65)
Archives of Environmental Contamination and Toxicology     Hybrid Journal   (Followers: 10, SJR: 0.846, h-index: 84)
Archives of Gynecology and Obstetrics     Hybrid Journal   (Followers: 16, SJR: 0.695, h-index: 47)
Archives of Microbiology     Hybrid Journal   (Followers: 8, SJR: 0.702, h-index: 85)
Archives of Orthopaedic and Trauma Surgery     Hybrid Journal   (Followers: 8, SJR: 1.039, h-index: 56)
Archives of Osteoporosis     Hybrid Journal   (Followers: 2, SJR: 1.092, h-index: 13)
Archives of Sexual Behavior     Hybrid Journal   (Followers: 9, SJR: 1.198, h-index: 74)
Archives of Toxicology     Hybrid Journal   (Followers: 16, SJR: 1.595, h-index: 76)
Archives of Virology     Hybrid Journal   (Followers: 4, SJR: 1.086, h-index: 90)
Archives of Women's Mental Health     Hybrid Journal   (Followers: 13, SJR: 1.264, h-index: 50)
Archivio di Ortopedia e Reumatologia     Hybrid Journal  
Archivum Immunologiae et Therapiae Experimentalis     Hybrid Journal   (Followers: 2, SJR: 1.2, h-index: 42)
ArgoSpine News & J.     Hybrid Journal   (SJR: 0.102, h-index: 3)
Argumentation     Hybrid Journal   (Followers: 4, SJR: 0.295, h-index: 18)
Arid Ecosystems     Hybrid Journal   (Followers: 3)
Arkiv för Matematik     Hybrid Journal   (SJR: 0.948, h-index: 22)
Arnold Mathematical J.     Hybrid Journal   (Followers: 1)
Arthropod-Plant Interactions     Hybrid Journal   (Followers: 2, SJR: 0.797, h-index: 17)
Arthroskopie     Hybrid Journal   (Followers: 1, SJR: 0.145, h-index: 8)
Artificial Intelligence and Law     Hybrid Journal   (Followers: 8, SJR: 0.288, h-index: 25)
Artificial Intelligence Review     Hybrid Journal   (Followers: 15, SJR: 0.948, h-index: 48)
Artificial Life and Robotics     Hybrid Journal   (Followers: 8, SJR: 0.231, h-index: 14)
Asia Europe J.     Hybrid Journal   (Followers: 4, SJR: 0.247, h-index: 9)
Asia Pacific Education Review     Hybrid Journal   (Followers: 9, SJR: 0.371, h-index: 17)
Asia Pacific J. of Management     Hybrid Journal   (Followers: 11, SJR: 1.676, h-index: 50)
Asia-Pacific Education Researcher     Hybrid Journal   (Followers: 11, SJR: 0.353, h-index: 13)
Asia-Pacific Financial Markets     Hybrid Journal   (Followers: 2, SJR: 0.19, h-index: 15)
Asia-Pacific J. of Atmospheric Sciences     Hybrid Journal   (Followers: 20, SJR: 1.006, h-index: 14)
Asian Business & Management     Hybrid Journal   (Followers: 7, SJR: 0.41, h-index: 10)
Asian J. of Business Ethics     Hybrid Journal   (Followers: 7)
Asian J. of Criminology     Hybrid Journal   (Followers: 5, SJR: 0.263, h-index: 8)
AStA Advances in Statistical Analysis     Hybrid Journal   (Followers: 2, SJR: 0.681, h-index: 15)
AStA Wirtschafts- und Sozialstatistisches Archiv     Hybrid Journal   (Followers: 5, SJR: 0.195, h-index: 5)
ästhetische dermatologie & kosmetologie     Full-text available via subscription  
Astronomy and Astrophysics Review     Hybrid Journal   (Followers: 21, SJR: 4.511, h-index: 44)
Astronomy Letters     Hybrid Journal   (Followers: 19, SJR: 0.58, h-index: 30)
Astronomy Reports     Hybrid Journal   (Followers: 12, SJR: 0.473, h-index: 23)
Astrophysical Bulletin     Hybrid Journal   (Followers: 2, SJR: 0.469, h-index: 11)
Astrophysics     Hybrid Journal   (Followers: 22, SJR: 0.243, h-index: 11)

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Journal Cover Applied Intelligence
  [SJR: 0.777]   [H-I: 43]   [13 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1573-7497 - ISSN (Online) 0924-669X
   Published by Springer-Verlag Homepage  [2335 journals]
  • Attribute weighting for averaged one-dependence estimators
    • Authors: Zhong-Liang Xiang; Dae-Ki Kang
      Abstract: Averaged one-dependence estimators (AODE) is a type of supervised learning algorithm that relaxes the conditional independence assumption that governs standard naïve Bayes learning algorithms. AODE has demonstrated reasonable improvement in terms of classification performance when compared with a naïve Bayes learner. However, AODE does not consider the relationships between the super-parent attribute and other normal attributes. In this paper, we propose a novel method based on AODE that weighs the relationship between the attributes called weighted AODE (WAODE), which is an attribute weighting method that uses the conditional mutual information metric to rank the relations among the attributes. We have conducted experiments on University of California, Irvine (UCI) benchmark datasets and compared accuracies between AODE and our proposed learner. The experimental results in our paper show that WAODE exhibits higher accuracy performance than the original AODE.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0854-3
       
  • An efficient method for mining frequent sequential patterns using
           multi-Core processors
    • Authors: Bao Huynh; Bay Vo; Vaclav Snasel
      Abstract: The problem of mining frequent sequential patterns (FSPs) has attracted a great deal of research attention. Although there are many efficient algorithms for mining FSPs, the mining time is still high, especially for large or dense datasets. Parallel processing has been widely applied to improve processing speed for various problems. Some parallel algorithms have been proposed, but most of them have problems related to synchronization and load balancing. Based on a multi-core processor architecture, this paper proposes a load-balancing parallel approach called Parallel Dynamic Bit Vector Sequential Pattern Mining (pDBV-SPM) for mining FSPs from huge datasets using the dynamic bit vector data structure for fast determining support values. In the pDBV-SPM approach, the support count is sorted in ascending order before the set of frequent 1-sequences is partitioned into parts, each of which is assigned to a task on a processor so that most of the nodes in the leftmost branches will be infrequent and thus pruned during the search; this strategy helps to better balance the search tree. Experiments are conducted to verify the effectiveness of pDBV-SPM. The experimental results show that the proposed algorithm outperforms PIB-PRISM for mining FSPs in terms of mining time and memory usage.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0859-y
       
  • A mathematical model for solving fully fuzzy linear programming problem
           with trapezoidal fuzzy numbers
    • Authors: Sapan Kumar Das; T. Mandal; S. A. Edalatpanah
      Abstract: In this paper, an efficient method is introduced to solve fully fuzzy linear programming problems. The proposed method is derived from the multi-objective linear programming problem and lexicographic ordering method. Theoretical analysis for the proposed method has been provided. Moreover, some numerical experiments are given to show the preference of the proposed methods and are compared with some available methods.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0779-x
       
  • A novel immune dominance selection multi-objective optimization algorithm
           for solving multi-objective optimization problems
    • Abstract: In this paper, we propose a novel immune dominance selection multi-objective optimization algorithm (IDSMOA) to solve multi-objective numerical and engineering optimization problems in the real world. IDSMOA was inspired by the mechanism that controls how B cells and T cells differentiate, recombine, and mutate self-adjustably to produce new lymphocytes matching antigens with high affinity, then how lymphocytes cooperatively eliminate antigens. The main idea of IDSMOA is to promote 2 populations, population B and population T, to coevolve through an immune selection operator, immune clone operator, immune gen operator, and memory selection operator to produce satisfying Pareto front. Therefore, several operators enable IDSMOA to exploit and excavate the search space, and decrease the number of dominance resistant solutions (DRSs). We compared IDSMOA performance with 3 known multi-objective optimization algorithms and IDSMOA without the combination operator in simulation experiments optimizing 12 benchmark functions. Our simulations indicated that IDSMOA is a competitive optimization tool for multi-objective optimization problems.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0866-z
       
  • An efficient forecasting model based on an improved fuzzy time series and
           a modified group search optimizer
    • Authors: Chin-Ling Lee; Shye-Chorng Kuo; Cheng-Jian Lin
      Abstract: This paper presents a prediction model based on an improved fuzzy time series (IFTS) and a modified group search optimizer to effectively solve forecasting problems. IFTS can accurately predict whether subsequent predicted data will increase or decrease according to ratio value in the fuzzy logical relationship. In addition, the modified group search optimizer is used to adjust the length of an interval. The proposed prediction model is also used to forecast the enrollments of the University of Alabama the enrollments of a university of technology in central Taiwan, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) Experimental results show that the proposed model obtains the smallest prediction error than those of other methods.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0857-0
       
  • A novel disruption in biogeography-based optimization with application to
           optimal power flow problem
    • Authors: Jagdish Chand Bansal; Pushpa Farswan
      Abstract: Biogeography-based optimization (BBO) is an emerging meta-heuristic algorithm. Due to ease of implementation and very few user-dependent parameters, BBO gained popularity among researchers. The performance of BBO is highly dependent on its two operators, migration and mutation. The performance of BBO can be significantly improved by either modifying these operators or by introducing a new operator into it. This paper proposes a new operator, namely the disruption operator to improve the capability of exploration and exploitation in BBO. The proposed DisruptBBO (DBBO) has been tested on well-known benchmark problems and compared with various versions of BBO and other state-of-the-art metaheuristics. The experimental results and statistical analyses confirm the superior performance of the proposed DBBO in solving various nonlinear complex optimization problems. The proposed algorithm has also been applied to the optimal power flow optimization problem from the electrical engineering background.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0848-1
       
  • A complex-valued encoding wind driven optimization for the 0-1 knapsack
           problem
    • Authors: Yongquan Zhou; Zongfan Bao; Qifang Luo; Sen Zhang
      Abstract: This paper presents a complex-valued encoding wind driven optimization (CWDO) with a greedy strategy for the 0-1 knapsack problem. We introduce a complex-value encoding method, which can be viewed as an effective global optimization strategy, and a greedy strategy, which can be viewed as an enhanced local search strategy into wind driven optimization. These strategies increase the diversity of the population and avoid premature convergence. This paper presents three types of test cases for evaluation: standard, small-scale, and large-scale test cases. The experimental results show that the proposed algorithm is suitable for these three cases. Compared to the complex valued cuckoo search algorithm, greedy genetic algorithm, wind driven optimization, binary cuckoo search algorithm, bat algorithm and particle swarm optimization, the performance, stability, and robustness of the CWDO algorithm is better. The simulation results show that the CWDO algorithm is an effective and feasible method for solving the 0-1 knapsack problem.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0855-2
       
  • Speech translation system for english to dravidian languages
    • Authors: J. Sangeetha; S. Jothilakshmi
      Abstract: In this paper the Speech-to-Speech Translation (SST) system, which is mainly focused on translation from English to Dravidian languages (Tamil and Malayalam) has been proposed. Three major techniques involved in SST system are Automatic continuous speech recognition, machine translation, and text-to-speech synthesis system. In this paper automatic Continuous Speech Recognition (CSR) has been developed based on the Auto Associative Neural Network (AANN), Support Vector Machine (SVM) and Hidden Markov Model (HMM). The HMM yields better results compared with SVM and AANN. Hence the HMM based Speech recognizer for English language has been taken. We propose a hybrid Machine Translation (MT) system (combination of Rule based and Statistical) for converting English to Dravidian languages text. A syllable based concatenative Text To Speech Synthesis (TTS) for Tamil and Malayalam has been proposed. AANN based prosody prediction has been done for the Tamil language which is used to improve the naturalness and intelligibility. The domain is restricted to sentences that cover the announcements in the railway station, bus stop and airport. This work is framed a novel translation method for English to Dravidian languages. The improved performance of each module HMM based CSR, Hybrid MT and concatenative TTS increases the overall speech translation performance. This proposed speech translation system can be applied to English to any Indian languages if we train and create a parallel corpus for those languages.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0846-3
       
  • Fuzzy C-means for english sentiment classification in a distributed system
    • Authors: Vo Ngoc Phu; Nguyen Duy Dat; Vo Thi Ngoc Tran; Vo Thi Ngoc Chau; Tuan A. Nguyen
      Abstract: Sentiment classification plays a significant role in everyday life, in political activities, in activities relating to commodity production, and commercial activities. Finding a solution for the accurate and timely classification of emotions is a challenging task. In this research, we propose a new model for big data sentiment classification in the parallel network environment. Our proposed model uses the Fuzzy C-Means (FCM) method for English sentiment classification with Hadoop MAP (M) /REDUCE (R) in Cloudera. Cloudera is a parallel network environment. Our proposed model can classify the sentiments of millions of English documents in the parallel network environment. We tested our model using the testing data set (which comprised 25,000 English reviews, 12,500 being positive and 12,500 negative) and achieved 60.2 % accuracy. Our English training data set has 60,000 English sentences, comprising 30,000 positive English sentences and 30,000 negative English sentences.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0858-z
       
  • Attributes coupling based matrix factorization for item recommendation
    • Authors: Yonghong Yu; Can Wang; Hao Wang; Yang Gao
      Abstract: Recommender systems have attracted lots of attention since they alleviate the information overload problem for users. Matrix factorization is one of the most widely employed collaborative filtering techniques in the research of recommender systems due to its effectiveness and efficiency in dealing with very large user-item rating matrices. Recently, additional information, such as social network and user demographics, have been adopted by several recommendation algorithms to provide useful insights for matrix factorization techniques. However, most of them focus on dealing with the cold start user problem and ignore the cold start item problem. In addition, there are few suitable similarity measures for these content enhanced matrix factorization approaches to compute the similarity between categorical items. In this paper, we propose an attributes coupling based matrix factorization method by incorporating item-attribute information into the matrix factorization model as well as adopting coupled object similarity to capture the relationship among items. Item-attribute information is formed as an item relationship regularization term to constrain the process of matrix factorization. Experimental results on two real data sets show that our proposed method outperforms the state-of-the-art recommendation algorithms and can effectively cope with the cold start item problem when such item-attribute information is available.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0841-8
       
  • DSHMP-IOT: A distributed self healing movement prediction scheme for
           internet of things applications
    • Authors: Azadeh Zamanifar; Eslam Nazemi; Mojtaba Vahidi-Asl
      Abstract: The IOT infrastructure - IP-based mobile sensor network- makes it possible to provide two-directional communication between mobile sensors and the remote server. Mobility direction prediction is a major challenge in IP-based networks by which we can predict the next movement direction of moving objects carrying mobile node(s). In this paper, we have introduced a Distributed Self-Healing Movement Prediction scheme for IOT applications, so-called DSHMP-IOT, to predict movement direction of mobile IP-based sensors in a multi-user environment, such as a health-care system. This is the first time that an AI solution is applied to predict the direction of the mobile node(s) in an IP-based mobile network. The proposed scheme takes advantage of Hidden Semi-Markov Model (HSMM) to predict the movement direction with high accuracy and low overhead. The previous works for estimating the direction of a mobile node(s) in IP-based mobile networks are based on AOA, a hardware-specific method. The proposed scheme has several advantages. First, it eliminates the need for special hardware (directional antenna, an antenna array, etc.) which is required in AOA based methods. Second, it is not sensitive to noise, speed and sudden changing of movement direction which cause false positive movement direction prediction in AOA method. Third, in this context, it is the only work with self-healing capability whenever one or more static sensors fail(s). Fourth, it includes a recovery mechanism which prevents the mobile node from being disconnected in case of false prediction of our learning model. The simulation results show the superiority of our scheme regarding power consumption and hand-off delay, as well as packet loss, compared to similar approaches.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0849-0
       
  • A ν -twin support vector machine based regression with automatic
           accuracy control
    • Authors: Reshma Rastogi; Pritam Anand; Suresh Chandra
      Abstract: This paper presents an efficient ν-Twin Support Vector Machine Based Regression Model with Automatic Accuracy Control (ν-TWSVR). This ν-TWSVR model is motivated by the celebrated ν-SVR model (Schlkoff et al. 1998) and recently introduced 𝜖-TSVR model (Shao et al., Neural Comput Applic 23(1):175–185, 2013). The ν-TSVR model can automatically optimize the parameters 𝜖 1 and 𝜖 2 according to the structure of the data such that at most certain specified fraction ν 1(respectively ν 2) of data points contribute to the errors in up (respectively down) bound regressor. The ν-TWSVR formulation constructs a pair of optimization problems which are mathematically derived from a related ν-TWSVM formulation (Peng, Neural Netw 23(3):365–372, 2010) and making use of an important result of Bi and Bennett (Neurocomputing 55(1):79–108, 2003). The experimental results on artificial and UCI benchmark datasets show the efficacy of the proposed model in practice.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0860-5
       
  • Picture inference system: a new fuzzy inference system on picture fuzzy
           set
    • Authors: Le Hoang Son; Pham Van Viet; Pham Van Hai
      Abstract: In this paper, we propose a novel fuzzy inference system on picture fuzzy set called picture inference system (PIS) to enhance inference performance of the traditional fuzzy inference system. In PIS, the positive, neutral and negative degrees of the picture fuzzy set are computed using the membership graph that is the combination of three Gaussian functions with a common center and different widths expressing a visual view of degrees. Then, the positive and negative defuzzification values, synthesized from three degrees of the picture fuzzy set, are used to generate crisp outputs. Learning in PIS including training centers, widths, scales and defuzzification parameters is also discussed. The system is adapted for all architectures such as the Mamdani, the Sugeno and the Tsukamoto fuzzy inferences. Experimental results on benchmark UCI Machine Learning Repository datasets and an example in control theory - the Lorenz system are examined to verify the advantages of PIS.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0856-1
       
  • A modified combination rule in generalized evidence theory
    • Authors: Wen Jiang; Jun Zhan
      Abstract: Dempster-Shafer evidence theory is an efficient tool used in knowledge reasoning and decision-making under uncertain environments. Conflict management is an open issue in Dempster-Shafer evidence theory. There is no good practice that can be generally accepted until the presence of generalized evidence theory (GET). GET addresses conflict management in an open world, where the frame of discernment (FOD) is incomplete since uncertainty and lacking knowledge. With the in-depth study, however, the original generalized combination rule (GCR) still has its issue. As an example, based on the original GCR, the system judges whether the FOD is complete or not even though the GBPAs clearly indicate that the proposition is outside of FOD. In this paper, we proposed a modified generalized combination rule (mGCR) in the framework of GET. The mGCR satisfies all properties of GCR in GET, illustrating and modeling the real world more reasonably than the original. Numerical examples demonstrate that mGCR combines GBPAs effectively and has more distinct geometric and physical meaning than the original GCR. Several experiments using real data sets are presented at the end of this paper to evaluate the effectiveness of mGCR.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0851-6
       
  • Correlations among three performance indices with decision about training
           parameters based on energy variation in a robot’s part micro-assembly
           methodologies
    • Authors: Changman Son
      Abstract: Correlations among three performance indices, including the probability of success, fuzzy entropy, and system energy, with a decision about training parameters based on the energy variation of a neural network system are newly introduced. Methodologies are used based on the robot’s part micro-assembly. The enhancement of efficiency in the performance of the robot’s part-in-assembly hole (target) task implies the maximization of the probability of success as well as the minimization of fuzzy entropy and system energy in the execution of the associated task. Two part micro-assembly algorithms are introduced that bring a part from an initial position to a target for the purposes of part-mating and storage. The two part micro-assembly algorithms are then compared through simulations and chosen specific criteria. Also, the novelty of the methodologies used in this paper is described. In the 1st algorithm, a grid based on a neural network categorizes an assembly type which is fed to a fuzzy coordinator that places the part at the selected position, where it is ready to mate successfully with a target. The energy variation of the neural network system is used as a new tool to find better values of training parameters, such as the learning rate, the number of nodes in a hidden layer, and the momentum. The 2nd algorithm is a fuzziness-minimizing learning algorithm that assists the robot to adapt to its unfamiliar workspace. The 2nd algorithm then finds a plan with the lowest degree of uncertainty among the generated feasible plans composed of a sequence of coordinates from the part’s arbitrary starting to the target positions. The results obtained by the two algorithms show that the three performance indices reach the desirable states such that the fuzzy entropy and the system energy are minimized and the probability of success is simultaneously maximized as trainings are successively reiterated. The results also show that the three performance indices can be a useful tool to estimate the performance results of a robot’s various types of part assemblies.
      PubDate: 2017-04-01
      DOI: 10.1007/s10489-016-0847-2
       
  • Improved multi-objective particle swarm optimization algorithm for
           optimizing watermark strength in color image watermarking
    • Authors: Nitin Saxena; K. K. Mishra
      Abstract: A variant of Multi-Objective Particle Swarm Optimization (MOPSO), named as MOPSOtridist, is proposed in this paper. To improve the performance of existing MOPSO algorithms, new leader selection strategy and personal best (pbest) replacement scheme is introduced in this variant. In existing MOPSO algorithms, selection of leader is done only on the basis of particle’s current position and particle movement history is not taken into account. In MOPSOtridist, this information is used by selecting the most appropriate leader from the archive which has minimum distance from the region where the particle had visited recently. The proposed leader selection strategy efficiently explores the whole Pareto front by attracting the distinct regions explored by different particles. Additionally, a pbest replacement scheme is introduced to handle its stagnation at local optimal solutions by replacing the stagnated pbest of the particle with a new archive member, which is at maximum distance from the particle’s local optimal solutions. This will add diversity and forces those particles to explore other regions. For measuring the distance between particle’s regions and archive member, triangular distance (tridist) is used. The proposed MOPSOtridist algorithm along with other widely known variants of MOPSO, are tested exhaustively over two series of benchmark functions ZDT and DTLZ. The experiment results show that the proposed algorithm outperforms other MOPSO algorithms significantly in terms of standard performance metrics. Further, the proposed variant MOPSOtridist is applied to digital image watermarking problem for colour images in RGB colour space. Results demonstrate that MOPSOtridist efficiently produce optimal values of watermark strength to achieve good trade-offs between imperceptibility and robustness objectives.
      PubDate: 2017-03-15
      DOI: 10.1007/s10489-016-0889-5
       
  • Image-format-independent tampered image detection based on overlapping
           concurrent directional patterns and neural networks
    • Authors: Meng-Luen Wu; Chin-Shyurng Fahn; Yi-Fan Chen
      Abstract: With the advancement of photo editing software, digital documents can easily be altered, which causes some legal issues. This paper proposes an image authentication method, which determines whether an image is authentic. Unlike many existing methods that only work with images in the JPEG format, the proposed method is image format independent, implying that it works with both noncompressed images and images in all compression formats. To improve the authentication accuracy, some strategies, such as overlapping image blocks only on concurrent directions, using a two-scale local binary pattern operator, and choosing the mean deviation instead of the standard deviation, are applied. A back-propagation neural network (BPNN) is used instead of support vector machines (SVMs) for classification to make online learning easier and achieve higher accuracy. In our experiments, we used the CASIA Database (CASIA TIDE v1.0) of compressed images and the Columbia University Digital Video Multimedia (DVMM) dataset of uncompressed images to evaluate our image authentication method. This benchmark dataset includes two types of image tampering, namely image splicing and copy–move forgery. Experiments were performed using both the SVM and BPNN classifiers with various parameters. We determined that the BPNN achieved a higher accuracy of up to 97.26 %.
      PubDate: 2017-03-13
      DOI: 10.1007/s10489-017-0893-4
       
  • A fast algorithm for mining high average-utility itemsets
    • Authors: Jerry Chun-Wei Lin; Shifeng Ren; Philippe Fournier-Viger; Tzung-Pei Hong; Ja-Hwung Su; Bay Vo
      Abstract: Mining high-utility itemsets (HUIs) in transactional databases has become a very popular research topic in recent years. A popular variation of the problem of HUI mining is to discover high average-utility itemsets (HAUIs), where an alternative measure called the average-utility is used to evaluate the utility of itemsets by considering their lengths. Albeit, HAUI mining has been studied extensively, current algorithms often consume a large amount of memory and have long execution times, due to the large search space and the usage of loose upper bounds to estimate the average-utilities of itemsets. In this paper, we present a more efficient algorithm for HAUI mining, which includes three pruning strategies to provide a tighter upper bound on the average-utilities of itemsets, and thus reduce the search space more effectively to decrease the runtime. The first pruning strategy utilizes relationships between item pairs to reduce the search space for itemsets containing three or more items. The second pruning strategy provides a tighter upper bound on the average-utilities of itemsets to prune unpromising candidates early. The third strategy reduces the time for constructing the average-utility-list structures for itemsets, which is used to calculate their upper bounds. Substantial experiments conducted on both real-life and synthetic datasets show that the proposed algorithm with three pruning strategies can efficiently and effectively reduce the search space for mining HAUIs, when compared to the state-of-the-art algorithms, in terms of runtime, number of candidates, memory usage, performance of the pruning strategies and scalability.
      PubDate: 2017-03-11
      DOI: 10.1007/s10489-017-0896-1
       
  • Adaptive pattern search for large-scale optimization
    • Authors: Vincent Gardeux; Mahamed G. H. Omran; Rachid Chelouah; Patrick Siarry; Fred Glover
      Abstract: The emergence of high-dimensional data requires the design of new optimization methods. Indeed, conventional optimization methods require improvements, hybridization, or parameter tuning in order to operate in spaces of high dimensions. In this paper, we present a new adaptive variant of a pattern search algorithm to solve global optimization problems exhibiting such a character. The proposed method has no parameters visible to the user and the default settings, determined by almost no a priori experimentation, are highly robust on the tested datasets. The algorithm is evaluated and compared with 11 state-of-the-art methods on 20 benchmark functions of 1000 dimensions from the CEC’2010 competition. The results show that this approach obtains good performances compared to the other methods tested.
      PubDate: 2017-03-11
      DOI: 10.1007/s10489-017-0901-8
       
  • Erratum to: A mathematical model for solving fully fuzzy linear
           programming problem with trapezoidal fuzzy numbers
    • Authors: Sapan Kumar Das; T. Mandal; S. A. Edalatpanah
      PubDate: 2017-03-02
      DOI: 10.1007/s10489-017-0923-2
       
 
 
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