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Publisher: Emerald   (Total: 357 journals)

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Showing 1 - 200 of 357 Journals sorted alphabetically
A Life in the Day     Hybrid Journal   (Followers: 12)
Academia Revista Latinoamericana de Administraci√≥n     Open Access   (Followers: 2, SJR: 0.178, CiteScore: 1)
Accounting Auditing & Accountability J.     Hybrid Journal   (Followers: 33, SJR: 1.71, CiteScore: 3)
Accounting Research J.     Hybrid Journal   (Followers: 25, SJR: 0.144, CiteScore: 0)
Accounting, Auditing and Accountability J.     Hybrid Journal   (Followers: 27, SJR: 2.187, CiteScore: 4)
Advances in Accounting Education     Hybrid Journal   (Followers: 18, SJR: 0.279, CiteScore: 0)
Advances in Appreciative Inquiry     Hybrid Journal   (Followers: 1, SJR: 0.451, CiteScore: 1)
Advances in Autism     Hybrid Journal   (Followers: 33, SJR: 0.222, CiteScore: 1)
Advances in Dual Diagnosis     Hybrid Journal   (Followers: 46, SJR: 0.21, CiteScore: 1)
Advances in Gender Research     Full-text available via subscription   (Followers: 5, SJR: 0.16, CiteScore: 0)
Advances in Intl. Marketing     Full-text available via subscription   (Followers: 6)
Advances in Mental Health and Intellectual Disabilities     Hybrid Journal   (Followers: 84, SJR: 0.296, CiteScore: 0)
Advances in Mental Health and Learning Disabilities     Hybrid Journal   (Followers: 30)
African J. of Economic and Management Studies     Hybrid Journal   (Followers: 10, SJR: 0.216, CiteScore: 1)
Agricultural Finance Review     Hybrid Journal   (Followers: 1, SJR: 0.406, CiteScore: 1)
Aircraft Engineering and Aerospace Technology     Hybrid Journal   (Followers: 225, SJR: 0.354, CiteScore: 1)
American J. of Business     Hybrid Journal   (Followers: 20)
Annals in Social Responsibility     Full-text available via subscription  
Anti-Corrosion Methods and Materials     Hybrid Journal   (Followers: 11, SJR: 0.235, CiteScore: 1)
Arts and the Market     Hybrid Journal   (Followers: 9)
Asia Pacific J. of Innovation and Entrepreneurship     Open Access   (Followers: 1)
Asia Pacific J. of Marketing and Logistics     Hybrid Journal   (Followers: 8, SJR: 0.425, CiteScore: 1)
Asia-Pacific J. of Business Administration     Hybrid Journal   (Followers: 6, SJR: 0.234, CiteScore: 1)
Asian Association of Open Universities J.     Open Access   (Followers: 1)
Asian Education and Development Studies     Hybrid Journal   (Followers: 6, SJR: 0.233, CiteScore: 1)
Asian J. of Accounting Research     Open Access  
Asian J. on Quality     Hybrid Journal   (Followers: 3)
Asian Review of Accounting     Hybrid Journal   (Followers: 2, SJR: 0.222, CiteScore: 1)
Aslib J. of Information Management     Hybrid Journal   (Followers: 32, SJR: 0.725, CiteScore: 2)
Aslib Proceedings     Hybrid Journal   (Followers: 318)
Assembly Automation     Hybrid Journal   (Followers: 2, SJR: 0.603, CiteScore: 2)
Baltic J. of Management     Hybrid Journal   (Followers: 4, SJR: 0.309, CiteScore: 1)
Benchmarking : An Intl. J.     Hybrid Journal   (Followers: 11, SJR: 0.559, CiteScore: 2)
British Food J.     Hybrid Journal   (Followers: 17, SJR: 0.5, CiteScore: 2)
Built Environment Project and Asset Management     Hybrid Journal   (Followers: 15, SJR: 0.46, CiteScore: 1)
Business Process Re-engineering & Management J.     Hybrid Journal   (Followers: 8)
Business Strategy Series     Hybrid Journal   (Followers: 7)
Career Development Intl.     Hybrid Journal   (Followers: 18, SJR: 0.527, CiteScore: 2)
China Agricultural Economic Review     Hybrid Journal   (Followers: 2, SJR: 0.31, CiteScore: 1)
China Finance Review Intl.     Hybrid Journal   (Followers: 6, SJR: 0.245, CiteScore: 0)
Chinese Management Studies     Hybrid Journal   (Followers: 4, SJR: 0.278, CiteScore: 1)
Circuit World     Hybrid Journal   (Followers: 16, SJR: 0.246, CiteScore: 1)
Collection and Curation     Hybrid Journal   (Followers: 12, SJR: 0.296, CiteScore: 1)
COMPEL: The Intl. J. for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3, SJR: 0.22, CiteScore: 1)
Competitiveness Review : An Intl. Business J. incorporating J. of Global Competitiveness     Hybrid Journal   (Followers: 5, SJR: 0.274, CiteScore: 1)
Construction Innovation: Information, Process, Management     Hybrid Journal   (Followers: 14, SJR: 0.731, CiteScore: 2)
Corporate Communications An Intl. J.     Hybrid Journal   (Followers: 8, SJR: 0.453, CiteScore: 1)
Corporate Governance Intl. J. of Business in Society     Hybrid Journal   (Followers: 6, SJR: 0.336, CiteScore: 1)
Critical Perspectives on Intl. Business     Hybrid Journal   (SJR: 0.378, CiteScore: 1)
Cross Cultural & Strategic Management     Hybrid Journal   (Followers: 9, SJR: 0.504, CiteScore: 2)
Data Technologies and Applications     Hybrid Journal   (Followers: 335, SJR: 0.355, CiteScore: 1)
Development and Learning in Organizations     Hybrid Journal   (Followers: 8, SJR: 0.138, CiteScore: 0)
Digital Library Perspectives     Hybrid Journal   (Followers: 33, SJR: 0.341, CiteScore: 1)
Direct Marketing An Intl. J.     Hybrid Journal   (Followers: 6)
Disaster Prevention and Management     Hybrid Journal   (Followers: 21, SJR: 0.47, CiteScore: 1)
Drugs and Alcohol Today     Hybrid Journal   (Followers: 154, SJR: 0.245, CiteScore: 1)
Education + Training     Hybrid Journal   (Followers: 25)
Education, Business and Society : Contemporary Middle Eastern Issues     Hybrid Journal   (Followers: 2, SJR: 1.707, CiteScore: 3)
Emerald Emerging Markets Case Studies     Hybrid Journal   (Followers: 1)
Employee Relations     Hybrid Journal   (Followers: 7, SJR: 0.551, CiteScore: 2)
Engineering Computations     Hybrid Journal   (Followers: 3, SJR: 0.444, CiteScore: 1)
Engineering, Construction and Architectural Management     Hybrid Journal   (Followers: 10, SJR: 0.653, CiteScore: 2)
English Teaching: Practice & Critique     Hybrid Journal   (SJR: 0.417, CiteScore: 1)
Equal Opportunities Intl.     Hybrid Journal   (Followers: 3)
Equality, Diversity and Inclusion : An Intl. J.     Hybrid Journal   (Followers: 18, SJR: 0.5, CiteScore: 1)
EuroMed J. of Business     Hybrid Journal   (Followers: 1, SJR: 0.26, CiteScore: 1)
European Business Review     Hybrid Journal   (Followers: 11, SJR: 0.585, CiteScore: 3)
European J. of Innovation Management     Hybrid Journal   (Followers: 25, SJR: 0.454, CiteScore: 2)
European J. of Management and Business Economics     Open Access   (Followers: 2, SJR: 0.239, CiteScore: 1)
European J. of Marketing     Hybrid Journal   (Followers: 21, SJR: 0.971, CiteScore: 2)
European J. of Training and Development     Hybrid Journal   (Followers: 13, SJR: 0.477, CiteScore: 1)
Evidence-based HRM     Hybrid Journal   (Followers: 5, SJR: 0.537, CiteScore: 1)
Facilities     Hybrid Journal   (Followers: 4, SJR: 0.503, CiteScore: 2)
Foresight     Hybrid Journal   (Followers: 8, SJR: 0.34, CiteScore: 1)
Gender in Management : An Intl. J.     Hybrid Journal   (Followers: 19, SJR: 0.412, CiteScore: 1)
Global Knowledge, Memory and Communication     Hybrid Journal   (Followers: 1001, SJR: 0.261, CiteScore: 1)
Grey Systems : Theory and Application     Hybrid Journal   (Followers: 1)
Health Education     Hybrid Journal   (Followers: 2, SJR: 0.421, CiteScore: 1)
Higher Education Evaluation and Development     Open Access   (Followers: 5)
Higher Education, Skills and Work-based Learning     Hybrid Journal   (Followers: 51, SJR: 0.426, CiteScore: 1)
History of Education Review     Hybrid Journal   (Followers: 12, SJR: 0.26, CiteScore: 0)
Housing, Care and Support     Hybrid Journal   (Followers: 9, SJR: 0.171, CiteScore: 0)
Human Resource Management Intl. Digest     Hybrid Journal   (Followers: 20, SJR: 0.129, CiteScore: 0)
IMP J.     Hybrid Journal  
Indian Growth and Development Review     Hybrid Journal   (SJR: 0.174, CiteScore: 0)
Industrial and Commercial Training     Hybrid Journal   (Followers: 5, SJR: 0.301, CiteScore: 1)
Industrial Lubrication and Tribology     Hybrid Journal   (Followers: 7, SJR: 0.334, CiteScore: 1)
Industrial Management & Data Systems     Hybrid Journal   (Followers: 7, SJR: 0.904, CiteScore: 3)
Industrial Robot An Intl. J.     Hybrid Journal   (Followers: 2, SJR: 0.318, CiteScore: 1)
Info     Hybrid Journal   (Followers: 1)
Information and Computer Security     Hybrid Journal   (Followers: 21, SJR: 0.307, CiteScore: 1)
Information Technology & People     Hybrid Journal   (Followers: 45, SJR: 0.671, CiteScore: 2)
Innovation & Management Review     Open Access  
Interactive Technology and Smart Education     Hybrid Journal   (Followers: 12, SJR: 0.191, CiteScore: 1)
Interlending & Document Supply     Hybrid Journal   (Followers: 63)
Internet Research     Hybrid Journal   (Followers: 37, SJR: 1.645, CiteScore: 5)
Intl. J. for Lesson and Learning Studies     Hybrid Journal   (Followers: 4, SJR: 0.324, CiteScore: 1)
Intl. J. for Researcher Development     Hybrid Journal   (Followers: 10)
Intl. J. of Accounting and Information Management     Hybrid Journal   (Followers: 9, SJR: 0.275, CiteScore: 1)
Intl. J. of Bank Marketing     Hybrid Journal   (Followers: 9, SJR: 0.654, CiteScore: 3)
Intl. J. of Climate Change Strategies and Management     Hybrid Journal   (Followers: 17, SJR: 0.353, CiteScore: 1)
Intl. J. of Clothing Science and Technology     Hybrid Journal   (Followers: 8, SJR: 0.318, CiteScore: 1)
Intl. J. of Commerce and Management     Hybrid Journal   (Followers: 1)
Intl. J. of Conflict Management     Hybrid Journal   (Followers: 15, SJR: 0.362, CiteScore: 1)
Intl. J. of Contemporary Hospitality Management     Hybrid Journal   (Followers: 14, SJR: 1.452, CiteScore: 4)
Intl. J. of Culture Tourism and Hospitality Research     Hybrid Journal   (Followers: 20, SJR: 0.339, CiteScore: 1)
Intl. J. of Development Issues     Hybrid Journal   (Followers: 9, SJR: 0.139, CiteScore: 0)
Intl. J. of Disaster Resilience in the Built Environment     Hybrid Journal   (Followers: 6, SJR: 0.387, CiteScore: 1)
Intl. J. of Educational Management     Hybrid Journal   (Followers: 6, SJR: 0.559, CiteScore: 1)
Intl. J. of Emergency Services     Hybrid Journal   (Followers: 9, SJR: 0.201, CiteScore: 1)
Intl. J. of Emerging Markets     Hybrid Journal   (Followers: 4, SJR: 0.474, CiteScore: 2)
Intl. J. of Energy Sector Management     Hybrid Journal   (Followers: 2, SJR: 0.349, CiteScore: 1)
Intl. J. of Entrepreneurial Behaviour & Research     Hybrid Journal   (Followers: 5, SJR: 0.629, CiteScore: 2)
Intl. J. of Ethics and Systems     Hybrid Journal   (Followers: 3, SJR: 0.333, CiteScore: 1)
Intl. J. of Event and Festival Management     Hybrid Journal   (Followers: 7, SJR: 0.388, CiteScore: 1)
Intl. J. of Gender and Entrepreneurship     Hybrid Journal   (Followers: 7, SJR: 0.445, CiteScore: 1)
Intl. J. of Health Care Quality Assurance     Hybrid Journal   (Followers: 13, SJR: 0.358, CiteScore: 1)
Intl. J. of Health Governance     Hybrid Journal   (Followers: 26, SJR: 0.247, CiteScore: 1)
Intl. J. of Housing Markets and Analysis     Hybrid Journal   (Followers: 9, SJR: 0.211, CiteScore: 1)
Intl. J. of Human Rights in Healthcare     Hybrid Journal   (Followers: 6, SJR: 0.205, CiteScore: 0)
Intl. J. of Information and Learning Technology     Hybrid Journal   (Followers: 8, SJR: 0.226, CiteScore: 1)
Intl. J. of Innovation Science     Hybrid Journal   (Followers: 12, SJR: 0.197, CiteScore: 1)
Intl. J. of Intelligent Computing and Cybernetics     Hybrid Journal   (Followers: 3, SJR: 0.214, CiteScore: 1)
Intl. J. of Intelligent Unmanned Systems     Hybrid Journal   (Followers: 4)
Intl. J. of Islamic and Middle Eastern Finance and Management     Hybrid Journal   (Followers: 10, SJR: 0.375, CiteScore: 1)
Intl. J. of Law and Management     Hybrid Journal   (Followers: 2, SJR: 0.217, CiteScore: 1)
Intl. J. of Leadership in Public Services     Hybrid Journal   (Followers: 28)
Intl. J. of Lean Six Sigma     Hybrid Journal   (Followers: 8, SJR: 0.802, CiteScore: 3)
Intl. J. of Logistics Management     Hybrid Journal   (Followers: 10, SJR: 0.71, CiteScore: 2)
Intl. J. of Managerial Finance     Hybrid Journal   (Followers: 5, SJR: 0.203, CiteScore: 1)
Intl. J. of Managing Projects in Business     Hybrid Journal   (Followers: 3, SJR: 0.36, CiteScore: 2)
Intl. J. of Manpower     Hybrid Journal   (Followers: 2, SJR: 0.365, CiteScore: 1)
Intl. J. of Mentoring and Coaching in Education     Hybrid Journal   (Followers: 29, SJR: 0.426, CiteScore: 1)
Intl. J. of Migration, Health and Social Care     Hybrid Journal   (Followers: 12, SJR: 0.307, CiteScore: 1)
Intl. J. of Numerical Methods for Heat & Fluid Flow     Hybrid Journal   (Followers: 11, SJR: 0.697, CiteScore: 3)
Intl. J. of Operations & Production Management     Hybrid Journal   (Followers: 21, SJR: 2.052, CiteScore: 4)
Intl. J. of Organization Theory and Behavior     Hybrid Journal  
Intl. J. of Organizational Analysis     Hybrid Journal   (Followers: 4, SJR: 0.268, CiteScore: 1)
Intl. J. of Pervasive Computing and Communications     Hybrid Journal   (Followers: 3, SJR: 0.138, CiteScore: 1)
Intl. J. of Pharmaceutical and Healthcare Marketing     Hybrid Journal   (Followers: 5, SJR: 0.25, CiteScore: 1)
Intl. J. of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 11, SJR: 1.821, CiteScore: 4)
Intl. J. of Prisoner Health     Hybrid Journal   (Followers: 7, SJR: 0.303, CiteScore: 1)
Intl. J. of Productivity and Performance Management     Hybrid Journal   (Followers: 8, SJR: 0.578, CiteScore: 2)
Intl. J. of Public Sector Management     Hybrid Journal   (Followers: 32, SJR: 0.438, CiteScore: 1)
Intl. J. of Quality & Reliability Management     Hybrid Journal   (Followers: 8, SJR: 0.492, CiteScore: 2)
Intl. J. of Quality and Service Sciences     Hybrid Journal   (Followers: 2, SJR: 0.309, CiteScore: 1)
Intl. J. of Retail & Distribution Management     Hybrid Journal   (Followers: 6, SJR: 0.742, CiteScore: 3)
Intl. J. of Service Industry Management     Hybrid Journal   (Followers: 2)
Intl. J. of Social Economics     Hybrid Journal   (Followers: 5, SJR: 0.225, CiteScore: 1)
Intl. J. of Sociology and Social Policy     Hybrid Journal   (Followers: 55, SJR: 0.3, CiteScore: 1)
Intl. J. of Sports Marketing and Sponsorship     Hybrid Journal   (Followers: 1, SJR: 0.269, CiteScore: 1)
Intl. J. of Structural Integrity     Hybrid Journal   (Followers: 2, SJR: 0.228, CiteScore: 0)
Intl. J. of Sustainability in Higher Education     Hybrid Journal   (Followers: 14, SJR: 0.502, CiteScore: 2)
Intl. J. of Tourism Cities     Hybrid Journal   (Followers: 2, SJR: 0.502, CiteScore: 0)
Intl. J. of Web Information Systems     Hybrid Journal   (Followers: 4, SJR: 0.186, CiteScore: 1)
Intl. J. of Wine Business Research     Hybrid Journal   (Followers: 8, SJR: 0.562, CiteScore: 2)
Intl. J. of Workplace Health Management     Hybrid Journal   (Followers: 10, SJR: 0.303, CiteScore: 1)
Intl. Marketing Review     Hybrid Journal   (Followers: 15, SJR: 0.895, CiteScore: 3)
Irish J. of Occupational Therapy     Open Access   (Followers: 12)
ISRA Intl. J. of Islamic Finance     Open Access   (Followers: 1)
J. for Multicultural Education     Hybrid Journal   (Followers: 1, SJR: 0.237, CiteScore: 1)
J. of Accounting & Organizational Change     Hybrid Journal   (Followers: 6, SJR: 0.301, CiteScore: 1)
J. of Accounting in Emerging Economies     Hybrid Journal   (Followers: 9)
J. of Adult Protection, The     Hybrid Journal   (Followers: 16, SJR: 0.314, CiteScore: 1)
J. of Advances in Management Research     Hybrid Journal   (Followers: 2)
J. of Aggression, Conflict and Peace Research     Hybrid Journal   (Followers: 47, SJR: 0.222, CiteScore: 1)
J. of Agribusiness in Developing and Emerging Economies     Hybrid Journal   (SJR: 0.108, CiteScore: 0)
J. of Applied Accounting Research     Hybrid Journal   (Followers: 18, SJR: 0.227, CiteScore: 1)
J. of Applied Research in Higher Education     Hybrid Journal   (Followers: 52, SJR: 0.2, CiteScore: 0)
J. of Asia Business Studies     Hybrid Journal   (Followers: 2, SJR: 0.245, CiteScore: 1)
J. of Assistive Technologies     Hybrid Journal   (Followers: 20)
J. of Business & Industrial Marketing     Hybrid Journal   (Followers: 10, SJR: 0.652, CiteScore: 2)
J. of Business Strategy     Hybrid Journal   (Followers: 12, SJR: 0.333, CiteScore: 1)
J. of Capital Markets Studies     Open Access  
J. of Centrum Cathedra     Open Access  
J. of Children's Services     Hybrid Journal   (Followers: 5, SJR: 0.243, CiteScore: 1)
J. of Chinese Economic and Foreign Trade Studies     Hybrid Journal   (Followers: 2, SJR: 0.2, CiteScore: 0)
J. of Chinese Entrepreneurship     Hybrid Journal   (Followers: 4)
J. of Chinese Human Resource Management     Hybrid Journal   (Followers: 8, SJR: 0.173, CiteScore: 1)
J. of Communication Management     Hybrid Journal   (Followers: 6, SJR: 0.625, CiteScore: 1)
J. of Consumer Marketing     Hybrid Journal   (Followers: 20, SJR: 0.664, CiteScore: 2)
J. of Corporate Real Estate     Hybrid Journal   (Followers: 3, SJR: 0.368, CiteScore: 1)
J. of Criminal Psychology     Hybrid Journal   (Followers: 147, SJR: 0.268, CiteScore: 1)
J. of Criminological Research, Policy and Practice     Hybrid Journal   (Followers: 50, SJR: 0.254, CiteScore: 1)
J. of Cultural Heritage Management and Sustainable Development     Hybrid Journal   (Followers: 9, SJR: 0.257, CiteScore: 1)
J. of Defense Analytics and Logistics     Open Access  
J. of Documentation     Hybrid Journal   (Followers: 206, SJR: 0.613, CiteScore: 1)
J. of Economic and Administrative Sciences     Hybrid Journal   (Followers: 2)
J. of Economic Studies     Hybrid Journal   (Followers: 5, SJR: 0.733, CiteScore: 1)
J. of Economics, Finance and Administrative Science     Open Access   (Followers: 2, SJR: 0.217, CiteScore: 1)
J. of Educational Administration     Hybrid Journal   (Followers: 9, SJR: 1.252, CiteScore: 2)
J. of Enabling Technologies     Hybrid Journal   (Followers: 11, SJR: 0.369, CiteScore: 1)
J. of Engineering, Design and Technology     Hybrid Journal   (Followers: 16, SJR: 0.212, CiteScore: 1)
J. of Enterprise Information Management     Hybrid Journal   (Followers: 4, SJR: 0.827, CiteScore: 4)
J. of Enterprising Communities People and Places in the Global Economy     Hybrid Journal   (Followers: 1, SJR: 0.281, CiteScore: 1)
J. of Entrepreneurship and Public Policy     Hybrid Journal   (Followers: 8, SJR: 0.262, CiteScore: 1)
J. of European Industrial Training     Hybrid Journal   (Followers: 2)
J. of European Real Estate Research     Hybrid Journal   (Followers: 3, SJR: 0.268, CiteScore: 1)
J. of Facilities Management     Hybrid Journal   (Followers: 6, SJR: 0.33, CiteScore: 1)
J. of Family Business Management     Hybrid Journal   (Followers: 7)

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Similar Journals
Journal Cover
International Journal of Intelligent Computing and Cybernetics
Journal Prestige (SJR): 0.214
Citation Impact (citeScore): 1
Number of Followers: 3  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1756-378X
Published by Emerald Homepage  [357 journals]
  • A hybrid genetic algorithm for multi-objective flexible job shop
           scheduling problem considering transportation time
    • Pages: 154 - 174
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 12, Issue 2, Page 154-174, June 2019.
      Purpose Flexible job-shop scheduling is significant for different manufacturing industries nowadays. Moreover, consideration of transportation time during scheduling makes it more practical and useful. The purpose of this paper is to investigate multi-objective flexible job-shop scheduling problem (MOFJSP) considering transportation time. Design/methodology/approach A hybrid genetic algorithm (GA) approach is integrated with simulated annealing to solve the MOFJSP considering transportation time, and an external elitism memory library is employed as a knowledge library to direct GA search into the region of better performance. Findings The performance of the proposed algorithm is tested on different MOFJSP taken from literature. Experimental results show that proposed algorithm performs better than the original GA in terms of quality of solution and distribution of the solution, especially when the number of jobs and the flexibility of the machine increase. Originality/value Most of existing studies have not considered the transportation time during scheduling of jobs. The transportation time is significantly desired to be included in the FJSP when the time of transportation of jobs has significant impact on the completion time of jobs. Meanwhile, GA is one of primary algorithms extensively used to address MOFJSP in literature. However, to solve the MOFJSP, the original GA has a possibility to get a premature convergence and it has a slow convergence speed. To overcome these problems, a new hybrid GA is developed in this paper.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-05-15T10:14:47Z
      DOI: 10.1108/IJICC-10-2018-0136
       
  • Application of quasi-oppositional symbiotic organisms search based extreme
           learning machine for stock market prediction
    • Pages: 175 - 193
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 12, Issue 2, Page 175-193, June 2019.
      Purpose Forecasting of stock indices is a challenging issue because stock data are dynamic, non-linear and uncertain in nature. Selection of an accurate forecasting model is very much essential to predict the next-day closing prices of the stock indices. The purpose of this paper is to develop an efficient and accurate forecasting model to predict the next-day closing prices of seven stock indices. Design/methodology/approach A novel strategy called quasi-oppositional symbiotic organisms search-based extreme learning machine (QSOS-ELM) is proposed to forecast the next-day closing prices effectively. Accuracy in the prediction of closing price depends on output weights which are dependent on input weights and biases. This paper mainly deals with the optimal design of input weights and biases of the ELM prediction model using QSOS and SOS optimization algorithms. Findings Simulation is carried out on seven stock indices, and performance analysis of QSOS-ELM and SOS-ELM prediction models is done by taking various statistical measures such as mean square error, mean absolute percentage error, accuracy and paired sample t-test. Comparative performance analysis reveals that the QSOS-ELM model outperforms the SOS-ELM model in predicting the next-day closing prices more accurately for all the seven stock indices under study. Originality/value The QSOS-ELM prediction model and SOS-ELM are developed for the first time to predict the next-day closing prices of various stock indices. The paired t-test is also carried out for the first time in literature to hypothetically prove that there is a zero mean difference between the predicted and actual closing prices.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-05-15T10:14:51Z
      DOI: 10.1108/IJICC-10-2018-0145
       
  • Universal usability evaluation by using an integrated fuzzy multi criteria
           decision making approach
    • Pages: 194 - 223
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 12, Issue 2, Page 194-223, June 2019.
      Purpose The purpose of this paper is to propose an integrated fuzzy approach to determine important universal usability problems (UUPs) by providing experts who behave like real users and to establish a work plan to correct the most important ones. Design/methodology/approach In this study, a fuzzy multi-criteria decision-making approach with three stages is proposed for the evaluation of universal usability. At the first stage, UUPs are identified by performing modified heuristic evaluation, and severity rating of each problem is determined by experts. At the second stage, critical problems are specified by applying the fuzzy Delphi considering these severity ratings. At the third stage, Fuzzy Decision Making Trial and Evaluation Laboratory approach is applied to prioritize critical problems as sub and main criteria. An illustrative example related to emergency service is performed to apply the proposed approach. Findings Results showed that the elevator button design, the elevator emergency button design and the position of the floor signboard are the first three problems that should be primarily improved as sub-criteria. In terms of main criteria, equitable use, simple and intuitive use, and perceptible information are the first three main criteria that should be improve in emergency service. Originality/value This study is original in terms of methodology and providing a new perspective for building design evaluation. The results can help the designers to see the UUPs in buildings, to focus the most important UUPs and to establish improvement ranking. These advantages provide time and cost-effective design improvement actions.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-01-22T10:54:59Z
      DOI: 10.1108/IJICC-05-2018-0060
       
  • On the development of cat swarm metaheuristic using distributed learning
           strategies and the applications
    • Pages: 224 - 244
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 12, Issue 2, Page 224-244, June 2019.
      Purpose The purpose of this paper is to propose distributed learning-based three different metaheuristic algorithms for the identification of nonlinear systems. The proposed algorithms are experimented in this study to address problems for which input data are available at different geographic locations. In addition, the models are tested for nonlinear systems with different noise conditions. In a nutshell, the suggested model aims to handle voluminous data with low communication overhead compared to traditional centralized processing methodologies. Design/methodology/approach Population-based evolutionary algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) and cat swarm optimization (CSO) are implemented in a distributed form to address the system identification problem having distributed input data. Out of different distributed approaches mentioned in the literature, the study has considered incremental and diffusion strategies. Findings Performances of the proposed distributed learning-based algorithms are compared for different noise conditions. The experimental results indicate that CSO performs better compared to GA and PSO at all noise strengths with respect to accuracy and error convergence rate, but incremental CSO is slightly superior to diffusion CSO. Originality/value This paper employs evolutionary algorithms using distributed learning strategies and applies these algorithms for the identification of unknown systems. Very few existing studies have been reported in which these distributed learning strategies are experimented for the parameter estimation task.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-05-15T10:14:49Z
      DOI: 10.1108/IJICC-10-2018-0146
       
  • Trajectory tracking control of robotic transcranial magnetic stimulation
    • Pages: 245 - 259
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 12, Issue 2, Page 245-259, June 2019.
      Purpose Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique. Based on the unique functions of TMS, it has been widely used in clinical, scientific research and other fields. Nowadays, the robot-assisted automatic TMS has become the trend. In order to simplify the operation procedures of robotic TMS and reduce the costs, the purpose of this paper is to apply the marker-based augmented-reality technology to robotic TMS system. Design/methodology/approach By using the marker of ARToolKitPlus library and monocular camera, the patient’s head is positioned in real time. Furthermore, the force control is applied to keep contact between the coil and subject’s head. Findings The authors fuse with visual positioning which is based on augmented-reality and force-control technologies to track the movements of the patient’s head, bring the coil closer to the stimulation site and increase treatment effects. Experimental results indicate that the trajectory tracking control of robotic TMS system designed in this paper is practical and flexible. Originality/value This paper provides a trajectory tracking control method for the robotic TMS. The marker-based augmented-reality technology is implemented which simplifies the operation procedures of robotic TMS as well as reduce the costs. During the treatment process, the patients would wear an AR glasses, which can help patients relax through virtual scenes and reduce the uncomfortableness produce by treatment.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-02-08T03:50:57Z
      DOI: 10.1108/IJICC-06-2018-0077
       
  • Influence of time delay on weighted pseudo-almost periodic dynamics in
           SICNNs
    • Pages: 260 - 273
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 12, Issue 2, Page 260-273, June 2019.
      Purpose The purpose of this paper is to investigate the weighted pseudo-almost periodic solutions of shunting inhibitory cellular neural networks (SICNNs) with time-varying delays and distributed delays. Design/methodology/approach The principle of weighted pseudo-almost periodic functions and some new mathematical analysis skills are applied. Findings A set of sufficient criteria which guarantee the existence and exponential stability of the weighted pseudo-almost periodic solutions of the considered SICNNs are established. Originality/value The derived results of this paper are new and complement some earlier works. The innovation of this paper concludes two points: a new sufficient criteria guaranteeing the existence and exponential stability of the weighted pseudo-almost periodic solutions of SICNNs are established; and the ideas of this paper can be applied to investigate some other similar neural networks.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-05-15T10:14:46Z
      DOI: 10.1108/IJICC-04-2018-0054
       
  • LSTM based prediction algorithm and abnormal change detection for
           temperature in aerospace gyroscope shell
    • Pages: 274 - 291
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 12, Issue 2, Page 274-291, June 2019.
      Purpose Abnormal changes in temperature directly affect the stability and reliability of a gyroscope. Predicting the temperature and detecting the abnormal change is great value for timely understanding of the working state of the gyroscope. Considering that the actual collected gyroscope shell temperature data have strong non-linearity and are accompanied by random noise pollution, the prediction accuracy and convergence speed of the traditional method need to be improved. The purpose of this paper is to use a predictive model with strong nonlinear mapping ability to predict the temperature of the gyroscope to improve the prediction accuracy and detect the abnormal change. Design/methodology/approach In this paper, an double hidden layer long-short term memory (LSTM) is presented to predict temperature data for the gyroscope (including single point and period prediction), and the evaluation index of the prediction effect is also proposed, and the prediction effects of shell temperature data are compared by BP network, support vector machine (SVM) and LSTM network. Using the estimated value detects the abnormal change of the gyroscope. Findings By combined simulation calculation with the gyroscope measured data, the effect of different network hyperparameters on shell temperature prediction of the gyroscope is analyzed, and the LSTM network can be used to predict the temperature (time series data). By comparing the performance indicators of different prediction methods, the accuracy of the shell temperature estimation by LSTM is better, which can meet the requirements of abnormal change detection. Quick and accurate diagnosis of different types of gyroscope faults (steps and drifts) can be achieved by setting reasonable data window lengths and thresholds. Practical implications The LSTM model is a deep neural network model with multiple non-linear mapping levels, and can abstract the input signal layer by layer and extract features to discover deeper underlying laws. The improved method has been used to solve the problem of strong non-linearity and random noise pollution in time series, and the estimated value can detect the abnormal change of the gyroscope. Originality/value In this paper, based on the LSTM network, an double hidden layer LSTM is presented to predict temperature data for the gyroscope (including single point and period prediction), and validate the effectiveness and feasibility of the algorithm by using shell temperature measurement data. The prediction effects of shell temperature data are compared by BP network, SVM and LSTM network. The LSTM network has the best prediction effect, and is used to predict the temperature of the gyroscope to improve the prediction accuracy and detect the abnormal change.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-05-15T10:14:48Z
      DOI: 10.1108/IJICC-11-2018-0152
       
  • Clustering in the presence of side information: a non-linear approach
    • Pages: 292 - 314
      Abstract: International Journal of Intelligent Computing and Cybernetics, Volume 12, Issue 2, Page 292-314, June 2019.
      Purpose Constrained clustering is an important recent development in clustering literature. The goal of an algorithm in constrained clustering research is to improve the quality of clustering by making use of background knowledge. The purpose of this paper is to suggest a new perspective for constrained clustering, by finding an effective transformation of data into target space on the reference of background knowledge given in the form of pairwise must- and cannot-link constraints. Design/methodology/approach Most of existing methods in constrained clustering are limited to learn a distance metric or kernel matrix from the background knowledge while looking for transformation of data in target space. Unlike previous efforts, the author presents a non-linear method for constraint clustering, whose basic idea is to use different non-linear functions for each dimension in target space. Findings The outcome of the paper is a novel non-linear method for constrained clustering which uses different non-linear functions for each dimension in target space. The proposed method for a particular case is formulated and explained for quadratic functions. To reduce the number of optimization parameters, the proposed method is modified to relax the quadratic function and approximate it by a factorized version that is easier to solve. Experimental results on synthetic and real-world data demonstrate the efficacy of the proposed method. Originality/value This study proposes a new direction to the problem of constrained clustering by learning a non-linear transformation of data into target space without using kernel functions. This work will assist researchers to start development of new methods based on the proposed framework which will potentially provide them with new research topics.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-05-15T10:14:54Z
      DOI: 10.1108/IJICC-04-2018-0046
       
  • Analyzing China’s OFDI using a novel multivariate grey prediction
           model with Fourier series
    • Abstract: International Journal of Intelligent Computing and Cybernetics, Ahead of Print.
      Purpose With the development of economy, China’s OFDI constantly increase in recent year. Meanwhile, OFDI has spillover effect on economic development and technological development of home country. Thus, accurate OFDI prediction is a prerequisite for the effective development of international investment strategies. The purpose of this paper is to predict China’s OFDI accurately using a novel multivariable grey prediction model with Fourier series. Design/methodology/approach This paper applied a multivariable grey prediction model, GM(1,N), to forecast China’s OFDI. In order to improve the prediction accuracy and without changing local characteristics of grey model prediction, this paper proposed a novel grey prediction model to improve the performance of the traditional GM(1,N) model by combining with residual modification model using GM(1,1) model and Fourier series. Findings The coefficients indicate that the export and GDP have positive influence on China’s OFDI, and, according to the prediction result, China’s OFDI shows a growing trend in next five years. Originality/value This paper proposed an effective multivariable grey prediction model that combined the traditional GM(1,N) model with a residual modification model in order to predict China’s OFDI. Accurate forecasting of OFDI provides reference for the Chinese Government to implement international investment strategies.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-06-21T11:03:27Z
      DOI: 10.1108/IJICC-07-2018-0095
       
  • Self-adaptive scale pedestrian detection algorithm based on deep residual
           network
    • Abstract: International Journal of Intelligent Computing and Cybernetics, Ahead of Print.
      Purpose The conventional pedestrian detection algorithms lack in scale sensitivity. The purpose of this paper is to propose a novel algorithm of self-adaptive scale pedestrian detection, based on deep residual network (DRN), to address such lacks. Design/methodology/approach First, the “Edge boxes” algorithm is introduced to extract region of interests from pedestrian images. Then, the extracted bounding boxes are incorporated to different DRNs, one is a large-scale DRN and the other one is the small-scale DRN. The height of the bounding boxes is used to classify the results of pedestrians and to regress the bounding boxes to the entity of the pedestrian. At last, a weighted self-adaptive scale function, which combines the large-scale results and small-scale results, is designed for the final pedestrian detection. Findings To validate the effectiveness and feasibility of the proposed algorithm, some comparison experiments have been done on the common pedestrian detection data sets: Caltech, INRIA, ETH and KITTI. Experimental results show that the proposed algorithm is adapted for the various scales of the pedestrians. For the hard detected small-scale pedestrians, the proposed algorithm has improved the accuracy and robustness of detections. Originality/value By applying different models to deal with different scales of pedestrians, the proposed algorithm with the weighted calculation function has improved the accuracy and robustness for different scales of pedestrians.
      Citation: International Journal of Intelligent Computing and Cybernetics
      PubDate: 2019-06-06T12:37:41Z
      DOI: 10.1108/IJICC-12-2018-0167
       
 
 
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