Subjects -> MATHEMATICS (Total: 1118 journals)
    - APPLIED MATHEMATICS (92 journals)
    - GEOMETRY AND TOPOLOGY (23 journals)
    - MATHEMATICS (819 journals)
    - MATHEMATICS (GENERAL) (45 journals)
    - NUMERICAL ANALYSIS (26 journals)
    - PROBABILITIES AND MATH STATISTICS (113 journals)

MATHEMATICS (819 journals)                  1 2 3 4 5 | Last

Showing 1 - 200 of 538 Journals sorted alphabetically
Abakós     Open Access   (Followers: 5)
Abhandlungen aus dem Mathematischen Seminar der Universitat Hamburg     Hybrid Journal   (Followers: 3)
Accounting Perspectives     Full-text available via subscription   (Followers: 9)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 17)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 5)
ACM Transactions on Mathematical Software (TOMS)     Hybrid Journal   (Followers: 9)
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 44)
Acta Applicandae Mathematicae     Hybrid Journal   (Followers: 2)
Acta Mathematica     Hybrid Journal   (Followers: 11)
Acta Mathematica Hungarica     Hybrid Journal   (Followers: 2)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5)
Acta Mathematica Sinica, English Series     Hybrid Journal   (Followers: 6)
Acta Mathematica Vietnamica     Hybrid Journal  
Acta Mathematicae Applicatae Sinica, English Series     Hybrid Journal  
Advanced Science Letters     Full-text available via subscription   (Followers: 13)
Advances in Applied Clifford Algebras     Hybrid Journal   (Followers: 6)
Advances in Catalysis     Full-text available via subscription   (Followers: 8)
Advances in Complex Systems     Hybrid Journal   (Followers: 12)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 23)
Advances in Decision Sciences     Open Access   (Followers: 4)
Advances in Difference Equations     Open Access   (Followers: 5)
Advances in Fixed Point Theory     Open Access   (Followers: 9)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 22)
Advances in Linear Algebra & Matrix Theory     Open Access   (Followers: 10)
Advances in Materials Science     Open Access   (Followers: 22)
Advances in Mathematical Physics     Open Access   (Followers: 10)
Advances in Mathematics     Full-text available via subscription   (Followers: 22)
Advances in Numerical Analysis     Open Access   (Followers: 8)
Advances in Operations Research     Open Access   (Followers: 14)
Advances in Operator Theory     Hybrid Journal   (Followers: 4)
Advances in Porous Media     Full-text available via subscription   (Followers: 6)
Advances in Pure Mathematics     Open Access   (Followers: 11)
Advances in Science and Research (ASR)     Open Access   (Followers: 8)
Aequationes Mathematicae     Hybrid Journal   (Followers: 2)
African Journal of Educational Studies in Mathematics and Sciences     Full-text available via subscription   (Followers: 12)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 7)
Afrika Matematika     Hybrid Journal   (Followers: 3)
Air, Soil & Water Research     Open Access   (Followers: 13)
AKSIOMA Journal of Mathematics Education     Open Access   (Followers: 4)
AKSIOMATIK : Jurnal Penelitian Pendidikan dan Pembelajaran Matematika     Open Access   (Followers: 1)
Al-Jabar : Jurnal Pendidikan Matematika     Open Access   (Followers: 1)
Al-Qadisiyah Journal for Computer Science and Mathematics     Open Access   (Followers: 1)
AL-Rafidain Journal of Computer Sciences and Mathematics     Open Access   (Followers: 6)
Algebra and Logic     Hybrid Journal   (Followers: 8)
Algebra Colloquium     Hybrid Journal   (Followers: 4)
Algebra Universalis     Hybrid Journal   (Followers: 2)
Algorithmic Operations Research     Open Access   (Followers: 5)
Algorithms     Open Access   (Followers: 14)
Algorithms Research     Open Access   (Followers: 2)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 10)
American Journal of Mathematical Analysis     Open Access   (Followers: 2)
American Journal of Mathematical and Management Sciences     Hybrid Journal   (Followers: 1)
American Journal of Mathematics     Full-text available via subscription   (Followers: 9)
American Journal of Operations Research     Open Access   (Followers: 8)
American Mathematical Monthly     Full-text available via subscription   (Followers: 7)
An International Journal of Optimization and Control: Theories & Applications     Open Access   (Followers: 13)
Analele Universitatii Ovidius Constanta - Seria Matematica     Open Access  
Analysis and Applications     Hybrid Journal   (Followers: 2)
Analysis and Mathematical Physics     Hybrid Journal   (Followers: 10)
Analysis Mathematica     Full-text available via subscription  
Anargya : Jurnal Ilmiah Pendidikan Matematika     Open Access   (Followers: 8)
Annales Mathematicae Silesianae     Open Access   (Followers: 2)
Annales mathématiques du Québec     Hybrid Journal   (Followers: 4)
Annales Universitatis Mariae Curie-Sklodowska, sectio A – Mathematica     Open Access   (Followers: 1)
Annales Universitatis Paedagogicae Cracoviensis. Studia Mathematica     Open Access  
Annali di Matematica Pura ed Applicata     Hybrid Journal   (Followers: 1)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 17)
Annals of Discrete Mathematics     Full-text available via subscription   (Followers: 8)
Annals of Functional Analysis     Hybrid Journal   (Followers: 4)
Annals of Mathematics     Full-text available via subscription   (Followers: 4)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 16)
Annals of PDE     Hybrid Journal  
Annals of Pure and Applied Logic     Open Access   (Followers: 6)
Annals of the Alexandru Ioan Cuza University - Mathematics     Open Access  
Annals of the Institute of Statistical Mathematics     Hybrid Journal   (Followers: 1)
Annals of West University of Timisoara - Mathematics     Open Access   (Followers: 1)
Annals of West University of Timisoara - Mathematics and Computer Science     Open Access   (Followers: 2)
Annuaire du Collège de France     Open Access   (Followers: 6)
ANZIAM Journal     Open Access   (Followers: 2)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 3)
Applications of Mathematics     Hybrid Journal   (Followers: 3)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 16)
Applied Mathematics     Open Access   (Followers: 10)
Applied Mathematics     Open Access   (Followers: 6)
Applied Mathematics & Optimization     Hybrid Journal   (Followers: 13)
Applied Mathematics - A Journal of Chinese Universities     Hybrid Journal   (Followers: 2)
Applied Mathematics and Nonlinear Sciences     Open Access   (Followers: 1)
Applied Mathematics Letters     Full-text available via subscription   (Followers: 3)
Applied Mathematics Research eXpress     Hybrid Journal   (Followers: 2)
Applied Network Science     Open Access   (Followers: 3)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 6)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 6)
Arab Journal of Mathematical Sciences     Open Access   (Followers: 4)
Arabian Journal of Mathematics     Open Access   (Followers: 2)
Archive for Mathematical Logic     Hybrid Journal   (Followers: 4)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 6)
Archive of Numerical Software     Open Access  
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 6)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
Armenian Journal of Mathematics     Open Access   (Followers: 1)
Arnold Mathematical Journal     Hybrid Journal   (Followers: 1)
Artificial Satellites     Open Access   (Followers: 24)
Asia-Pacific Journal of Operational Research     Hybrid Journal   (Followers: 3)
Asian Journal of Algebra     Open Access   (Followers: 1)
Asian Research Journal of Mathematics     Open Access  
Asian-European Journal of Mathematics     Hybrid Journal   (Followers: 4)
Australian Mathematics Teacher, The     Full-text available via subscription   (Followers: 7)
Australian Primary Mathematics Classroom     Full-text available via subscription   (Followers: 7)
Australian Senior Mathematics Journal     Full-text available via subscription   (Followers: 2)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Axioms     Open Access   (Followers: 1)
Baltic International Yearbook of Cognition, Logic and Communication     Open Access   (Followers: 2)
Banach Journal of Mathematical Analysis     Hybrid Journal   (Followers: 1)
Basin Research     Hybrid Journal   (Followers: 6)
BIBECHANA     Open Access   (Followers: 2)
Biomath     Open Access  
BIT Numerical Mathematics     Hybrid Journal   (Followers: 1)
Boletim Cearense de Educação e História da Matemática     Open Access  
Boletim de Educação Matemática     Open Access  
Boletín de la Sociedad Matemática Mexicana     Hybrid Journal  
Bollettino dell'Unione Matematica Italiana     Full-text available via subscription   (Followers: 3)
British Journal for the History of Mathematics     Hybrid Journal  
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 20)
Bruno Pini Mathematical Analysis Seminar     Open Access  
Buletinul Academiei de Stiinte a Republicii Moldova. Matematica     Open Access   (Followers: 14)
Bulletin des Sciences Mathamatiques     Full-text available via subscription   (Followers: 4)
Bulletin of Dnipropetrovsk University. Series : Communications in Mathematical Modeling and Differential Equations Theory     Open Access   (Followers: 3)
Bulletin of Mathematical Sciences     Open Access   (Followers: 1)
Bulletin of Symbolic Logic     Full-text available via subscription   (Followers: 3)
Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics     Open Access  
Bulletin of the Australian Mathematical Society     Full-text available via subscription   (Followers: 2)
Bulletin of the Brazilian Mathematical Society, New Series     Hybrid Journal  
Bulletin of the Iranian Mathematical Society     Hybrid Journal  
Bulletin of the London Mathematical Society     Hybrid Journal   (Followers: 3)
Bulletin of the Malaysian Mathematical Sciences Society     Hybrid Journal  
Cadernos do IME : Série Matemática     Open Access   (Followers: 2)
Calculus of Variations and Partial Differential Equations     Hybrid Journal  
Canadian Journal of Mathematics / Journal canadien de mathématiques     Hybrid Journal  
Canadian Journal of Science, Mathematics and Technology Education     Hybrid Journal   (Followers: 23)
Canadian Mathematical Bulletin     Hybrid Journal  
Carpathian Mathematical Publications     Open Access   (Followers: 1)
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 6)
CHANCE     Hybrid Journal   (Followers: 5)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals : X     Open Access   (Followers: 1)
ChemSusChem     Hybrid Journal   (Followers: 8)
Chinese Annals of Mathematics, Series B     Hybrid Journal  
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 3)
Chinese Journal of Mathematics     Open Access  
Ciencia     Open Access   (Followers: 1)
CODEE Journal     Open Access   (Followers: 2)
Cogent Mathematics     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 3)
Collectanea Mathematica     Hybrid Journal  
College Mathematics Journal     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 17)
Commentarii Mathematici Helvetici     Hybrid Journal  
Communications in Advanced Mathematical Sciences     Open Access  
Communications in Combinatorics and Optimization     Open Access  
Communications in Contemporary Mathematics     Hybrid Journal  
Communications in Mathematical Physics     Hybrid Journal   (Followers: 4)
Communications On Pure & Applied Mathematics     Hybrid Journal   (Followers: 5)
Complex Analysis and its Synergies     Open Access   (Followers: 3)
Complex Variables and Elliptic Equations: An International Journal     Hybrid Journal  
Composite Materials Series     Full-text available via subscription   (Followers: 11)
Compositio Mathematica     Full-text available via subscription  
Comptes Rendus : Mathematique     Open Access  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 4)
Computational and Mathematical Methods     Hybrid Journal  
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 3)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 1)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 9)
Computational Mechanics     Hybrid Journal   (Followers: 10)
Computational Methods and Function Theory     Hybrid Journal  
Computational Optimization and Applications     Hybrid Journal   (Followers: 11)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 11)
Confluentes Mathematici     Hybrid Journal  
Constructive Mathematical Analysis     Open Access   (Followers: 1)
Contributions to Discrete Mathematics     Open Access   (Followers: 1)
Contributions to Game Theory and Management     Open Access  
COSMOS     Hybrid Journal   (Followers: 1)
Cryptography and Communications     Hybrid Journal   (Followers: 14)
Cuadernos de Investigación y Formación en Educación Matemática     Open Access  
Cubo. A Mathematical Journal     Open Access  
Current Research in Biostatistics     Open Access   (Followers: 8)
Czechoslovak Mathematical Journal     Hybrid Journal   (Followers: 1)
Daya Matematis : Jurnal Inovasi Pendidikan Matematika     Open Access   (Followers: 1)
Demographic Research     Open Access   (Followers: 16)
Design Journal : An International Journal for All Aspects of Design     Hybrid Journal   (Followers: 35)
Desimal : Jurnal Matematika     Open Access   (Followers: 3)
Developments in Clay Science     Full-text available via subscription   (Followers: 1)
Developments in Mineral Processing     Full-text available via subscription   (Followers: 3)
Dhaka University Journal of Science     Open Access  
Differential Equations and Dynamical Systems     Hybrid Journal   (Followers: 4)

        1 2 3 4 5 | Last

Similar Journals
Journal Cover
Annals of Data Science
Number of Followers: 17  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2198-5804 - ISSN (Online) 2198-5812
Published by Springer-Verlag Homepage  [2658 journals]
  • On a Class of Elliptic (p, q)-Kirchhoff Type Systems with Multiple
           Parameters

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      Abstract: This article concerns the existence of positive solutions for elliptic (p, q)-Kirchhoff type systems with multiple parameters. Our approach is based on the method of sub and super-solutions. The concepts of sub- and super-solution were introduced by Nagumo (Proc Phys-Math Soc Jpn19:861–866, 1937) in 1937 who proved, using also the shooting method, the existence of at least one solution for a class of nonlinear Sturm-Liouville problems. In fact, the premises of the sub- and super-solution method can be traced back to Picard. He applied, in the early 1880s, the method of successive approximations to argue the existence of solutions for nonlinear elliptic equations that are suitable perturbations of uniquely solvable linear problems. This is the starting point of the use of sub- and super-solutions in connection with monotone methods. Picard’s techniques were applied later by Poincaré (J Math Pures Appl 4:137–230, 1898) in connection with problems arising in astrophysics. We refer to Rădulescu (Qualitative analysis ofnonlinear elliptic partial differential equations: monotonicity, analytic, and variational methods, contemporary mathematics and its applications, Hindawi Publishing Corporation, New York, 2008).
      PubDate: 2021-12-01
       
  • Spectral Algorithms for Streaming Graph Analysis: A Survey

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      Abstract: Streaming data models refer to some constrained settings through which continuous flow of information regarding updates on the data becomes available. Graphs can also be represented in a streaming setting where interaction information turns out to be accessible as a stream of inclusion or exclusion of interactions. Analysis of streaming graphs helps to understand extreme-scale and dynamic real-life interactions in different forms. The growth of world wide web has drastically changed the way we look at various real-life evolving gigantic networks. This has motivated the development of streaming algorithms to be applied on graphs at scale. To achieve this scalability, sketching and sampling strategies are generally adopted to realize the different attributes of graphs. Spectrum of a graph, being one of the most appreciated characteristics, has lead to the evolution of an entire class of spectral algorithms. In this paper, we touch upon the state-of-the-art progress in streaming graph analysis with spectral algorithms. We mainly cover the latest developments in the areas like sampling, sparsification, singular value decomposition, counting problems related to local structures, analysis of global structures, partitioning, labeling, mesh processing, discovery of patterns, anomalous hotspot discovery, detection of communities, etc. on the subject of streaming graphs.
      PubDate: 2021-12-01
       
  • Marshall–Olkin Extended Inverse Weibull Distribution: Different
           Methods of Estimations

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      Abstract: The inverse Weibull distribution is successfully applied in many different disciplines e.g., reliability engineering, bioengineering and modeling of survival data. There are lots of statistical and computer science techniques e.g., particle swarm optimization, employed to estimate the parameters of this distribution and its generalization. The suitable methods for estimating the parameters of Marshall–Olkin extended inverse Weibull distribution are specified in this paper. So, the performance of different estimation methods called maximum likelihood, Percentiles, Least squares, Weighted least squares, Cramér–van Mises and Anderson–Darling methods, is compared in terms of the bias and mean squared error through extensive numerical simulations. Also, empirical illustration on real life dataset supported the obtained conclusion.
      PubDate: 2021-12-01
       
  • Patient Discharge Classification Using Machine Learning Techniques

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      Abstract: Patient discharge is one of the critical processes for medical providers from any health facility to transfer the care of the patient to another care provider after hospitalisation. The discharge plan, final clinical and physical checks, patient education, patient readiness, and general practitioner appointments play an important role in the success of this procedure. However, it has loopholes that need to be addressed to lessen the complexity of managing this critical process. When this is left unchecked, serious consequences and challenges may occur such as re-hospitalisation and financial pressure. This research investigates machine learning technology on the problem of patient discharge by using a real dataset. In particular, the applicability of techniques including Decision Trees, Bayes Net, and Random Forest have been investigated in order to predict the discharge outcome of a patient after surgery. The results of the analysis show that Bayes Net performed better than Decision Tree, and Random Forest in predicting the response variable (class) using tenfold cross validation with respect to classification accuracy. The target audiences of this research are the staff working in a healthcare facility such as clinicians, chief medical officer, and physicians among others.
      PubDate: 2021-12-01
       
  • An Assessment of Football Through the Lens of Data Science

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      Abstract: The rise of Data Science and related fields of Big Data, Machine Learning, and Deep Learning has transformed the industrial landscape. The areas of sports and sports analytics are no exception. While to the layman, its influence may not be evident, but they have changed the way various sports are played up to different degrees. Hence, in recent times, sports institutions and clubs have given increased importance to such research that will ultimately help them have a competitive edge over rivals. The effects of these institutions incorporating these researches into their ways of competing have had impacts on and off the playing field. These effects aren’t only in terms of physiological enhancements of the athletes, but also socio-political and economic impacts as well. Out of the various sports implementing these techniques, we will focus on the effects mentioned above of Data Science on Football (“Soccer” in the USA). The following is a detailed review of the concepts as mentioned earlier.
      PubDate: 2021-12-01
       
  • Zero-Inflated Models for Count Data: An Application to Number of Antenatal
           Care Service Visits

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      Abstract: The risk of maternal death in developing countries is projected to be one in 61, while for developed countries it is estimated to be one in 2800. Antenatal care is a protective obstetric health care system aimed at improving the outcome of the pregnant fetus by routine pregnancy monitoring. One of the most important functions of antenatal care is to offer health information and services that can significantly improve the health of women and their infants. 6450 pregnant women from Ethiopian Demographic and Health Survey of 2016 were used to analyze the determinants of the barriers in number of antenatal care service visits among pregnant women in Ethiopia. The data were found to have excess zeros (35%); thus several count data models such as Poisson, Negative Binomial, Zero Inflated Poisson, Zero Inflated Negative Binomial and Hurdle regression models were modeled and fitted. From the exploratory analysis the results showed that among those eligible pregnant women, it was seen that 2240 (34.7%) of them did not visit antenatal care service during their periods of pregnancy months. The visualization of data using scatter plot depicts that all of the variables selected for modeling have an influence on the event of not visiting antenatal care cervices while each of these variables had opposite slope in non-zero number of such events in their respective categories. To select the model which best fits the data, models were compared based on their Akaike information criterion value by using the simulation study. The simulation experiment revealed that models for zero-inflated data such as; Zero Inflated Poisson, Zero Inflated Negative Binomial and Hurdle were models that fitted the data better than the classical models Poisson and Negative Binomial. Each of these zero-inflated models was compared using Voung test and Hurdle model was better fitted the data which was characterized by excess zeros and high variability in the non-zero outcome than any other zero-inflated models. In this study, maternal education, partner education level, age of mothers, religion of mothers and wealth index are major predictors of antenatal care service utilization. Through simulation experiment, it was found that Zero Inflated Poisson, Zero Inflated Negative Binomial and Hurdle models were better fitted zero-inflated data than Poisson and Negative Binomial. Voung test suggests that Hurdle model was better fitted zero-inflated (ZI) data than any other zero inflated models and therefore, it was selected as the best parsimonious model.
      PubDate: 2021-12-01
       
  • Parameter Estimation for the Exponentiated Kumaraswamy-Power Function
           Distribution Based on Order Statistics with Application

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      Abstract: Exponentiated Kumaraswamy-power function (EKPF) distribution has been proposed recently by Bursa and Ozel (Hacet J Math Stat 46:277–292, 2017) as a quite flexible in terms of probability density and hazard rate functions than power function distribution. In this paper, we obtain the explicit expressions for the single, double (product), triple and quadruple moments and moment generating function for single, double, triple and quadruple of order statistics of the EKPF distribution. By using these relations, we have tabulated the means and variances of order statistics from samples of sizes up to 10 for various values of the parameters. We use five frequentist estimation methods to estimate the unknown parameters and a simulation study is used to compare the performance of the different estimators. Finally, we analyse a real data set for illustrative purpose.
      PubDate: 2021-12-01
       
  • Asymmetric Effect and Dynamic Relationships Between Stock Prices and
           Exchange Rates Volatility

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      Abstract: The analysis of time-varying correlation between stock prices and exchange rates in the context of international investments has been well researched in the literature in last few years. In this paper, we study the interdependence of exchange rates and stock prices for seven countries (Canada, Japan, Denmark, Hong Kong, Singapore, Mexico and Brazil). To do so, we both use the DCC-FIEGARCH and FIAPARCH-DCC models during the period spanning from January 1, 2000 until January 1, 2016. The empirical results suggest asymmetric responses in stock prices-exchange rates linkages, a high persistence of the conditional correlation. They also show bidirectional spillovers effects between different series. Moreover, the results indicate different behavior of exchange rates-stock prices nexus during the crisis periods, suggesting the need for specific policy measures. Finally, our findings offer investors, portfolios managers and policymakers insights on international portfolios and monetary.
      PubDate: 2021-12-01
       
  • Weighted Tchebycheff Optimization Technique Under Uncertainty

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      Abstract: In a multi-objective optimization problem there is more than one objective function and there is no single optimal solution which simultaneously optimizes all of the given objective functions. For these unsuitable conditions the decision makers always search for the most ‘‘preferred’’ solution, in contrast to the optimal solution. A number of mathematical programming methods, namely Weighted-sum method, Goal programming, Lexicographic method, Weighted min–max method, Exponential weighted criterion, Weighted product method, Bounded objective function method and Weighted Tchebycheff optimization methods have been applied in the recent past to find the optimal solution. In this paper weighted Tchebycheff optimization methods has been applied to find the optimal solution of a multi-objective optimization problem. A solution procedure of weighted Tchebycheff technique has been discussed to find the optimal solution of the multi-objective optimization problems. For the most part, the parameters of a multi-objective optimization model are thought to be deterministic and settled. Nonetheless, the qualities watched for the parameters in true multi-objective optimization problems are frequently loose and subject to change. In this way, we utilize multi-objective optimization model inside a vulnerability based system and propose a multi-objective optimization model whose coefficients are uncertain in nature. We accept the uncertain variables (UVs) to have linear uncertainty distributions. Finally, a numerical example is solved weighted Tchebycheff technique.
      PubDate: 2021-12-01
       
  • Robust Ratio- and Product-Type Estimators Under Non-normality via Linear
           Transformation Using Certain Known Population Parameters

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      Abstract: In the literature, a linear transformation on an auxiliary variable has been widely used to increase the efficiencies of ratio- and product-type estimators. However, additional information of unknown population parameters is required to utilize such estimators. In this paper, we propose two novel ratio-type and two novel product-type estimators under non-normality using the minimum and maximum values of the auxiliary variable. The expressions for mean square errors and biases for the proposed estimators are derived. We also calculate confidence intervals of the estimators. Theoretical results are supported using simulation studies. We also illustrate our results using a real life application of a body fat data set. We study robustness properties of the proposed estimators. We show that the proposed ratio-type estimators which utilize certain known auxiliary information can improve some other existing estimators which do not utilize such auxiliary information.
      PubDate: 2021-12-01
       
  • Using Social Media to Predict the Stock Market Crash and Rebound amid the
           Pandemic: The Digital ‘Haves’ and ‘Have-mores’

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      Abstract: Since the 2019 novel Coronavirus disease (COVID-19) spread across the globe, risks brought by the pandemic set in and stock markets tumbled worldwide. Amidst the bleak economic outlook, investors’ concerns over the pandemic spread rapidly through social media but wore out shortly. Similarly, the crash only caused a relatively short-lived bear market, which bottomed out and recovered quickly. Meanwhile, technology stocks have grabbed the spotlight as the digitally advanced sectors seemed to show resilience in this Coronavirus-plagued market. This paper aims to examine market sentiments using social media to predict the stock market performance before, during and after the March 2020 stock market crash. In addition, using the Organisation for Economic Co-operation and Development Taxonomy of Sectoral Digital-intensity Framework, we identified market sectors that have outperformed others as the market sentiment was impacted by the unfolding of the pandemic. The daily stock performance of a usable sample of 1619 firms from 34 sectors was first examined via a combination of hierarchical clustering and shape-based distance measure. This was then tested against a time series of daily price changes through augmented vector auto-regression. Results show that market sentiments towards the pandemic have significantly impacted the price differences. More interestingly, the stock performance across sectors is characterized by the level of digital intensity, with the most digitally advanced sectors demonstrating resilience against negative market sentiments on the pandemic. This research is among the first to demonstrate how digital intensity mitigates the negative effect of a crisis on stock market performance.
      PubDate: 2021-09-15
       
  • Estimation of the Daily Recovery Cases in Egypt for COVID-19 Using Power
           Odd Generalized Exponential Lomax Distribution

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      Abstract: Covid-19 has become an important topic this days, because of its bad effect in many fields such as Economics, industrial and commerce. In this paper, Covid-19 will be studied statistically point of view depending on the recovery cases in the Arab Republic of Egypt in the interval of (20 March to 20 August 2020). A power odd generalized exponential Lomax distribution has been considered. Some mathematical properties of the distribution are studied. The method of maximum likelihood and maximum product of spacings are used for estimating the model parameters. Also 95% asymptotic confidence intervals for the estimates of the parameters are derived. A simulation study was conducted to evaluate the numerical behavior of the estimates. The proposed methods are utilized to find estimates of the parameters of power odd generalized exponential Lomax distribution for the recovery cases of corona virus in Egypt.
      PubDate: 2021-09-06
      DOI: 10.1007/s40745-021-00336-x
       
  • Predicting Indian Stock Market Using the Psycho-Linguistic Features of
           Financial News

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      Abstract: Financial forecasting using news articles is an emerging field. In this paper, we proposed hybrid intelligent models for stock market prediction using the psycholinguistic variables (LIWC and TAALES) extracted from news articles as predictor variables. For prediction purpose, we employed various intelligent techniques such as Multilayer Perceptron, Group Method of Data Handling (GMDH), General Regression Neural Network (GRNN), Random Forest, Quantile Regression Random Forest, Classification and regression tree and Support Vector Regression. We experimented on the data of 12 companies’ stocks, which are listed in Bombay Stock Exchange. We employed Chi squared and maximum relevance and minimum redundancy feature selection techniques on the psycho-linguistic features obtained from the news articles etc. After extensive experimentation, using Diebold-Mariano test, we conclude that GMDH and GRNN are statistically the best techniques in that order with respect to the MAPE and NRMSE values.
      PubDate: 2021-09-01
      DOI: 10.1007/s40745-020-00272-2
       
  • A Generalization of the Quantile-Based Flattened Logistic Distribution

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      Abstract: In this paper, we propose a generalization of the quantile-based flattened logistic distribution Sharma and Chakrabarty (Commun Stat Theory Methods 48(14):3643–3662, 2019. https://doi.org/10.1080/03610926.2018.1481966). Having described the need for such a generalization from the data science perspective, several important properties of the distribution are derived here. We show that the rth order L-moment of the distribution can be written in a closed form expression. The L-skewness ratio and the L-kurtosis ratio of the distribution have been studied in detail. The distribution is shown to posses a skewness-invariant kurtosis measure based on quantiles and L-moments. The method of matching L-moments estimation has been used to estimate the parameters of the proposed model. The model has been applied to two real-life datasets and appropriate goodness-of-fit procedures have been used to test the validity of the model.
      PubDate: 2021-09-01
      DOI: 10.1007/s40745-021-00322-3
       
  • Analytical Split Value Calculation for Numerical Attributes in Hoeffding
           Trees with Misclassification-Based Impurity

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      Abstract: Hoeffding tree is a method to incrementally build decision trees. A common approach to handle numerical attributes in Hoeffding trees is to represent their sufficient statistics as Gaussian distributions. Our contribution in this paper is to prove that by using Gaussian distribution as sufficient statistics and misclassification error as impurity measure, there is an analytical method to exactly calculate the best splitting values. Three different approaches for using this theorem are proposed and all three are tested on both synthetic and real datasets. The experiments suggest that this approach can create smaller trees and learn faster and achieve higher accuracy in most problems.
      PubDate: 2021-09-01
      DOI: 10.1007/s40745-019-00225-4
       
  • A Clustering Algorithm Based on Document Embedding to Identify Clinical
           Note Templates

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      Abstract: This paper proposes a novel unsupervised document embedding based clustering algorithm to generate clinical note templates. We adapted Charikar’s SimHash to embed each clinical document into a vector representation. We modified the traditional K-means algorithm to merge any two clusters with centroids when they are very close. Under the K-means paradigm, our algorithm designates the cluster representative corresponding to the document vector closest to the centroid as the prototype template. On a corpus of clinical notes, we evaluated the feasibility of utilizing our algorithm at the individual author level. The corpus contains 1,063,893 clinical notes corresponding to 19,146 unique providers between January 2011 and July 2016. Our algorithm achieved more than 80% precision and runs in O(n) time complexity. We further validated our algorithm using human annotators who reported it is able to efficiently detect a real clinical document that can represent the other documents in the same cluster at both the department level and the individual clinician level.
      PubDate: 2021-09-01
      DOI: 10.1007/s40745-020-00296-8
       
  • On Step-Stress Accelerated Life Testing for Power Generalized Weibull
           Distribution Under Progressive Type-II Censoring

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      Abstract: In this paper, step-stress accelerated life testing is studied when the lifetime of test units follows power generalized Weibull distribution (PGW). Maximum likelihood estimates (MLEs) and Bayes estimates (BEs) of the model parameters are obtained under type-II progressive censoring. Moreover, the approximate and credible confidence intervals of the parameters are derived. Also, simulation studies are conducted to check the precision of the MLEs and BEs for the parameters of PGW distribution. Finally, some interesting conclusions are obtained.
      PubDate: 2021-09-01
      DOI: 10.1007/s40745-020-00270-4
       
  • A Comprehensive Review on Performance Prediction of Solar Air Heaters
           Using Artificial Neural Network

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      Abstract: Solar air heater (SAH) is a most commonly used solar energy utilization system, which collects solar radiation on absorber plate and transmits absorbed thermal energy to the flowing air. Many techniques were used by various researchers for increasing the performance of SAHs by experimental examination, but analytical and experimental studies takes more time and are very costly. To avoid these types of problems soft computing techniques are used, in which artificial neural network (ANN) technique plays an important role to predict and optimize the performances of SAHs. This technique is very popular due to its fast computing speed and ability to solve complicated problems accurately which is not solved by other conventional approaches. For solving any problem programming code is not required which is the main advantage of this technique. The main purpose of present work is to review the work related to applications of neural model for performance prediction of SAHs and find out the research gap for future investigations. Various research works shown in this paper concluded that ANN is very efficient technique for performance prediction of SAHs.
      PubDate: 2021-09-01
      DOI: 10.1007/s40745-019-00236-1
       
  • A Two-Phase Multi-criteria Fuzzy Group Decision Making Approach for
           Supplier Evaluation and Order Allocation Considering Multi-objective,
           Multi-product and Multi-period

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      Abstract: Due to severe competition among business organizations, the selection of supplier becomes more important for business success. However, supplier selection problems are complex and unstructured since it involves a large number of criteria and some of the criteria cannot be assessed accurately. Also, supplier’s performance fluctuations and unknown information always exist in the real-world decisions. Moreover, the criteria may be qualitative or quantitative in nature as well as supplier evaluation involves a group of experts with diverse opinions. To handle such uncertain and vague information of suppliers, use of fuzzy sets is an appropriate option. Hence, for making a realistic decision, this research proposes a two-phase method to select the suitable suppliers and allocate appropriate orders to them. In first phase of the study, the ranking of supplier is performed by using fuzzy MULTIMOORA method with regard to the important criteria. Then, multi-objective linear programming (MOLP) method in fuzzy environment is proposed to allocate orders to the preferred suppliers in the second phase. The model is developed in multi-product environment by satisfying demand, lead time and capacity constraints. We used expected value method to transform the fuzzy multi objective problem into a crisp single objective problem. Appropriate orders are assigned to the preferred suppliers by considering the closeness coefficient to the fuzzy MOLP model. At last, a case study is performed in an Indian manufacturing organization to illustrate the proposed model.
      PubDate: 2021-09-01
      DOI: 10.1007/s40745-020-00255-3
       
  • On Discrimination Between the Lindley and xgamma Distributions

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      Abstract: For a given data set the problem of selecting either Lindley or xgamma distribution with unknown parameter is investigated in this article. Both these distributions can be used quite effectively for analyzing skewed non-negative data and in modeling time-to-event data sets. We have used the ratio of the maximized likelihoods in choosing between the Lindley and xgamma distributions. Asymptotic distributions of the ratio of the maximized likelihoods are obtained and those are utilized to determine the minimum sample size required to discriminate between these two distributions for user specified probability of correct selection and tolerance limit.
      PubDate: 2021-09-01
      DOI: 10.1007/s40745-020-00243-7
       
 
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