Softcomputing: Theories and Applications

Dear Colleagues,

Softcomputing or Computational Intelligence is a very open scientific area which emerged in the second half of the 20th century, changing dramatically the space of mathematical and computational modelling, especially in the areas of decision making, data analytics, Artificial Intelligence, machine learning, and automated control.

Softcomputing offered a new perspective very much based on intuition, characterized by hybrid solutions and intelligent methods frequently inspired from natural connectionist and evolutive metaphors, but more and more associated to new axiomatic developments which incorporate a mathematical compass to the construction of new useful theoretical spaces with strong impact.

Papers with softcomputing theoretical approaches and diverse applications are brought together in this Special Issue.

Papers gather softcomputing classical approaches like fuzzy logic, neural network probabilistic modelling, support vector machines, and rough sets, new theoretical approaches to them, and applications in the framework of multicriteria decision making, outranking, optimization, games theory, coalition analysis, and other disciplines.

A wide range of management and technology problems in business and organizations like supply chain risk management, portfolio selection, sorting, trading, image treatment, risk management, design of processes and products, failure dynamics study, big data optimization, text mining, public policies, political collaboration in campaigns, human capital, competences management, customer relationship management, corporate open data assessing, decision support in medicine, public policies, social wellbeing analysis, evaluation of energy efficiency, video indexing, retrieval based on content, signal processing, coalition analysis, group decision making, minimum cost consensus, etc. are presented using the mentioned methods and mixing them.

Prof. Dr. Rafael Alejandro Espin Andrade
Prof. Dr. Witold Pedrycz
Guest Editors

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