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FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Computational Intelligence for applied research. The contributions to the eighth edition in the series of FLINS conferences cover state-of-the-art research, development, and technology for computational intelligence systems in general, and for intelligent decision and control in particular.
FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Computational Intelligence for applied research. The contributions to the eighth edition in the series of FLINS conferences cover state-of-the-art research, development, and technology for computational intelligence systems in general, and for intelligent decision and control in particular.
FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Computational Intelligence for applied research. The contributions to the ninth in the series of FLINS conferences cover state-of-the-art research, development, and technology for computational intelligence systems — both from foundations and applications points-of-view.
In recent years, there has been a growing interest in the need for designing intelligent systems to address complex decision systems. One of the most challenging issues for the intelligent system is to effectively handle real-world uncertainties that cannot be eliminated. These uncertainties include various types of information that are incomplete, imprecise, fragmentary, not fully reliable, vague, contradictory, deficient, and overloading. The uncertainties result in a lack of the full and precise knowledge of the decision system, including the determining and selection of evaluation criteria, alternatives, weights, assignment scores, and the final integrated decision result. Computational intelligent techniques (including fuzzy logic, neural networks, and genetic algorithms etc.), which are complimentary to the existing traditional techniques, have shown great potential to solve these demanding, real-world decision problems that exist in uncertain and unpredictable environments. These technologies have formed the foundation for intelligent systems.
This volume is a tribute to Professor Dr Da Ruan, who passed away suddenly on July 31, 2011, aged 50. The flood of emails that spread throughout the fuzzy logic research community with the tragic news was testimony to the respect and liking felt for this remarkable man. Da was a hardworking , highly productive scientist who, during his short life, published 35 books and more than 250 research papers in highly ranked journals and conference proceedings. He established two successful conferences, FLINS and ISKE, as well as the international journal, JCIS. This book is a collection of contributions from 88 of Da's academic friends from 47 institutes, presented in 60 chapters and over 70 pictures. A Foreword by Lotfi Zadeh begins Da's story. Section 1 provides an overview of Da's funeral on August 6, 2011. Part II outlines Da’s scientific life, his education, scientific career, publications and keynote talks. Part III presents testimonials by Da's colleagues of academic activities, including guest professorships and his many visits to foreign institutes. Part IV contains thirty contributions from colleagues and friends across the world to describe their collaborative experience with Da. We hope this book will keep the memory of Da alive – great scientist, great friend, great humanitarian. He will remain in our hearts forever.
FLINS, originally an acronym for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended to Computational Intelligence for applied research. The contributions to the 10th of FLINS conference cover state-of-the-art research, development, and technology for computational intelligence systems, both from the foundations and the applications points-of-view. Sample Chapter(s). Foreword (55 KB). Evaluation of Manufacturing Technology of Photovoltaic Cells (124 KB). Contents: Decision Making and Decision Support Systems; Uncertainty Modeling; Foundations of Computational Intelligence; Statistics, Data Analysis and Data Mining; Intelligent Information Processing; Productivity and Reliability; Applied Research. Readership: Graduate students, researchers, and academics in artificial intelligence/machine learning, information management, decision sciences, databases/information sciences and fuzzy logic.
This book constitutes the refereed proceedings of the 12th International Conference on Artificial Intelligence and Symbolic Computation, AISC 2014, held in Seville, Spain, in December 2014. The 15 full papers presented together with 2 invited papers were carefully reviewed and selected from 22 submissions. The goals were on one side to bind mathematical domains such as algebraic topology or algebraic geometry to AI but also to link AI to domains outside pure algorithmic computing. The papers address all current aspects in the area of symbolic computing and AI: basic concepts of computability and new Turing machines; logics including non-classical ones; reasoning; learning; decision support systems; and machine intelligence and epistemology and philosophy of symbolic mathematical computing.
Decision making is an omnipresent, most crucial activity of the human being, and also of virtually all artificial broadly perceived “intelligent” systems that try to mimic human behavior, reasoning and choice processes. It is quite obvious that such a relevance of decision making had triggered vast research effort on its very essence, and attempts to develop tools and techniques which would make it possible to somehow mimic human decision making related acts, even to automate decision making processes that had been so far reserved for the human beings. The roots of those attempts at a scientific analysis can be traced to the ancient times but – clearly – they have gained momentum in the recent 50 or 100 years following a general boom in science. Depending on the field of science, decision making can be viewed in different ways. The most general view can be that decision making boils down to some cognitive, mental process(es) that lead to the selection of an option or a course of action among several alternatives. Then, looking in a deeper way, from a psychological perspective this process proceeds in the context of a set of needs, preferences, rational choice of an individual, a group of individuals, or even an organization. From a cognitive perspective, the decision making process proceeds in the context of various interactions with the environment.
This book presents selected papers from the 4th International Conference on Mechanical, Manufacturing and Plant Engineering (ICMMPE 2018), which was held in Melaka, Malaysia from the 14th to the 15th of November 2018. The proceedings discuss genuine problems concerning joining technologies that are at the heart of various manufacturing sectors. In addition, they present the outcomes of experimental and numerical works addressing current problems in soldering, arc welding and solid-state joining technologies.
This volume constitutes the refereed proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2017, held in La Rioja, Spain, in June 2017. The 60 full papers published in this volume were carefully reviewed and selected from 130 submissions. They are organized in the following topical sections: data mining, knowledge discovery and big data; bioinspired models and evolutionary computing; learning algorithms; visual analysis and advanced data processing techniques; data mining applications; and hybrid intelligent applications.