Intelligent systems, or artificial intelligence technologies, are playing an increasing role in areas ranging from medicine to the major manufacturing industries to financial markets. The consequences of flawed artificial intelligence systems are equally wide ranging and can be seen, for example, in the programmed trading-driven stock market crash of October 19, 1987. Intelligent Systems: Technology and Applications, Six Volume Set connects theory with proven practical applications to provide broad, multidisciplinary coverage in a single resource. In these volumes, international experts present case-study examples of successful practical techniques and solutions for diverse applications ranging from robotic systems to speech and signal processing, database management, and manufacturing.
Intelligence systems. We perfonn routine tasks on a daily basis, as for example: • recognition of faces of persons (also faces not seen for many years), • identification of dangerous situations during car driving, • deciding to buy or sell stock, • reading hand-written symbols, • discriminating between vines made from Sauvignon Blanc, Syrah or Merlot grapes, and others. Human experts carry out the following: • diagnosing diseases, • localizing faults in electronic circuits, • optimal moves in chess games. It is possible to design artificial systems to replace or "duplicate" the human expert. There are many possible definitions of intelligence systems. One of them is that: an intelligence system is a system able to make decisions that would be regarded as intelligent ifthey were observed in humans. Intelligence systems adapt themselves using some example situations (inputs of a system) and their correct decisions (system's output). The system after this learning phase can make decisions automatically for future situations. This system can also perfonn tasks difficult or impossible to do for humans, as for example: compression of signals and digital channel equalization.
This volume constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Fuzzy Logic and Applications held in Naples, Italy, in October 2003. The 40 revised full papers presented have gone through two rounds of reviewing and revision. All current issues of theoretical, experimental and applied fuzzy logic and related techniques are addressed with special attention to rough set theory, neural networks, genetic algorithms and soft computing. The papers are organized in topical section on fuzzy sets and systems, fuzzy control, neuro-fuzzy systems, fuzzy decision theory and application, and soft computing in image processing.
Hard boundaries have traditionally existed between such fields as fuzzy systems, neural networks, genetic algorithms, chaotic systems and expert systems. Gradually those boundaries are tending to vanish and "soft computing"-based systems that mix these different approaches have begun to emerge. Soft Computing Techniques in Human-Related Sciences focuses on the use of novel techniques such as artificial neural networks, fuzzy logic and genetic algorithms to solve practical problems related to humans: their activities, health and social needs. This volume illustrates and presents in an organized manner some of the recent progress in the applications of soft computing to fields related to social science, medical science, psychology, psychiatry , management of health and community services, and humanoid robots. Soft Computing Techniques in Human-Related Sciences begins with an introductory chapter to aid newcomers with the basic concepts, and progresses to the methodology of the use of soft computing in robotics, prosthetics, medicine, psycchology and man-machine interaction.
The 30 coherently written chapters by leading researchers presented in this anthology are devoted to basic results achieved in computational intelligence since 1997. The book provides complete coverage of the core issues in the field, especially in fuzzy logic and control as well as for evolutionary optimization algorithms including genetic programming, in a comprehensive and systematic way. Theoretical and methodological investigations are complemented by prototypic applications for design and management tasks in electrical engineering, mechanical engineering, and chemical engineering. This book will become a valuable source of reference for researchers active in computational intelligence. Advanced students and professionals interested in learning about and applying advanced techniques of computational intelligence will appreciate the book as a useful guide enhanced by numerous examples and applications in a variety of fields.
This text provides guidelines to develop tools for smart processing of knowledge and information. It uses cutting-edge ideas, recent research, and case studies to explore the complexities and challenges of modern knowledge management issues.
This book constitutes the refereed proceedings of the 6th Industrial Conference on Data Mining, ICDM 2006, held in Leipzig, Germany in July 2006. Presents 45 carefully reviewed and revised full papers organized in topical sections on data mining in medicine, Web mining and logfile analysis, theoretical aspects of data mining, data mining in marketing, mining signals and images, and aspects of data mining, and applications such as intrusion detection, and more.
Computational intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Computational intelligence is a rapidly growing research field including a wide variety of problem-solving techniques inspired by nature. Traditionally computational intelligence consists of three major research areas: Neural Networks, Fuzzy Systems, and Evolutionary Computation. Neural networks are mathematical models inspired by brains. Neural networks have massively parallel network structures with many neurons and weighted connections. Whereas each neuron has a simple input-output relation, a neural network with many neurons can realize a highly non-linear complicated mapping. Connection weights between neurons can be adjusted in an automated manner by a learning algorithm to realize a non-linear mapping required in a particular application task. Fuzzy systems are mathematical models proposed to handle inherent fuzziness in natural language. For example, it is very difficult to mathematically define the meaning of “cold” in everyday conversations such as “It is cold today” and “Can I have cold water”. The meaning of “cold” may be different in a different situation. Even in the same situation, a different person may have a different meaning. Fuzzy systems offer a mathematical mechanism to handle inherent fuzziness in natural language. As a result, fuzzy systems have been successfully applied to real-world problems by extracting linguistic knowledge from human experts in the form of fuzzy IF-THEN rules. Evolutionary computation includes various population-based search algorithms inspired by evolution in nature. Those algorithms usually have the following three mechanisms: fitness evaluation to measure the quality of each solution, selection to choose good solutions from the current population, and variation operators to generate offspring from parents. Evolutionary computation has high applicability to a wide range of optimization problems with different characteristics since it does not need any explicit mathematical formulations of objective functions. For example, simulation-based fitness evaluation is often used in evolutionary design. Subjective fitness evaluation by a human user is also often used in evolutionary art and music. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers.
This book presents the state of the art of computational intelligence ion engineering. It offers challenging problems for efficient modeling of intelligent systems and details different methodologies of computational intelligence with real life applications.
The book is about the development of the theory of epistemic fields with the corresponding relational and information fields as a framework for the understanding of strategies and tactics of the theory of knowing as the production of intellectual investment flows and the theory of knowledge accumulation as the production of intellectual capital stocks in systems of factories and departments providing the foundations for the development of open algorithms in the open space of problem-solution dualities. The concepts and the roles of thinking and reasoning with curiosity, creativity, hope, Ill-posed problems, phantom problems, unsolved problems, misinformation, disinformation, fake news, and courage are introduced, defined, and analyzed on the cognitive journeys over the space of ignorance-knowledge dualities, where dualistic-polar conflicts between duals in the space of ignorance-knowledge dualities are resolved with the instruments of fuzzy optimization, the results of which are used to induced the zones of ignorance, the zones of knowledge, and the zones of contentions. A complete development of the set of connecting paths of spaces and sub-spaces is provided, where all varieties, categories, and spaces reside in dualistic-polar structures with knowledge stock viewed as a single tree with the same roots, one trunk, many branches, and a fruit cocktail. The ontological space contains the space of actual-potential dualities as the primary category of knowing, and the epistemological space contains the space of imagination-reality dualities as the derived category of knowing within the space of primary-derived dualities. The space of potentials contains the space of imaginations which contains the sub-spaces of possibility-impossibility, probability-improbability, and possibility-probability dualities with corresponding spaces of necessity-freedom and anticipation-expectation dualities leading to the conception of the possible-world-impossible-world dualities in the space of semantic-non-semantic dualities. This book is also a continuation of the sequence of my works on the theories of paradigms of thought, rationality, info-statics, info-dynamics, entropy, problem-solution dualities in self-contained mathematics and philosophy, and their relational connectivity to information, language, knowing, knowledge, cognitive practices and open maching learning relative to nominalism, and the space of construction-reduction dualities over the spaces of fundamental-applied, production-consumption, input-output, and cost-benefit dualities.
