2001, ISBN: 9783790814385

Gebunden, 308 Seiten, 241mm x 160mm x 22mm, Sprache(n): eng Novel neuro-fuzzy architectures and hybrid learning algorithmsOverview of early and latest results concerning neural networks a… More...

Gebunden, 308 Seiten, 241mm x 160mm x 22mm, Sprache(n): eng Novel neuro-fuzzy architectures and hybrid learning algorithmsOverview of early and latest results concerning neural networks and fuzzy sets and systemsIncludes supplementary material: sn.pub/extrasThe advent of the computer age has set in motion a profound shift in our perception of science -its structure, its aims and its evolution. Traditionally, the principal domains of science were, and are, considered to be mathe­ matics, physics, chemistry, biology, astronomy and related disciplines. But today, and to an increasing extent, scientific progress is being driven by a quest for machine intelligence - for systems which possess a high MIQ (Machine IQ) and can perform a wide variety of physical and mental tasks with minimal human intervention. The role model for intelligent systems is the human mind. The influ­ ence of the human mind as a role model is clearly visible in the methodolo­ gies which have emerged, mainly during the past two decades, for the con­ ception, design and utilization of intelligent systems. At the center of these methodologies are fuzzy logic (FL); neurocomputing (NC); evolutionary computing (EC); probabilistic computing (PC); chaotic computing (CC); and machine learning (ML). Collectively, these methodologies constitute what is called soft computing (SC). In this perspective, soft computing is basically a coalition of methodologies which collectively provide a body of concepts and techniques for automation of reasoning and decision-making in an environment of imprecision, uncertainty and partial truth. Versandkostenfreie Lieferung ArtificialIntelligence, fuzzy, fuzzysystems, gorithms, neuralnetworks, Neuro-fuzzySystems, algorithms, expertsystem, FuzzySet, fuzzysystem, geneticalgorithms, intelligence, IntelligentSystems<

ISBN: 9783790814385

The advent of the computer age has set in motion a profound shift in our perception of science -its structure, its aims and its evolution. Traditionally, the principal domains of science … More...

The advent of the computer age has set in motion a profound shift in our perception of science -its structure, its aims and its evolution. Traditionally, the principal domains of science were, and are, considered to be mathe­ matics, physics, chemistry, biology, astronomy and related disciplines. But today, and to an increasing extent, scientific progress is being driven by a quest for machine intelligence - for systems which possess a high MIQ (Machine IQ) and can perform a wide variety of physical and mental tasks with minimal human intervention. The role model for intelligent systems is the human mind. The influ­ ence of the human mind as a role model is clearly visible in the methodolo­ gies which have emerged, mainly during the past two decades, for the conception, design and utilization of intelligent systems. At the center of these methodologies are fuzzy logic (FL); neurocomputing (NC); evolutionary computing (EC); probabilistic computing (PC); chaotic computing (CC); and machine learning (ML). Collectively, these methodologies constitute what is called soft computing (SC). In this perspective, soft computing is basically a coalition of methodologies which collectively provide a body of concepts and techniques for automation of reasoning and decision-making in an environment of imprecision, uncertainty and partial truth. New Textbooks>Hardcover>Technology>Xxxsoftware Engr>* Desc Unknown, Physica-Verlag HD Core >2 >T<

ISBN: 9783790814385

The advent of the computer age has set in motion a profound shift in our perception of science -its structure, its aims and its evolution. Traditionally, the principal domains of science … More...

The advent of the computer age has set in motion a profound shift in our perception of science -its structure, its aims and its evolution. Traditionally, the principal domains of science were, and are, considered to be mathe­ matics, physics, chemistry, biology, astronomy and related disciplines. But today, and to an increasing extent, scientific progress is being driven by a quest for machine intelligence - for systems which possess a high MIQ (Machine IQ) and can perform a wide variety of physical and mental tasks with minimal human intervention. The role model for intelligent systems is the human mind. The influ­ ence of the human mind as a role model is clearly visible in the methodolo­ gies which have emerged, mainly during the past two decades, for the con­ ception, design and utilization of intelligent systems. At the center of these methodologies are fuzzy logic (FL); neurocomputing (NC); evolutionary computing (EC); probabilistic computing (PC); chaotic computing (CC); and machine learning (ML). Collectively, these methodologies constitute what is called soft computing (SC). In this perspective, soft computing is basically a coalition of methodologies which collectively provide a body of concepts and techniques for automation of reasoning and decision-making in an environment of imprecision, uncertainty and partial truth., Physica<