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[Annotatie]: This book comprises a selection of papers from IFSA 2007 on new methods for analysis and design of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including fuzzy logic, neural networks, and genetic algorithms, which can be used to produce powerful hybrid intelligent systems for solving problems in pattern recognition, time series prediction, intelligent control, robotics and automation. Hybrid intelligent systems that combine several SC techniques are needed due to the complexity and high dimensionality of real-world problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of these systems, for this reason it is very important to optimize architecture design. The architectures can combine, in different ways, neural networks, fuzzy logic and genetic algorithms, to achieve the ultimate goal of pattern recognition, time series prediction, intelligent control, or other application areas. TOC:Part I Type-2 Fuzzy Logic: Theory and Applications.- Part II Fuzzy Clustering: Theory and Applications.- Part III Intelligent Identification and Control .- Part IV Time Series Prediction.- Part V Pattern Recognition.- Part VI Evolutionary Computation.- Part VII Fuzzy Modeling.- Part VIII Intelligent Manufacturing and Scheduling.- Part IX Intelligent Agents.- Part X Neural Networks Theory.- Part XI Robotics.- Part XII Fuzzy Logic Applications.[Flaptekst]: This book comprises a selection of papers on new methods for analysis and design of hybrid intelligent systems using soft computing techniques from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007. |
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