http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Soft computing in industrial electronics
It is expected that the use of soft computing will increase greatly in industrial applications, because the conceptual structure of hard computing is much too precise in relation to the great imprecision of the world around us. This book aims at attracting researchers and engineers both in the fields of industrial electronics (IE) and computational intelligence (CI). By approaching the different viewpoints of IE and CI people, it is hoped to provide practicing engineers with new solutions to the demanding real-world problems. The applications are divided into two categories, Electric Power Applications and Emerging Applications.
Part I: Electric Power Applications: X.-Z. Gao, S.J. Ovaska: Motor Fault Detection and Diagnosis Using Soft Computing -- M.P. Kazmierkowski, T. Orlowska-Kowalska: Neural Network Estimation and Neuro-Fuzzy Control in Converter-Fed Induction Motor Drives -- A.D. Cheok: High Robustness of Fuzzy Logic Systems in Switched Reluctance Motor Drives -- B. Tomescu, H.F. VanLandingham: On the Use of Fuzzy Logic to Control Paralleled DC-DC Converters -- A. Kamiya et al.: Soft Computing-Based Optimal Operation in Power Energy System -- A. Halinka et al.: Neural Network-Based Adaptive Protection System -- Part II: Emerging Applications: J. Niittymäki et al.: Fuzzy Logic-Based Traffic Controller -- T.G.W. Gordon, P.J. Bentley: On Evolvable Hardware -- T. Fujinaka et al.: Category Classification Using Neural Networks.
With bibliographical references and index.
Studies in fuzziness and soft computing ; 101