Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches.
The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Preface. Methodologies. Accuracy and Transparency of Fuzzy Systems; R. Babuska. Should Tendency Assessment Precede Rule Extraction by Clustering? (No!); J.C. Bezdek, et al. A Review of Wavelet Networks, Wavenets, Fuzzy Wavenets and their Applications; M. Thuillard. Investigating Neural Network Efficiency and Structure by Weight Investigation; M. Lefley, T. Kinsella. An Evaluation of Confidence Bound Estimation Methods for Neural Networks; L. Yang, et al. Compensation of Periodic Disturbances in Continuous Processing Plants by Means of a Neural Controller; M. Rau, D. Schröder. Predictive Control with Restricted Genetic Optimisation; S. Garrido, et al. Adaptive Parameterization of Evolutionary Algorithms and Chaotic Populations; M. Annunziato, S. Pizzuti. Neuro-Fuzzy Systems for Rule-Based Modelling of Dynamic Processes; M.B. Gorzalczany, A. Gluszek. Hybrid Intelligent Architectures using a Neurofuzzy Approach; L.P. Maguire, et al. Unifying Learning with Evolution Through Baldwinian Evolution and Lamarckism; C. Giraud-Carrier. Using An Evolutionary Strategy to Select Input Features for a Neural Network Classifier; J. Strackeljan, A. Schubert. Advances in Machine Learning; M.W. van Someren. Symbolic and Neural Learning of Named-Entity Recognition and Classification Systems in Two Languages; G. Petasis, et al. Fuzzy Model-Based Reinforcement Learning; M. Appl, W. Brauer. A Cellular Space for Feature Extraction and Classification; C. Kuhn, J. Wernstedt. Applications. A Fuzzy Approach to Taming the Bullwhip Effect; C. Carlsson, R. Fullér. Forecast of Short Term Trends in Stock Exchange using Fuzzy Rules and Neural Networks on Multiresolution Processed Signals; A. Tsakonas, et al. Customer Relationship Management: A Combined Approachby Customer Segmentation and Database Marketing; M. Nelke. A New Vendor Evaluation Product for SAP R/3® Systems; U. Grimmer, et al. About Robustness of Fuzzy Logic PD and PID Controller under Changes of Reasoning Methods; B.S. Butkiewicz. Control of MIMO Dead Time Processes Using Fuzzy Relational Models; B.A. Gormandy, et al. Fuzzy Sliding Mode Controllers Synthesis through Genetic Optimization; M. Dotoli, et al. Fuzzy RED: Congestion Control for TCP/IP Diff-Serv; L. Rossides, et al. The Use of Reinforcement Learning Algorithms in Traffic Control of High Speed Networks; A. Atlasis, A. Vasilakos. Fuzzy Reasoning in WCDMA Radio Resource Functions; T. Frantti, P. Mähönen. Odour Classification based on Computational Intelligence Techniques; G. Tselentis, et al. Fuzzy Rule Based Systems for Diagnosis of Stone Construction Cracks of Buildings; S. Shtovba, et al. Automated Design of Multi-Drilling Gear Machines; G. Klene, et al. Optimal Design of Alloy Steels Using Genetic Algorithms; M. Mahfouf. Intelligent Systems in Biomedicine; M.F. Abbod, et al. Diagnosis of Aphasia Using Neural and Fuzzy Techniques; J. Jantzen, et al. Gene Expression Data Mining for Functional Genomics using Fuzzy Technology; R. Guthke, et al. Symbolic, Neural and Neuro-fuzzy Approaches to Pattern Recognition in Cardiotocograms; O. Fontenla-Romero, et al. Perspectives of Computational Intelligence; G. Tselentis, M.W. van Someren. Index.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
EUR 28,73 per la spedizione da Regno Unito a Italia
Destinazione, tempi e costiEUR 9,70 per la spedizione da Germania a Italia
Destinazione, tempi e costiDa: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologicall. Codice articolo 5830671
Quantità: Più di 20 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9789401038720_new
Quantità: Più di 20 disponibili
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches.The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 536 pp. Englisch. Codice articolo 9789401038720
Quantità: 1 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches.The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence. Codice articolo 9789401038720
Quantità: 1 disponibili
Da: California Books, Miami, FL, U.S.A.
Condizione: New. Codice articolo I-9789401038720
Quantità: Più di 20 disponibili
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Condizione: New. Codice articolo ABLIING23Apr0412070054112
Quantità: Più di 20 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 536 Index. Codice articolo 2654517722
Quantità: 4 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand pp. 536 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam. Codice articolo 55074821
Quantità: 4 disponibili
Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND pp. 536. Codice articolo 1854517712
Quantità: 4 disponibili
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Advances in Computational Intelligence and Learning: Methods and Applications presents new developments and applications in the area of Computational Intelligence, which essentially describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics. Generally Fuzzy Technology, Artificial Neural Nets and Evolutionary Computing are considered to be such approaches.The Editors have assembled new contributions in the areas of fuzzy sets, neural sets and machine learning, as well as combinations of them (so called hybrid methods) in the first part of the book. The second part of the book is dedicated to applications in the areas that are considered to be most relevant to Computational Intelligence. 536 pp. Englisch. Codice articolo 9789401038720
Quantità: 2 disponibili