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Advances in computational intelligence and learning : methods and applications

Advances in computational intelligence and learning : methods and applications (1회 대출)

자료유형
단행본
개인저자
Zimmermann, H.-J. (Hans-Ju<rgen) , 1934-
서명 / 저자사항
Advances in computational intelligence and learning : methods and applications / edited by Hans-Ju<rgen Zimmermann ... [et al.].
발행사항
Boston :   Kluwer Academic Publishers,   c2002.  
형태사항
xvi, 511 p. : ill. ; 25 cm.
총서사항
International series in intelligent technologies ; 18
ISBN
0792376455 (acid-free paper)
일반주기
Includes index.  
일반주제명
Computational intelligence. Machine learning.
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245 0 0 ▼a Advances in computational intelligence and learning : ▼b methods and applications / ▼c edited by Hans-Ju<rgen Zimmermann ... [et al.].
260 ▼a Boston : ▼b Kluwer Academic Publishers, ▼c c2002.
300 ▼a xvi, 511 p. : ▼b ill. ; ▼c 25 cm.
440 0 ▼a International series in intelligent technologies ; ▼v 18
500 ▼a Includes index.
650 0 ▼a Computational intelligence.
650 0 ▼a Machine learning.
700 1 ▼a Zimmermann, H.-J. ▼q (Hans-Ju<rgen) , ▼d 1934-

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/서고6층/ 청구기호 006.3 A2443 등록번호 111228754 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

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. Schroder. 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. Fuller. 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. Mahonen. 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.


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