Hybrid fuzzy-neural network-based composite contingency ranking employing fuzzy curves for feature selection

Neurocomputing

Volumn 73, Issue 1-3, 2009, Pages 506-516

  Chaturvedi, K T ^a   Pandit, Manjaree ^b   Srivastava, Laxmi ^b   Sharma, Jaydev ^c   Bhatele, R P ^d  

^a UNIVERSITY INSTITUTE OF TECHNOLOGY   (India)

^b MITS   (India)

^c INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

^d MPPTCL   (India)

Author keywords

Contingency ranking; Fuzzy composite performance index (FCPI); Fuzzy curves; Fuzzy neural network; Levenberg Marquardt algorithm; Membership values

Indexed keywords

CONTINGENCY RANKING; FUZZY COMPOSITE PERFORMANCE INDEX (FCPI); FUZZY CURVES; LEVENBERG-MARQUARDT ALGORITHM; MEMBERSHIP VALUES;

CEMENTS; DEREGULATION; ELECTRIC POWER TRANSMISSION NETWORKS; VOLTAGE STABILIZING CIRCUITS;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; CONTROLLED STUDY; ELECTRIC POTENTIAL; ELECTRICITY; FLOW RATE; FUZZY SYSTEM; HYBRID COMPUTER; INDIAN; LEARNING ALGORITHM; MATHEMATICAL COMPUTING; ONLINE SYSTEM; PRIORITY JOURNAL; PROCESS OPTIMIZATION;

EID: 70350702673     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2009.06.012     Document Type: Article

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