Application of supervised learning artificial neural networks [CPNN, BPNN ] for solving power flow problem

IET Seminar Digest

Volumn 2007, Issue 2, 2007, Pages 156-160

  Rathinam, A ^a   Padmini, S ^a   Ravikumar, V ^a  

^a SRM INSTITUTE OF SCIENCE AND TECHNOLOGY   (India)

Author keywords

Admittance matrix; Counterpropagation neural network; Grossberg layer; Kohonen layer

Indexed keywords

ADMITTANCE MATRIX; ARTIFICIAL NEURAL NETWORK; BUS SYSTEMS; BUS VOLTAGE MAGNITUDE; COMPETITIVE LEARNING; COMPUTATION TIME; COUNTER PROPAGATION NEURAL NETWORKS; COUNTERPROPAGATION NEURAL NETWORK; EUCLIDEAN DISTANCE; FAST DECOUPLED; FAST DECOUPLED LOAD FLOW; FAST LEARNING; GROSSBERG LAYER; HIDDEN NEURONS; KOHONEN LAYER; LOAD FLOW; LOADING CONDITION; MULTILAYER FEEDFORWARD NETWORKS; NETWORK PARAMETERS; NON-LINEAR; ON-LINE APPLICATIONS; OPERATION AND CONTROL; POWER FLOW PROBLEM; POWER FLOW STUDIES; POWER FLOWS; POWER SYSTEM PLANNING; POWER SYSTEMS; POWER UTILITY; STATIC STATE; STEADY-STATE OPERATING CONDITIONS; TRAINING TIME;

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; EDUCATION; ELECTRIC POTENTIAL; ELECTRIC POWER TRANSMISSION NETWORKS; FEATURE EXTRACTION; FEEDFORWARD NEURAL NETWORKS; MATHEMATICAL MODELS; MULTILAYER NEURAL NETWORKS; NEWTON-RAPHSON METHOD; ONLINE SYSTEMS; POWER TRANSMISSION;

LEARNING ALGORITHMS;

EID: 67650448243     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1049/ic:20070603     Document Type: Conference Paper

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