Load identification in neural networks for a non-intrusive monitoring of industrial electrical loads

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5236 LNCS, Issue , 2008, Pages 664-674

  Chang, Hsueh Hsien ^a,b   Yang, Hong Tzer ^b   Lin, Ching Lung ^c  

^a Jin Wen University of Science and Technology   (Taiwan)

^b CHUNG YUAN CHRISTIAN UNIVERSITY   (Taiwan)

^c MINGHSIN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

Author keywords

Electromagnetic Transient Program; Load identification; Neural network; Non intrusive load monitoring

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; CLASSIFIERS; COMPUTATIONAL EFFICIENCY; COMPUTER NETWORKS; DYNAMIC LOADS; ELECTRIC LOADS; ELECTRIC NETWORK ANALYSIS; ELECTRIC SURGES; ELECTROMAGNETISM; GROUPWARE; INTERACTIVE COMPUTER SYSTEMS; LEARNING SYSTEMS; PAPER; TRANSIENTS; VECTOR QUANTIZATION; VEGETATION;

BACK PROPAGATIONS; COMPUTATIONAL REQUIREMENTS; COMPUTATIONAL TIMES; DATA SETS; ELECTRICAL LOADS; ELECTROMAGNETIC TRANSIENT PROGRAM; FEATURE SELECTIONS; INDUSTRIAL LOADS; LEARNING VECTOR QUANTIZATIONS; LOAD IDENTIFICATION; LOAD MEASUREMENTS; MULTIPLE OPERATIONS; NEURAL NETWORK CLASSIFIERS; NON-INTRUSIVE LOAD MONITORING; POWER SIGNATURES; TRANSIENT ENERGIES;

NEURAL NETWORKS;

EID: 58349119360     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-92719-8_60     Document Type: Conference Paper

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