Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm

Proceedings of the 3rd IASTED International Conference on Advances in Computer Science and Technology, ACST 2007

Volumn , Issue , 2007, Pages 388-392

  Yap, Keem Siah ^a   Abidin, Izham Z ^a   Ahmad, Abdul Rahim ^a   Hussien, Zahrul Faizi ^b   Pok, Hooi Loong ^b   Ismail, Fariq Izwan ^b   Mohamad, Abdul Malik ^c  

^a Centre for Microelectronic and Nano Engineering   (Malaysia)

^b UNITEN   (Malaysia)

^c NONE   (Malaysia)

Author keywords

Dual lagrangian optimization; Dynamic crossover point; Genetic algorithm; Pre populated database; Support vector machine

Indexed keywords

ALGORITHMS; COMPUTER SCIENCE; COMPUTERS; DATABASE SYSTEMS; DIESEL ENGINES; GENETIC ALGORITHMS; IMAGE RETRIEVAL; INTELLIGENT SYSTEMS; LEARNING SYSTEMS; MULTILAYER NEURAL NETWORKS; NEURAL NETWORKS; VECTORS;

10 FOLD CROSS VALIDATIONS; AND GENETIC ALGORITHMS; CLASSIFICATION TECHNIQUES; COMPARISON RESULTS; CONSUMPTION PATTERNS; CUSTOMER CONSUMPTION DATUMS; DETECTION ACCURACIES; DISTRIBUTION LOSSES; DUAL LAGRANGIAN OPTIMIZATION; DYNAMIC CROSSOVER POINT; FRAUD DETECTIONS; GAUSSIAN; GENERALIZATION PERFORMANCES; HYBRID ALGORITHMS; KERNEL PARAMETERS; MALAYSIA; OPTIMIZED SOLUTIONS; PRE-POPULATED DATABASE; RBF KERNELS; SUPPORT VECTOR MACHINE; SUPPORT VECTORS; SVM CLASSIFICATIONS; TECHNICAL LOSSES;

SUPPORT VECTOR MACHINES;

EID: 56149083812     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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