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

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

This paper presents an intelligent system to reduce Non Technical Loss (NTL) using hybrid Support Vector Machine (SVM) and Genetic Algorithm (GA). The main motivation for this research is to assist Sabah Electricity Sdn. Bhd. (SESB) to reduce their distribution loss, estimated around 15% at present...

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Bibliographic Details
Main Authors:	Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.
Other Authors:	24448864400
Format:	Conference Paper
Published:	2023
Subjects:	Dual lagrangian optimization Dynamic crossover point Genetic algorithm Pre-populated database Support vector machine 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 Fraud detections Gaussian Generalization performances Hybrid algorithms Kernel parameters Malaysia Optimized solutions RBF kernels Support vectors SVM classifications Technical losses Support vector machines
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm

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