Short Term Load Forcasting Using Heuristic Algorithm and Support Vector Machine
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Analysis of data is very important for accurate prediction. Particle Swarm Optimization (PSO) and Support Vector Machine (SVM) is used for load forcasting. Features are selected using PSO and redundant features are removed. Data is divided into training and testing data. Load forecasting is done by using SVM classifier. However, SVM classifier predicts short term load accurately and efficiently. Multiple time testing is done on data for checking accuracy of PSO. SVM shows efficient performance as compared to Principle Component Analysis (PCA).
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