Short Term Load Forcasting Using Heuristic Algorithm and Support Vector Machine

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 772)


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).


Short-term Load Support Vector Machine (SVM) Forcasting Test Multiple Times Inner Mongolia Regional 
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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Abasyn University Department of Computing and TechnologyIslamabadPakistan
  2. 2.COMSATS Institute of Information TechnologyIslamabadPakistan
  3. 3.Islamic International UniversityIslamabadPakistan
  4. 4.The University of Lahore, Gujrat CampusGujranwalaPakistan
  5. 5.Mirpur University of Science and TechnologyAzad KashmirPakistan

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