﻿ 基于粒子群算法LSSVM短期负荷预测模型研究

基于粒子群算法LSSVM短期负荷预测模型研究LSSVM Based on PSO Algorithm to Short-Term Load Forecasting Model Research

Abstract: Short-term load forecasting accuracy directly affects the reliability of power system operation and power supply quality. Least squares support vector machine short-term load forecasting model based on model particle swarm optimization algorithm is proposed. The model optimizes the parameter of least squares support vector machines, with the test set error as the basis of judgment for optimal selection of the model parameters so as to improve prediction accuracy, avoid blind choice of model parameters in the forecasting process and prevent dependence on least squares support vector machine experience. We use this model to predict the loads on the grid and prove that the model has better convergence, higher accuracy and faster training speed.

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