Title:
SVM_Short-term-Load-Forecasting
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Description: first expounds the recent application research of load forecasting, summarized the characteristics of load forecasting and influencing factors, summed up common methods of short-term load forecasting, and analyzed the advantages and disadvantages of each method then introduced statistical learning theory and the principle of SVM as the basis of support vector machine (SVM ) theory, SVM regression model is derived this paper adopted least squares support vector machine (LSSVM) model, according to the historical load data and meteorological data of a certain area of Zhejiang Taizhou, Analysised the various factors affecting the forecast, summed up the regularity of load change , amended "outliers" in the historical load data,the load forecasting factors to be considered were normalized. The two parameters of LSSVM have a significant impact on the model, but it is still soluted based on the experience currently. So, this paper adopted particle swarm optimization algorithm to optimized
- [pca-svm] - err
- [LS_SVMlab] - Least squares support vector machine cod
- [pso_gray] - Particle swarm optimization algorithm co
- [ANN] - bp neural network for short-term load fo
- [pso] - This is an implementation of Particle Sw
- [shili2] - Improved Particle Swarm Optimization and
- [113172231LSSVM] - LSSVN used to predict the program, want
- [POS-GA] - Article on the particle swarm optimizati
- [LS_SVM] - Least squares support vector machine for
- [FIG_SVM_sh] - Fuzzy- support vector machines for fuzzy
File list (Check if you may need any files):
数据\a23.xls
....\a45.xls
....\B2.xls
....\b3.xls
....\B4.xls
....\B5.xls
....\bdata1.xls
AdaptFunc.m
AdaptFunc1.m
BaseStepPso.m
gaijin.m
InitSwarm.m
pso.m
shorttime.m
基于支持向量机的短期电力负荷预测.doc
数据
