THE EFFECT OF INTERVAL LENGTH AND MODEL BASIS ON FUZZY TIME SERIES ELECTRIC LOAD FORECASTING.

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THE EFFECT OF INTERVAL LENGTH AND MODEL BASIS ON FUZZY TIME SERIES ELECTRIC LOAD FORECASTING.

Abstract:

Fuzzy Time Series (FTS) forecasting technique is the amalgamation of fuzzy logic and time series technique. The critical issue in FTS forecasting is the determination of the interval length. This paper therefore, is a research on the effect of varying interval length and model basis on electric load forecasting using Fuzzy Time Series Model. The methodology adopted is presented and the data used is the load (in MW/MVA) obtained from PHCN over a 24-week period. The data for 18 weeks is used as the test data while the remaining 6 weeks is the validation data. It is shown that varying interval length and model basis give different forecasting results and that interval length five gives a significantly better result than others based on the quantitative and qualitative performance test. Furthermore, the results obtained show that model basis of four gives better forecasting result when compared to model basis of five and six. The results obtained are presented and discussed from the standpoint of their degree of consistency exhibited by the two elements.

THE EFFECT OF INTERVAL LENGTH AND MODEL BASIS ON FUZZY TIME SERIES ELECTRIC LOAD FORECASTING.

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