International Journal of Business Information Systems, 2012
Load forecasting is a significant factor in the planning and economic and secure operation of mod... more Load forecasting is a significant factor in the planning and economic and secure operation of modern power system. This research work has compared different forecasting techniques and opted to find out better technique in context of load generation, which varies rapidly from time to time. The dataset has been generated from yearly demand of electricity of Bangladesh for last five years. Four factors have been considered as input parameters (Year, Irrigation season, Temperature, Rainfall amount) where as single output is demand of load in adaptive neuro fuzzy inference system (ANFIS). Another artificial intelligence technique, artificial neural network (ANN) has been used to validate the output results. The best suited traditional technique for forecasting load generation is seasonal forecasting. Seasonal forecasting is also used to compare with ANFIS and ANN to find out better technique. The result of experiment indicates that ANFIS is superior method to tackle forecasting of load generation from different error measures.
International Journal of Business Information Systems, 2012
Load forecasting is a significant factor in the planning and economic and secure operation of mod... more Load forecasting is a significant factor in the planning and economic and secure operation of modern power system. This research work has compared different forecasting techniques and opted to find out better technique in context of load generation, which varies rapidly from time to time. The dataset has been generated from yearly demand of electricity of Bangladesh for last five years. Four factors have been considered as input parameters (Year, Irrigation season, Temperature, Rainfall amount) where as single output is demand of load in adaptive neuro fuzzy inference system (ANFIS). Another artificial intelligence technique, artificial neural network (ANN) has been used to validate the output results. The best suited traditional technique for forecasting load generation is seasonal forecasting. Seasonal forecasting is also used to compare with ANFIS and ANN to find out better technique. The result of experiment indicates that ANFIS is superior method to tackle forecasting of load generation from different error measures.
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