In view of the defects of the prediction model based on neural network, such as when doing
prediction of nonlinear sequence, it is likely to fall into local hypo-strong point, and the rate of …

The development of a fuzzy wavelet neural network (FWNN) for the prediction of electricity
consumption is presented. The fuzzy rules that contain wavelets are constructed. Based on …

Electricity load forecasting plays a paramount role in capacity planning, scheduling, and the
operation of power systems. Reliable and accurate planning and prediction of electricity …

Power load forecasting is an essential tool for energy management systems. Accurate load
forecasting supports power companies to make unit commitment decisions and schedule …

In this study, we present a new approach for load forecasting (LF) using a recurrent fuzzy
neural network (RFNN) for Kermanshah City. Imagine if there is a need for electricity in a …

Energy has been one of the most important topics of political and social discussion in recent
decades. A significant proportion of the country's revenues is derived from energy resources …

This paper proposes an adaptive fuzzy expert system to concurrently estimate and forecast
both long-term electricity and natural gas (NG) consumptions with hike in prices. Using a …

This research develops a weighted evolving fuzzy neural network for monthly electricity
demand forecasting in Taiwan. This study modifies the evolving fuzzy neural network …

Load forecasting is a critical element of power system operation, involving prediction of the
future level of demand to serve as the basis for supply and demand planning. This paper …

Forecasting of electricity load demand is key task for the effective operation and planning of
power system. Electrical load forecasting is the process of prediction future electrical load …