Electricity demand forecasting is one of the most important factors in the planning, design, and operation of competitive electrical systems. However, most of the load forecasting methods are not accurate. Therefore, in order to increase the accuracy of the short-term electrical load forecast, this paper proposes a hybrid method for predicting electric load based on a deep neural network with a...

reservoir permeability is a critical parameter for the evaluation of hydrocarbon reservoirs. there are a lot of well log data related with this parameter. in this study, permeability is predicted using them and a supervised committee machine neural network (scmnn) which is combined of 30 estimators. all of data were divided in two low and high permeability populations using statistical study. e...

Abstract: Parking lots for electric vehicles (EVs) can make good utilization of the EVschr('39') battery capacity due to the large number of EVs. However, the location and size of parking lots will affect the distribution network condition. In this paper, a mixed-integer linear programming (MILP) model is proposed for locating and determining the optimal capacity of EVschr('39') parking lots co...