In this paper‎, ‎we study the class of rings in which every $P$-flat‎ ‎ideal is flat and which will be called $PFF$-rings‎. ‎In particular‎, ‎Von Neumann regular rings‎, ‎hereditary rings‎, ‎semi-hereditary ring‎, ‎PID and arithmetical rings are examples of $PFF$-rings‎. ‎In the context domain‎, ‎this notion coincide with‎ ‎Pr"{u}fer domain‎. ‎We provide necessary and sufficient conditions for‎...

The modeling of the relationships between the power loads and the variables that influence the power loads especially in the abnormal days is the key point to improve the performance of short-term load forecasting systems. To integrate the advantages of several forecasting models for improving the forecasting accuracy, based on data mining and artificial neural network techniques, an ensemble d...

Accurate forecasting of short-term passenger flow has been one of the most important issues in urban rail transit planning and operation. Considering the shortcomings of traditional forecasting methods, and in order to improve forecasting accuracy of passenger flow, this paper presents a wavelet neural network (WNN) for short-term passenger flow forecasting. One real urban rail transit station ...

Few clinical trials show important advantages for one therapy over another. When one does, a confirmatory trial will help decide whether the observation in the first trial was real. The need to replicate experimental results is fundamental in science. Systematic differences occur across clinical trials for a variety of reasons: differences in patient populations (geographically and over time), ...

T research examines the development of confidence and accuracy over time in the context of forecasting. Although overconfidence has been studied in many contexts, little research examines its progression over long periods of time or in consequential policy domains. This study employs a unique data set from a geopolitical forecasting tournament spanning three years in which thousands of forecast...

In this paper, we presented the performance of forecasting model and error correction will affect the accuracy of short-term load forecasting. Least squares support vector machines (LS-SVM) based on improved particle swarm optimization is selected as load forecasting model. Forecasting accuracy and generalization performance of LS-SVM depend on selection of its parameters greatly. Adaptive part...

The rising share of renewable energy in the mix brings with it new challenges such as power curtailment and lack reliable large-scale grid. forecasting wind generation for provision flexibility, defined ability to absorb manage fluctuations demand supply by storing at times surplus releasing when needed, is important. In this study, short-term models were developed using conventional time-serie...