Add to ORKGPrediction of time series is a task that cannot be efficiently done by using feed forward neural network. Recurrent neural network are the suitable neural networks for time series prediction task. Electricity load series is also a kind of chaotic time series. In this paper a echo state network is proposed to calculate the electricity load after half an hour. No other type of data is used for prediction except the previous electricity load values. The predicted values obtained from various simulation runs are very close to the actual value
The paper describes a novel neural model to electrical load forecasting in transformers. The network...
Reliable operations and economical utilization of power systems require electricity load forecasting...
Recently, a hot research topic has been time series forecasting via randomized neural networks and i...
With the introduction of distributed generation and the establishment of smart grids, several new ch...
In this paper we approach the problem of forecasting a time-series of electrical load measured on th...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
Successfully determining competitive optimal schedules for electricity generation intimately hinges ...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
Improving the prediction accuracy in electric load forecasting is an important goal to be pursued in...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
In this paper we propose a semi-supervised neural network algorithm to identify unusual load pattern...
Prediction of the electrical load schedule of an electrical system is an important aspect for determ...
Prediction of the electrical load schedule of an electrical system is an important aspect for determ...
The paper describes a novel neural model to electrical load forecasting in transformers. The network...
Reliable operations and economical utilization of power systems require electricity load forecasting...
Recently, a hot research topic has been time series forecasting via randomized neural networks and i...
With the introduction of distributed generation and the establishment of smart grids, several new ch...
In this paper we approach the problem of forecasting a time-series of electrical load measured on th...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
Successfully determining competitive optimal schedules for electricity generation intimately hinges ...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
Improving the prediction accuracy in electric load forecasting is an important goal to be pursued in...
Echo State Network (ESN) attracted significant interest in the research activities in last years. In...
In this paper we propose a semi-supervised neural network algorithm to identify unusual load pattern...
Prediction of the electrical load schedule of an electrical system is an important aspect for determ...
Prediction of the electrical load schedule of an electrical system is an important aspect for determ...
The paper describes a novel neural model to electrical load forecasting in transformers. The network...
Reliable operations and economical utilization of power systems require electricity load forecasting...
Recently, a hot research topic has been time series forecasting via randomized neural networks and i...