In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation o...
This paper is concerned with the reliable prediction of electricity demands using the Adaptive Neuro...
The paper discusses the implementation of a fuzzy-logic approach to provide a structural framework f...
This paper presents an experiment that consists of constructing auto-regressive moving average (ARMA...
Electricity is one of the energy types that have attracted a lotof interest due to its versatility.R...
Electricity is one of the energy types that have attracted a lotof interest due to its versatility.R...
Electrical energy consumption forecasting is, nowadays, essential in order to deal with the new para...
Making forecasts for the development of a given process over time, which depends on many factors, is...
Electricity is an important asset that influences not only the economy, but political or social secu...
Accurate prediction of future electrical power demands greatly facilitates the task of power generat...
Forecasting the electricity consumption is one of the most challenging tasks for energy domain stake...
Power load forecasting is an essential tool for energy management systems. Accurate load forecasting...
Seasonal fluctuations in electricity consumption, an uneven load of supply lines reduce not only the...
Forecasting the electricity consumption is one of the most challenging tasks for energy domain stake...
This paper proposes a novel hybrid strategy based on intelligent approaches to forecast electricity ...
Abstract—Electric load forecasting is an important research field to increase reliability of power s...
This paper is concerned with the reliable prediction of electricity demands using the Adaptive Neuro...
The paper discusses the implementation of a fuzzy-logic approach to provide a structural framework f...
This paper presents an experiment that consists of constructing auto-regressive moving average (ARMA...
Electricity is one of the energy types that have attracted a lotof interest due to its versatility.R...
Electricity is one of the energy types that have attracted a lotof interest due to its versatility.R...
Electrical energy consumption forecasting is, nowadays, essential in order to deal with the new para...
Making forecasts for the development of a given process over time, which depends on many factors, is...
Electricity is an important asset that influences not only the economy, but political or social secu...
Accurate prediction of future electrical power demands greatly facilitates the task of power generat...
Forecasting the electricity consumption is one of the most challenging tasks for energy domain stake...
Power load forecasting is an essential tool for energy management systems. Accurate load forecasting...
Seasonal fluctuations in electricity consumption, an uneven load of supply lines reduce not only the...
Forecasting the electricity consumption is one of the most challenging tasks for energy domain stake...
This paper proposes a novel hybrid strategy based on intelligent approaches to forecast electricity ...
Abstract—Electric load forecasting is an important research field to increase reliability of power s...
This paper is concerned with the reliable prediction of electricity demands using the Adaptive Neuro...
The paper discusses the implementation of a fuzzy-logic approach to provide a structural framework f...
This paper presents an experiment that consists of constructing auto-regressive moving average (ARMA...