This paper presents the investigations of forecasting performance of different type of Feedforward Neural Networks (FNN) in forecasting the sunspot numbers. Feedforward Neural Network will be used in this investigation by using different learning algorithms, sunspot data models and FNN transfer functions. Simulations are done using Matlab 7 where customized Graphic User Interface (GUI) called `Sunspot Neural Forecaster' have been developed for analysis. A complete analysis for different learning algorithms, sunspot data models and FNN transfer functions are examined in terms of Mean Square Error (MSE) and correlation analysis. Finally, the best optimized FNN parameters will be used to forecast the sunspot numbers
Solar activity has significant impacts on human activities and health. One most commonly used measur...
Over the years, solar radiation is the area of major concern. Most of the inventions done in l...
The aim of this thesis is to explore the application of feed forward neural networks, and other nume...
This paper presents the investigations of forecasting performance of different type of Feedforward N...
¾This paper presents a feedforward neural network approach to sunspot forecasting. The sunspot serie...
A recurrent connectionist network has been designed to model sunspot data. Preliminary experimental ...
In this paper, multi step ahead prediction of monthly sunspot real time series are carried out. This...
This paper presents a solar energy prediction method using artificial neural networks (ANNs). An ANN...
Researchers in many fields share a deep interest in the sunspot activity of the Sun. This kind of sol...
In this paper the solar radiation forecasting in Pekan located in Pahang is presented. The time seri...
AbstractIn this paper the solar radiation forecasting in Pekan located in Pahang is presented. The t...
This project was to perform prediction of solar energy and radiation in Singapore. Artificial Neural...
This research assesses the feasibility of using artificial neural networks (ANN) to predict and impr...
Abstract In the present study, a prominent 11-year cycle, supported by the pattern of the autocorrel...
The availability of accurate empirical models for multi-step-ahead (MS) prediction is desirable in m...
Solar activity has significant impacts on human activities and health. One most commonly used measur...
Over the years, solar radiation is the area of major concern. Most of the inventions done in l...
The aim of this thesis is to explore the application of feed forward neural networks, and other nume...
This paper presents the investigations of forecasting performance of different type of Feedforward N...
¾This paper presents a feedforward neural network approach to sunspot forecasting. The sunspot serie...
A recurrent connectionist network has been designed to model sunspot data. Preliminary experimental ...
In this paper, multi step ahead prediction of monthly sunspot real time series are carried out. This...
This paper presents a solar energy prediction method using artificial neural networks (ANNs). An ANN...
Researchers in many fields share a deep interest in the sunspot activity of the Sun. This kind of sol...
In this paper the solar radiation forecasting in Pekan located in Pahang is presented. The time seri...
AbstractIn this paper the solar radiation forecasting in Pekan located in Pahang is presented. The t...
This project was to perform prediction of solar energy and radiation in Singapore. Artificial Neural...
This research assesses the feasibility of using artificial neural networks (ANN) to predict and impr...
Abstract In the present study, a prominent 11-year cycle, supported by the pattern of the autocorrel...
The availability of accurate empirical models for multi-step-ahead (MS) prediction is desirable in m...
Solar activity has significant impacts on human activities and health. One most commonly used measur...
Over the years, solar radiation is the area of major concern. Most of the inventions done in l...
The aim of this thesis is to explore the application of feed forward neural networks, and other nume...