GA-optimized neural network for forecasting the geomagnetic storm index
نویسندگان
چکیده
منابع مشابه
A New Optimized GA-RBF Neural Network Algorithm
When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and recognition precision. Aiming at this probl...
متن کاملDeveloping an Evolutionary Neural Network Model for Stock Index Forecasting
The past few years have witnessed a growing rate of attraction in adoption of Artificial Intelligence (AI) techniques and combining them to improve forecasting accuracy in different fields. Besides, stock market forecasting has always been a subject of interest for most investors and professional analysts. Stock market forecasting is a tough problem because of the uncertainties involved in the ...
متن کاملStudy on Gold Price Forecasting Technique Based on Neural Network Optimized by GA with Projection Pursuit Algorithm
Gold price has significant nonlinearity and time-variance with many indeterminate influencing factors. In order to improve the forecast accuracy of gold price, this paper puts forward a gold price forecast model combing projection pursuit with neural network. At first, projection pursuit algorithm is used to screen the influencing factors, and then the influencing factors are used as the input ...
متن کاملStock Index Forecasting Using PSO Based Selective Neural Network Ensemble
Stock market analysis is one of the most important and hard problems in finance analysis field. Recently, the usage of intelligent systems for stock market prediction has been widely established. In this paper, a PSO based selective neural network ensemble (PSOSEN) algorithm is proposed, which is used for the Nasdaq-100 index of Nasdaq Stock Market and the S&P CNX NIFTY stock index analysis. In...
متن کاملA framework for neural network to make business forecasting with hybrid VAR and GA components
improve the NN's prediction capability. Two case studies have been carried out to demonstrate how to build our VAR-NN-GA system and its advantages. One is on the tourist patterns. Relatively recently, neural network is introduced into the tourist forecasting field [1, 2, 3]. Results show that the hybrid forecasting system is more robust and able to select variables automatically and makes more ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Geofísica Internacional
سال: 2018
ISSN: 0016-7169
DOI: 10.22201/igeof.00167169p.2018.57.4.2104