Hybrid Clustering-GWO-NARX neural network technique in predicting stock price
نویسندگان
چکیده
منابع مشابه
Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend
This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature...
متن کاملForecasting Wheat Price Using Backpropagation And NARX Neural Network
--------------------------------------------------ABSTRACT-------------------------------------------------------This study aims to investigate suitable model and forecast future wheat price using backpropagation neural network (BPNN) and nonlinear autoregressive models with exogenous inputs (NARX) networks. The price of wheat was estimated using prices of 3 types of grains widely used in agric...
متن کاملStock Price Prediction Using Quantum Neural Network
Quantum Neural Network (QNN) can improve upon the inadequacies of the classical neural network (CNN). The CNN requires a huge memory and needs more computational power. A new field of computation is emerging which integrates quantum computation with CNN. A quantum inspired hybrid model of quantum neurons and classical neurons is proposed. This paper details an approach, perhaps the first attemp...
متن کاملA Hybrid Fuzzy-Neural System for Egyptian Stock Price Prediction
In this paper, a hybrid fuzzy-neural system for Egyptian stock price prediction is proposed. In order to help in choosing the right stock mixture with the highest profit within a certain risk factor, a hybrid fuzzy-neural system is applied to significantly save effort and time of portfolio managers and increase the individual investors’ local market understanding by providing buy and sell signa...
متن کاملA Fuzzy Neural Network Model for Forecasting Stock Price
In this paper, a neural network-driven fuzzy reasoning system for stock price forecast is proposed on the basis of improved Takagi-Sugeno reasoning model. The experimental result shows that the fuzzy neural network has such properties as fast convergence, high precision and strong function approximation ability and is suitable for real stock price prediction.
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: Journal of Physics: Conference Series
سال: 2017
ISSN: 1742-6588,1742-6596
DOI: 10.1088/1742-6596/892/1/012018