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Volume & Issue no: Volume 3, Issue 4, July - August 2014

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Title:
Neuro-Fuzzy System Optimized Based Quantum Differential Evolutionary for Stock Market Forecasting
Author Name:
Osman Hegazy , Omar S. Soliman and Ahmed A. Toony
Abstract:
Abstract: The main objective of this paper is to predict the gold price in the Forex market, it introduces the use of Quantum Differential Evolution Algorithm in a Neuro-fuzzy system composed of an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller used in prediction of stock market, specified by an optimization technique based on a double chains quantum differential evolution algorithm, to evaluate the proposed model three performance measurements are used: Root Mean Squared Error (RMSE), percentage error and Mean Tendency Error (MTE). The algorithm was evaluated with actual financial data and proved the weakness of the comparative method by showing much improved and better predictions by finding the best value for optimization variable in ANFIS using a double chains quantum differential evolution algorithm. Keywords: Fuzzy logic, Neural network, Stock market prediction, Neuro – Fuzzy, Differential evolution, Quantum evolutionary.
Cite this article:
Osman Hegazy , Omar S. Soliman and Ahmed A. Toony , " Neuro-Fuzzy System Optimized Based Quantum Differential Evolutionary for Stock Market Forecasting " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 3, Issue 4, July - August 2014 , pp. 106-110 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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