Stock Market prediction is one of the hottest fields of research due to its commercial applications and the attractive benefits it offers. Nevertheless, the major challenge confronting stock investors is forecasting price movements in stock markets. For these reasons, this thesis presents a stock trend prediction model, generating a signal of either up, constant or down for each trading day based on the historical price of the stock only. The work goal is to give as many accurate predictions as possible. The presented model is a development of an integrated stock market trend prediction model based on Artificial Neural Network and fuzzy logic rules. This study constructs a hybrid model utilizing technical analysis tools: technical indicators and Elliott’s wave theory. The presented model will be conducted by developing predictor system, consisting of three main phases. In the first phase a trend predictor model based on neural network is developed. The Second phase is a fuzzy rule based system to predict the short term stock trend. The third and last phase is integration between the first two phases using neural network. This phase work on generating the final output.
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Maha M. Abdelrasoul is a Computer Science PhD student at Old Dominion University, earned her Master degree from Arab Academy for Science and Technology in 2011.Her research interests include Pattern Recognition, machine learning, Image processing, time series analysis, bio-informatics
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abdelrasoul MahaMaha M. Abdelrasoul is a Computer Science PhD student at Old Dominion University, earned her Master degree from Arab Academy for Science and Technology in 2011.Her research interests include Pattern Recognition, machi. Codice articolo 151242710
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Stock Market prediction is one of the hottest fields of research due to its commercial applications and the attractive benefits it offers. Nevertheless, the major challenge confronting stock investors is forecasting price movements in stock markets. For these reasons, this thesis presents a stock trend prediction model, generating a signal of either up, constant or down for each trading day based on the historical price of the stock only. The work goal is to give as many accurate predictions as possible. The presented model is a development of an integrated stock market trend prediction model based on Artificial Neural Network and fuzzy logic rules. This study constructs a hybrid model utilizing technical analysis tools: technical indicators and Elliott's wave theory. The presented model will be conducted by developing predictor system, consisting of three main phases. In the first phase a trend predictor model based on neural network is developed. The Second phase is a fuzzy rule based system to predict the short term stock trend. The third and last phase is integration between the first two phases using neural network. This phase work on generating the final output. 132 pp. Englisch. Codice articolo 9783330800106
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Stock Market prediction is one of the hottest fields of research due to its commercial applications and the attractive benefits it offers. Nevertheless, the major challenge confronting stock investors is forecasting price movements in stock markets. For these reasons, this thesis presents a stock trend prediction model, generating a signal of either up, constant or down for each trading day based on the historical price of the stock only. The work goal is to give as many accurate predictions as possible. The presented model is a development of an integrated stock market trend prediction model based on Artificial Neural Network and fuzzy logic rules. This study constructs a hybrid model utilizing technical analysis tools: technical indicators and Elliott's wave theory. The presented model will be conducted by developing predictor system, consisting of three main phases. In the first phase a trend predictor model based on neural network is developed. The Second phase is a fuzzy rule based system to predict the short term stock trend. The third and last phase is integration between the first two phases using neural network. This phase work on generating the final output. Codice articolo 9783330800106
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Taschenbuch. Condizione: Neu. Neuware -Stock Market prediction is one of the hottest fields of research due to its commercial applications and the attractive benefits it offers. Nevertheless, the major challenge confronting stock investors is forecasting price movements in stock markets. For these reasons, this thesis presents a stock trend prediction model, generating a signal of either up, constant or down for each trading day based on the historical price of the stock only. The work goal is to give as many accurate predictions as possible. The presented model is a development of an integrated stock market trend prediction model based on Artificial Neural Network and fuzzy logic rules. This study constructs a hybrid model utilizing technical analysis tools: technical indicators and Elliott¿s wave theory. The presented model will be conducted by developing predictor system, consisting of three main phases. In the first phase a trend predictor model based on neural network is developed. The Second phase is a fuzzy rule based system to predict the short term stock trend. The third and last phase is integration between the first two phases using neural network. This phase work on generating the final output.Books on Demand GmbH, Überseering 33, 22297 Hamburg 132 pp. Englisch. Codice articolo 9783330800106
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