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Synopsis
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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À propos de l?auteur
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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- ÉditeurNoor Publishing
- Date d'édition2016
- ISBN 10 3330800100
- ISBN 13 9783330800106
- ReliureBroché
- Langueanglais
- Nombre de pages132
- Coordonnées du fabricantnon disponible
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Stock Market Trend Prediction Using Neural Networks and Fuzzy Logic
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Etat : 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. N° de réf. du vendeur 151242710
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Stock Market Trend Prediction Using Neural Networks and Fuzzy Logic
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783330800106
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Stock Market Trend Prediction Using Neural Networks and Fuzzy Logic
Edité par
Noor Publishing Okt 2016, 2016
ISBN 10 : 3330800100
ISBN 13 : 9783330800106
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783330800106
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Stock Market Trend Prediction Using Neural Networks and Fuzzy Logic
Edité par
Noor Publishing Okt 2016, 2016
ISBN 10 : 3330800100
ISBN 13 : 9783330800106
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783330800106
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Stock Market Trend Prediction Using Neural Networks and Fuzzy Logic
Vendeur : Revaluation Books, Exeter, Royaume-Uni
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Paperback. Etat : Brand New. 132 pages. 8.66x5.91x0.30 inches. In Stock. N° de réf. du vendeur 3330800100
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