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http://ntur.lib.ntu.edu.tw/bitstream/246246/2007041910032021/1/00501839.pdf
In this paper, we propose an intelligent stock trading decision support system that can forecast the buying and selling signals according to the prediction of short-term and long-term trends using rule-based neural networks. This system can provide the user not only the stock trading suggestion but also the rules in the trained network.
https://www.researchgate.net/publication/3626473_A_rule-based_neural_stock_trading_decision_support_system
A rule-based neural stock trading decision support system. We propose an intelligent stock trading decision support system that can forecast the buying and selling signals according to the prediction of short-term and long-term trends using rule-based neural networks.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.471.4143
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): In this paper, we propose an intelligent stock trading decision support system that can forecast the buying and selling signals according to the prediction of short-term and long-term trends using rule-based neural networks. A rule-based neural network allows us to use domain knowledge in the form of inference rules ...
http://www.jimsjournal.org/28%20Jia-Hao%20Li.pdf
A Trading Decision Support System Based on Neuro-Fuzzy Technique: Evidence from Asian Stock Market Jia-Hao Li, Graduate School of Management, National Yunlin University of Science and Technology Jack J. W. Yang, Professor of Department of Finance , National Yunlin University of Science and Technology ABSTRACT
https://www.sciencedirect.com/science/article/pii/S0165011498003996
An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network Author links …Cited by: 351
https://www.researchgate.net/publication/224654606_An_ETF_Trading_Decision_Support_System_by_Using_Neural_Network_and_Technical_Indicators
We propose an intelligent stock trading decision support system that can forecast the buying and selling signals according to the prediction of short-term and long-term trends using rule-based ...
https://arxiv.org/pdf/1712.09592.pdf
An Artificial Neural Network-based Stock Trading System Using Technical Analysis and Big Data Framework ... the traditional decision support systems. Previous models are mostly based on static rules and analyses, hence can ... of our trading strategy. In our model, a stock is bought, sold
https://www.sciencedirect.com/science/article/pii/S0957417416301919
Oct 15, 2016 · Amornwattana, Enke, and Dagli (2007) illustrate the use of a hybrid options pricing model that uses multiple neural network models, along with a decision support system structure, to identify the correct stock options trading strategy based on direction and volatility forecast, as well as return forecasting (Enke & Amornwattana, 2008).Cited by: 66
https://link.springer.com/article/10.1007/BF02943610
Chou S.T., Yang C., Chen C. and Lai F. (1996), “A Rule-based Neural Stock Trading Decision Support System”,IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, 148–154. Google ScholarCited by: 9
http://www.iaeng.org/publication/WCECS2009/WCECS2009_pp312-316.pdf
statistic rules in essential trends of the stock market and implied rules can be recognized to a certain degree through the construction of proper clustering algorithm [9]. The authors’ proposed model for stock price prediction is based on Decision Support System (DSS) model by Turban et al. [10]. AI and DM are included in one of the subsystem
http://ntur.lib.ntu.edu.tw/bitstream/246246/2007041910032021/1/00501839.pdf
The proposed stock trading decision support system is composed of five components, namely, preprocessor, dual rule- based neural network module, postprocessor, initial …
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.471.4143
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): In this paper, we propose an intelligent stock trading decision support system that can forecast the buying and selling signals according to the prediction of short-term and long-term trends using rule-based neural networks. A rule-based neural network allows us to use domain knowledge in the form of inference rules ...
https://www.sciencedirect.com/science/article/pii/S0957417416301919
Oct 15, 2016 · Amornwattana, Enke, and Dagli (2007) illustrate the use of a hybrid options pricing model that uses multiple neural network models, along with a decision support system structure, to identify the correct stock options trading strategy based on direction and volatility forecast, as well as return forecasting (Enke & Amornwattana, 2008).Cited by: 66
https://link.springer.com/article/10.1007/s10489-007-0055-1
Jun 19, 2007 · Chou S-CT, Yang C-C, Chen C-H, Lai F (1996) A rule-based neural stock trading decision support system. In: Proceedings of the IEEE/IAFE conference on computer intelligence for financial engeneering, New York, pp 148–154Cited by: 17
https://www.sciencedirect.com/science/article/pii/S0165011498003996
An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network. ... T. ParngIntelligent stock trading decision support system using dual adaptive-structure neural networks. J. Inform. Sci. Eng., 9 (1993), pp. 271-297.Cited by: 351
http://www.iaeng.org/publication/WCECS2009/WCECS2009_pp312-316.pdf
Designing a Decision Support System Model for Stock Investment Strategy Chai Chee Yong and Shakirah Mohd Taib Proceedings of the World Congress on Engineering and Computer Science 2009 Vol I WCECS 2009, October 20-22, 2009, San Francisco, USA ISBN:978-988-17012-6-8 WCECS 2009
http://ntur.lib.ntu.edu.tw/bitstream/246246/2007041910032021/1/00501839.pdf
The proposed stock trading decision support system is composed of five components, namely, preprocessor, dual rule- based neural network module, postprocessor, initial …
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.471.4143
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): In this paper, we propose an intelligent stock trading decision support system that can forecast the buying and selling signals according to the prediction of short-term and long-term trends using rule-based neural networks. A rule-based neural network allows us to use domain knowledge in the form of inference rules ...
https://www.sciencedirect.com/science/article/pii/S0957417416301919
Oct 15, 2016 · Amornwattana, Enke, and Dagli (2007) illustrate the use of a hybrid options pricing model that uses multiple neural network models, along with a decision support system structure, to identify the correct stock options trading strategy based on direction and volatility forecast, as well as return forecasting (Enke & Amornwattana, 2008).Cited by: 69
https://link.springer.com/article/10.1007/s10489-007-0055-1
Jun 19, 2007 · Chou S-CT, Yang C-C, Chen C-H, Lai F (1996) A rule-based neural stock trading decision support system. In: Proceedings of the IEEE/IAFE conference on computer intelligence for financial engeneering, New York, pp 148–154Cited by: 17
https://www.sciencedirect.com/science/article/pii/S0165011498003996
An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network Author links open overlay panel R.J. Kuo a …Cited by: 350
http://www.iaeng.org/publication/WCECS2009/WCECS2009_pp312-316.pdf
Designing a Decision Support System Model for Stock Investment Strategy Chai Chee Yong and Shakirah Mohd Taib Proceedings of the World Congress on Engineering and Computer Science 2009 Vol I WCECS 2009, October 20-22, 2009, San Francisco, USA ISBN:978-988-17012-6-8 WCECS 2009
http://www.jimsjournal.org/28%20Jia-Hao%20Li.pdf
A Trading Decision Support System Based on Neuro-Fuzzy Technique: Evidence from Asian Stock Market Jia-Hao Li, Graduate School of Management, National Yunlin University of Science and Technology Jack J. W. Yang, Professor of Department of Finance , National Yunlin University of Science and Technology ABSTRACT
http://ntur.lib.ntu.edu.tw/bitstream/246246/2007041910032021/1/00501839.pdf
The proposed stock trading decision support system is composed of five components, namely, preprocessor, dual rule- based neural network module, postprocessor, initial rule generator and rule extractor.
https://www.researchgate.net/publication/3626473_A_rule-based_neural_stock_trading_decision_support_system
An intelligent stock trading decision support system that can forecast the buying and selling signals according to the prediction of short-term and long-term trends using rule-based NNs is developed in [43]. The NN component is composed of two rule-based NNs and they are used to predict the price trend of stocks…
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.471.4143
In this paper, we propose an intelligent stock trading decision support system that can forecast the buying and selling signals according to the prediction of short-term and long-term trends using rule-based neural networks. A rule-based neural network allows us to use domain knowledge in the form of inference rules to set up the initial structure of the neural network, and to extract refined domain knowledge from the trained …
http://www.jimsjournal.org/28%20Jia-Hao%20Li.pdf
The trading rules for the Stochastics trading system are as follows: Rule 1. Overbought conditions are generally taken as occurring when the D is greater than 80; oversold is taken when D is less than 20. Rule 2. When K breaks through D from up, then sell out. When K breaks through D from down then buy in. Whenever either rule is satisfied, the trading is conducted accordingly.
https://link.springer.com/chapter/10.1007/978-3-540-30537-8_27
A Neural Network and Web-Based Decision Support System for Forex Forecasting and Trading. Abstract. This study presents a neural network & web-based decision support system (DSS) for foreign exchange (forex) forecasting and trading decision, which is adaptable to the needs of financial organizations and individual investors.Cited by: 17
http://www.smallake.kr/wp-content/uploads/2017/04/1000009681354.pdf
In this paper, we implement an automatic stock decision support system, which utilizes DBNs to predict the highest and lowest stock price in the next period as the upper and lower boundary of the oscillation box and give an inspection rule in order to confirm whether a stock …
https://ieeexplore.ieee.org/document/1716414/
An ETF Trading Decision Support System by Using Neural Network and Technical Indicators Abstract: This paper proposed a neural network based decision support system (DSS) to provide investors with suggestions on transaction timing and transaction strategies of Taiwan 50 …
https://www.semanticscholar.org/paper/An-intelligent-stock-trading-decision-support-of-Kuo-Chen/40c238be863d8e1a38638d4b365911e9e38537a5
Mathematics, Computer Science; Published in Fuzzy Sets and Systems 2001; DOI: 10.1016/s0165-0114(98)00399-6 An intelligent stock trading decision support system through integration of genetic algorithm based fuzzy neural network and artificial neural network
https://ieeexplore.ieee.org/abstract/document/7097030
Abstract: This paper develops a new rule-based decision support system (RB-DSS) to find the safest solutions for routing, scheduling, and assignment in Hazmat transportation management. To define the safe program in RB-DSS, the accident frequency and severity are estimated for different scenarios of transportation, and they are used to classify the scenarios by a new structure of decision tree ...
https://journals.sagepub.com/doi/pdf/10.1177/2158244015579941
the skill or expertise of a seasoned trader. A genetic algorithm optimized Symbolic Aggregate approXimation (SAX)–Apriori. based stock trading recommender system, which can mine temporal association rules from the stock price data set to. generate stock trading recommendations, is …
https://www.amrita.edu/publication/temporal-association-rule-mining-based-decision-support-system-stock-trading
A temporal association rule mining based decision support system for stock trading
https://quizlet.com/281370434/chapter-10-flash-cards/
A(n) _____ is a computer-based information system designed to help knowledge workers select one of many alternative solutions to a problem. a. database management system (DBMS) b. geographic information system (GIS) c. expert system (EA) d. decision support system (DSS)
http://www.iaeng.org/publication/WCECS2009/WCECS2009_pp312-316.pdf
The authors’ proposed model for stock price prediction is based on Decision Support System (DSS) model by Turban et al. [10]. AI and DM are included in one of the subsystem which is Knowledge based subsystem. IV. DSS MODEL FOR STOCK INVESTMENT STRATEGY Amend the each component Fig. 1. The Flow of Stock Investment Strategy Decision Support System
https://dl.acm.org/citation.cfm?id=2151339
Generally, stock trading expert systems (STES) called also ''mechanical trading systems'' are based on the technical analysis, i.e., on methods for evaluating securities by analyzing statistics generated by the market activity, such as past prices and volumes (number of transactions during a unit of a timeframe).
https://quizlet.com/198955553/chapter-10-decision-support-and-expert-systems-flash-cards/
A decision support system's module is a database or data warehouse that provides the data for the intelligence phase of decision making. 30. Among the general statistical models, a(n) model is the best-fit straight-line relationship between two variables, such as sales and the money spent on marketing.
http://www.ai-machine-learning.com/artificialintelligencestockmarket.php
Artificial intelligence stock market or machine intelligence, not blockchain or cloud technology, will transform the stock market industry or have the biggest impact on …
https://pdfs.semanticscholar.org/29a7/e1e1386db50bbb22710d63eb820f9c86ae1b.pdf
In [1] Technical indicators and rough-set based system were used to predict on-day-ahead trend of SENSEX. In [2], technical indicators and a backpropagation neural network were used to create a decision support system for exchange traded funds trading. Technical indicators and neural networks were used in [3] to predict the US Dollar
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.384.3600
Essentially in this hybrid technique, fuzzy logic plays the role to formulate the relationship among the Stochastics indicators and stock price changes by using knowledge base. Neural networking is used to tune the formulated knowledge base based on historical data.
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