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A Decision Tree- Rough Set Hybrid System for Stock Market Trend Prediction
TLDR
This work presents the design and performance evaluation of a hybrid decision tree- rough set based stock market trend prediction system for predicting the one-day-ahead trend in the Bombay Stock Exchange (BSE-SENSEX). Expand
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A Stock Market Trend Prediction System Using a Hybrid Decision Tree-Neuro-Fuzzy System
TLDR
An automated decision tree-adaptive neuro-fuzzy hybrid automated stock market trend prediction system is proposed. Expand
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Multilingual speech recognition: a unified approach
TLDR
We use an automatic phone mapping algo-rithm to map phones across languages and reduce the effectivenumber of phones in the multilingual acoustic model to reduce theoverall size of the acoustic model. Expand
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A Methodology for Aiding Investment Decision between Assets in Stock Markets Using Artificial Neural Network
TLDR
This paper outlines a methodology for aiding the decision making process for investment between two financial market assets (eg a risky asset versus a risk-free asset), using neural network architecture. Expand
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Modeling and Predicting Stock Returns using the ARFIMA-FIGARCH A case study on Indian Stock data
Modeling of real world financial time series such as stock returns are very difficult, because of their inherent characteristics. ARIMA and GARCH models are frequently used in such cases. It isExpand
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Stock Market Prediction Using a Hybrid Neuro-fuzzy System
TLDR
An automated decision tree-adaptive neuro-fuzzy hybrid automated stock market prediction system is proposed. Expand
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A GA-artificial neural network hybrid system for financial time series forecasting
TLDR
An adaptive artificial neural network based system to predict the next day’s closing value of a stock market index. Expand
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Predicting stock market trends using hybrid ant-colony-based data mining algorithms: an empirical validation on the Bombay Stock Exchange
TLDR
A Support Vector Machine (SVM)-cAnt-Miner-based system for predicting the next-day's trend in stock markets is proposed. Expand
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An intelligent recommender system for stock trading
TLDR
In this study, a GA optimized technical indicator decision tree-SVM based intelligent recommender system is proposed, which can learn patterns from the stock price movements and then recommend appropriate one-day-ahead trading strategy. Expand
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