NDLI: The prediction system for data analysis of stock market by using Genetic Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Ching-Te Wang Yung-Yu Lin
Copyright Year	2015
Description	Author affiliation: Dept. of Inf. Manage., Nat. Chin-Yi Univ. of Technol., Taichung, Taiwan (Ching-Te Wang; Yung-Yu Lin)
Abstract	Data analyses have been growing importance on the stock market in the recent years. In order to get the profit of the investing, many investors need to know how to analyze the important data from the stock market. In a large amount of general literature on stock predict, it only a few specific guidance appear on the future prediction. Therefore, how to predict the stocks from the retrieval data, it becomes an important and considerable problem on market predict. In this paper, we will use the Web robot to capture data from the stock market. The system will explore and analyze the information to predict stock prices in the seesaw process. Using a group of cement, medical industries as the examples, this paper will discuss the topics of Web robot, Genetic Algorithm and Support Vector Machine, which can provide a framework for data analysis and predict the stock market. Furthermore, we will analyze the efficiency of our method and show the better performance for the efficiency and accuracy.
Starting Page	1721
Ending Page	1725
File Size	325996
Page Count	5
File Format	PDF
e-ISBN	9781467376822
DOI	10.1109/FSKD.2015.7382206
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Stock predict Sociology Genetic algorithm SVM Statistics Stock markets Robots Biological cells Web robot Genetic algorithms
Content Type	Text
Resource Type	Article

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