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Predicting stock prices with traditional time series analysis has proven to be difficult. Fuzzy models have recently been used to predict stock market prices because they are capable of extracting useful information from large sets of data without any assumption about a mathematical model. In this paper, three types of fuzzy rule formats to predict daily and weekly stock price indexes were presented. Their premises and consequences were composed of trapezoidal membership functions and novel nonlinear equations, respectively. As the most effective indicators for stock prediction, the information used in traditional candle stick-chart analysis was newly employed as input variables of our fuzzy models. The optimal fuzzy models were identified through an evolutionary process of differential evo-lution (DE). The different types of fuzzy models to predict the daily and weekly open, high, low, and close prices of the Korea Composite Stock Price Index (KOSPI) were built, and their performances were compared.

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권호기사 목록 테이블로 기사명, 저자명, 페이지, 원문, 기사목차 순으로 되어있습니다.
기사명 저자명 페이지 원문 목차
Synchronization of ball and beam systems with neural compensation Xiaoou Li ;Wen Yu pp.491-496

Guaranteed cost control of linear systems with distributed delays :a complete type functionals approach Omar Santos ;Sabine Mondié pp.497-505

New results in disturbance decoupled fault reconstruction in linear uncertain systems using two sliding mode observers in cascade Kok Yew Ng ;Chee Pin Tan ;Zhihong Man ;Rini Akmeliawati pp.506-518

(A)Biologically inspired improvement strategy for particle filter :ant colony optimization assisted particle filter Junpei Zhong ;Yu-fai Fung ;Mingjun Dai pp.519-526

Adaptive tracking and asymptotic rejection of unknown but bounded disturbances in nonlinear MIMO systems Hamid Khaloozadeh ;Mohammad Ali Nekoui ;Farid Shahni pp.527-533

Nonlinear dynamic modeling and control of a small-scale helicopter Baoquan Song ;James K. Mills ;Yunhui Liu ;Caizhi Fan pp.534-543

(A)Practical PID regulator with bounded torques for robot manipulators Victor Santibañez ;Karla Camarillo ;Javier Moreno-Valenzuela ;Ricardo Campa pp.544-555

Low-order robust power system stabilizer for single-machine systems :an LMI approach Seog-Joo Kim ;Soonman Kwon ;Young-Hyun Moon pp.556-563

Cadaver study for spinal fusion surgery using an image-guided surgical robot system Jaeheon Chung ;Sungmin Kim ;Byung-Ju Yi ;Young Soo Kim pp.564-573

Task space control of a welding robot using a fuzzy coordinator Mohammad Mehdi Fateh ;Shahab Shahrabi Farahani ;Arash Khatamianfar pp.574-582

CSMA/C with reservations in wireless communication for distributed robot system Dong Han Kim ;Kuk Won Ko ;Chongkug Park pp.583-596

(A)Method for combining odometry and distance sensor information for effective obstacle avoidance of autonomous mobile robots Dong Jin Seo ;Nak Yong Ko ;Jung Eun Son pp.597-603

Long-term stealth navigation in a security zone where the movement of the invader is monitored Junghee Park ;Jeong S. Choi ;Jimin Kim ;Sang-Hoon Ji ;Beom H. Lee pp.604-614

Correction of radial distortion based on line-fitting Gwang-Yul Song ;Joon-Woong Lee pp.615-621

Self-organization of unicycle swarm robots based on a modified particle swarm framework Dong Hun Kim pp.622-629

Stabilization of linear continuous systems with limited information Yuanlong Li ;Zhibin Yan ;Jian Wang pp.630-635

Robust Η_∞_ control for uncertain nonlinear active magnetic bearing systems via Takagi-Sugeno fuzzy models Dong Hwan Lee ;Jin Bae Park ;Young Hoon Joo ;Kuo Chi Lin ;Chan Ho Ham pp.636-646

Kharitonov's theorem and routh criterion for stability margin of interval systems Yogesh V. Hote ;J. R. P. Gupta ;D. Roy Choudhury pp.647-654

Delay-dependent approach to robust H_∞_ filtering for discrete-time singular systems with multiple time-varying delays and polytopic uncertainties Jong-Hae Kim pp.655-661

Spectral factorization for multiple input delayed discrete-time systems with applications to control Hong-Guo Zhao ;Huan-Shui Zhang ;Peng Cui ;Xiao Lu pp.662-666

Mobile robot localization with gyroscope and constrained Kalman filter Hyun Myung ;Hyoung-Ki Lee ;Kiwan Choi ;Seokwon Bang pp.667-676

Intelligent PSR estimator for feature extraction of a passive sonar target Hyun-Sik Kim ;Doheon Lee pp.677-682

Qualitative model based fault diagnosis using a threshold level Sobhi Baniardalani ;Javad Askari ;Jan Lunze pp.683-694

Analysis of FLC with changing fuzzy variables in frequency domain Kyoung-woong Lee ;Hansoo Choi pp.695-701

Fuzzy models for predicting time series stock price index Heesoo Hwang ;Jinsung Oh pp.702-706

참고문헌 (21건) : 자료제공( 네이버학술정보 )

참고문헌 목록에 대한 테이블로 번호, 참고문헌, 국회도서관 소장유무로 구성되어 있습니다.
번호 참고문헌 국회도서관 소장유무
1 An artificial stock market 네이버 미소장
2 B. M. Louis, Trend Forecasting with Technical Analysis, Marketplace BOOKS, 2000. 미소장
3 S. M. Kendall and K. Ord, Time Series, Oxford, 1997. 미소장
4 Pattern discovery of fuzzy time series for financial prediction 네이버 미소장
5 D. R. Jobman, The Handbook of Technical Analysis, Chicago, Probus Publishing, Illinois, 1995. 미소장
6 K. H. Lee and G. S. Jo, “Expert system for predicting stock market timing using a candlestick chart,” Expert System With Applications, vol. 16, pp. 357- 364, 1999. 미소장
7 T. J. Beckman, “Stock market forecasting using technical analysis,” The World Congress on Expert System Proceedings, pp. 2512-2519, 1991. 미소장
8 K. Nygren, Stock Prediction: A Neural Network Approach, Master Thesis, Royal Institute of Technology, KTH, March, 2004. 미소장
9 Y. Tang, F. Xu, X. Wan, and Y. Q. Zhang, “Webbased fuzzy neural networks for stock prediction,” Computational Intelligence and Applications, pp. 169-174, 2002. 미소장
10 A hybrid genetic-neural architecture for stock indexes forecasting 네이버 미소장
11 A TSK type fuzzy rule based system for stock price prediction 네이버 미소장
12 M. H. Zarandi, E. Neshat, I. B. Turksen, and B. Rezaee, “A type-2 fuzzy model for stock market analysis,” Proc. of Fuzzy System Conf., FUZZIEEE, pp. 1-6, July 2007. 미소장
13 Stock market trading rule discovery using two-layer bias decision tree 네이버 미소장
14 Fan and M. Palaniswami, “Stock selection using support vector machines,” Proceedings IJCNN, vol. 3, pp. 1793-1798, 2001. 미소장
15 M. Noor and R. H. Khokhar, “Fuzzy decision tree for data mining of time series stock market databases,” Critical Assessment of Mocroarray Data Analysis Conference, November 11-12, 2004. 미소장
16 P. Giudici, Applied Data Mining, Statistical Methods for Business and Industry, Wiley, 2003. 미소장
17 A fuzzy-logic-based approach to qualitative modeling 네이버 미소장
18 T. Takagi and M. Sugeno, “Fuzzy identification of systems and its application to modeling and control,” IEEE Trans. Syst. Man. Cybern., vol. 15, pp. 116-132, 1985. 미소장
19 H. S. Hwang, “Automatic design of fuzzy rule base for modeling and control using evolutionary programming,” IEEE Proc-Control Theory Appl., vol. 146, no. 1, pp. 9-16, 1996. 미소장
20 Evolutionary design of fuzzy rule base for nonlinear system modeling and control 네이버 미소장
21 Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces 네이버 미소장

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