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題名:建構兩階段多目標之類免疫支援向量廻歸模式於股價預測
書刊名:數據分析
作者:邱志洲蔡易潤呂奇傑 引用關係
作者(外文):Chiu, Chih-chouTsai, Yi-junLu, Chi-jie
出版日期:2015
卷期:10:5
頁次:頁1-30
主題關鍵詞:股價預測人工類免疫系統支援向量迴歸多目標最佳化Stock index predictionArtificial immune systemSupport vector regressionMulti-objective optimization
原始連結:連回原系統網址new window
相關次數:
  • 被引用次數被引用次數:期刊(1) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:1
  • 共同引用共同引用:1
  • 點閱點閱:1
期刊論文
1.Pai, Ping-feng、Lin, Chih-shen、Hong, Wei-chiang、Chen, Chen-tung(20060600)。A Hybrid Support Vector Machine Regression for Exchange Rate Prediction。International Journal of Information and Management Sciences,17(2),19-32。new window  new window
2.Malkiel, B. G.(2005)。Reflections on the Efficient Market Hypothesis: 30 Years Later。The Financial Review,40(1),1-9。  new window
3.Atsalakis, George S.、Valavanis, Kimon P.(2009)。Forecasting stock market short-term trends using a neuro-fuzzy based methodology。Expert Systems with Applications,36(7),10696-10707。  new window
4.Lee, T. S.、Chen, N. J.(2002)。Investigating the Information Content of Non-Cash-Trading Index Futures Using Neural Networks。Expert Systems with Applications,22(3),225-234。  new window
5.Timmermann, A.、Granger, C. W. J.(2004)。Efficient Market Hypothesis and Forecasting。International Journal of Forecasting,20(1),15-27。  new window
6.de Castro, L. N.、Von Zuben, F. J.(2002)。Learning and optimization using the clonal selection principle。IEEE Transactions on Evolutionary Computation,6(3),239-251。  new window
7.Cherkassky, V.、Ma, Y.(2004)。Practical selection of SVM parameters and noise estimation for SVM regression。Neural Networks,17,113-126。  new window
8.Cao, Lijuan、Tay, Francis E. H.(2003)。Support Vector Machine with Adaptive Parameters in Financial Time Series Forecasting。IEEE Transactions on Neural Networks,14(6),1506-1518。  new window
9.Chong, Yih Tng、Chen, Chun-Hsien(2010)。Management and forecast of dynamic customer needs: An artificial immune and neural system approach。Advanced Engineering Informatics,24(1),96-106。  new window
10.Duan, K.、Keerthi, S. S.、Poo, A. N.(2003)。Evaluation of simple performance measures for tuning SVM hyperparameters。Neurocomputing,51,41-59。  new window
11.Hong, W. C.、Pai, P. F.(2006)。Predicting engine reliability by support vector machines。The International Journal of Advanced Manufacturing Technology,28(1/2),154-161。  new window
12.Roh, Tae Hyup(2007)。Forecasting the volatility of stock price index。Expert Systems with Applications,33(4),916-922。  new window
13.Mohandes, M. A.、Halawani, T. O.、Rehman, S.、Hussain, A. A.(2004)。Support vector machines for wind speed prediction。Renewable Energy,29,939-947。  new window
14.Harta, E.、Timmis, J.(2008)。Application areas of AIS: The past, the present and the future。Applied Soft Computing,8,191-201。  new window
15.Myk, E.、Unold, O.(2010)。Mining fuzzy rules using an Artificial Immune System with fuzzy partition learning。Applied Soft Computing,11,1965-1974。  new window
16.Mobinia, M.、Mobinib, Z.、Rabbani, M.(2011)。An Artificial Immune Algorithm for the project scheduling problem under resource constraints。Applied Soft Computing,11,1975-1982。  new window
17.Sakthivel, V. P.、Bhuvaneswari, R.、Subramanian, S.(2010)。Artificial immune system for parameter estimation of induction motor。Expert Systems with Applications,37,6109-6115。  new window
18.Timmis, J.、Hone, A.、Stibor, T.、Clark, E.(2008)。Theoretical advances in artificial immune systems。Theoretical Computer Science,403,11-32。  new window
會議論文
1.Hart, E.、Ross, P.(2002)。Exploiting the analogy between immunology and sparse distributed memories: A system for clustering non-stationary data。The 1st International Conference on Artificial Immune Systems。Canterbury。49-58。  new window
2.Chen, K. Y.、Ho, C. H.(2005)。An improved support vector regression modeling for taiwan stock exchange market weighted index forecasting。Beijing。  new window
3.De Castro, L. N.、Von Zuben, F. J.(2000)。The clonal selection algorithm with engineering applications。GECCO Conference。Las Vagas, Nevada。36-39。  new window
4.Hong, W. C.、Lai, C. Y.、Hung, W. M.、Dong, Y.(2010)。Electric load forecasting by SVR with chaotic ant swarm optimization102-107。  new window
5.Hou, L. K.、Yang, Q. X.(2009)。Study on parameters selection of LSSVR based on grid diamond search method。Baoding。1219-1224。  new window
6.Luo, F.、Wu, J.、Yan, K.(2010)。A novel nonlinear combination model based on support vector machine for stock market prediction。Jinan。5048-5053。  new window
7.Lixing, D.、Jinhu, L.、Xuemei, L.、Lanlan, L.(2010)。Support vector regression and ant colony optimization for HVAC cooling load prediction。2010 International Symposium on Computer Communication Control and Automation。Tainan。537-541。  new window
8.Ju, Y. F.、Wu, S. W.(2010)。Village electrical load prediction by genetic algorithm and SVR。Chengdu。278-281。  new window
9.Zhao, S.、Wang, L.(2010)。Support vector regression based on particle swarm optimization for rainfall forecasting。Anhui。484-487。  new window
研究報告
1.Hsu, C. W.、Chang, C. C.、Lin, C. J.(2010)。A practical guide to support vector classification。National Taiwan University。  new window
圖書論文
1.Drucker, Harris、Burges, Christopher J. C.、Kaufman, Linda、Smola, Alex J.、Vapnik, Vladimir N.(1997)。Support vector regression machines。Advances in Neural Information Processing Systems。Cambridge, Massachusetts:MIT Press。  new window
2.Lee, T. S.、Chen, N. J.、Chiu, C. C.(2003)。Forecasting the opening cash price index using grey forecasting and neural networks: evidence from the SGX-DT MSCI Taiwan Index Futures Contracts。Computational Intelligence in Economics and Finance。Springer。  new window
3.Vapnik, V.、Golowich, S. E.、Smola, A.(1997)。Support vector method for function approximation, regression estimation and signal processing。Advance in Neural information processing system。Cambridge, MA:MIT Press。  new window
 
 
 
 
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