:::

詳目顯示

回上一頁
題名:分析能源類股股價影響因子與預測漲跌
書刊名:管理資訊計算
作者:邱登裕謝素真李玫郁蔡松偉
作者(外文):Chiu, Deng-yuHsieh, Su-chenLi, Mei-yuTsai, Sung-wei
出版日期:2022
卷期:11:2
頁次:頁64-73
主題關鍵詞:決策樹模糊分群法支持向量機股價趨勢預測Decision treeFuzzy C-meansSupport vector machineStock price
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(0) 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:0
  • 共同引用共同引用:0
  • 點閱點閱:5
期刊論文
1.Tsai, C.-F.、Lin, Y.-C.、Yen, D. C.、Chen, Y. M.(2011)。Predicting stock returns by classifier ensembles。Applied Soft Computing,11(2),2452-2459。  new window
2.Sun, B.、Guo, H.、Karimi, H. Reza、Ge, Y.、Xiong, S.(2015)。Prediction of stock index futures prices based on fuzzy sets and multivariate fuzzy time series。Neurocomputing,151,1528-1536。  new window
3.Göçken, Mustafa、Özçalıcı, Mehmet、Boru, Aslı、Dosdoğru, Ayşe Tuğba(2016)。Integrating metaheuristics and Artificial Neural Networks for improved stock price prediction。Expert Systems with Applications,44,320-331。  new window
4.Schumaker, Robert P.、Chen, Hsinchun(2009)。Textual analysis of stock market prediction using breaking financial news: the AZFin text system。ACM Transactions on Information Systems,27(2),1-19。  new window
5.Hao, P.-Y.、Kung, C.-F.、Chang, C.-Y.、Ou, J.-B.(2021)。Predicting Stock Price Trends Based on Financial News Articles and Using a Novel Twin Support Vector Machine with Fuzzy Hyperplane。Applied Soft Computing,98。  new window
6.Chatzis, S. P.、Siakoulis, V.、Petropoulos, A.、Stavroulakis, E.、Vlachogiannakis, N.(2018)。Forecasting stock market crisis events using deep and statistical machine learning techniques。Expert Systems with Applications,112,353-371。  new window
7.Alruwaili, M.、Siddiqi, M. H.、Javed, M. A.(2020)。A robust clustering algorithm using spatial fuzzy C-means for brain MR images。Egyptian Informatics Journal,21(1),51-66。  new window
8.Bisoi, R.、Dash, P. K.、Parida, A. K.(2019)。Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis。Applied Soft Computing,74,652-678。  new window
9.Chen, J.-H.、Ong, C. F.、Zheng, L.、Hsu, S.-C.(2017)。Forecasting Spatial Dynamics of the Housing Market Using Support Vector Machine。International Journal of Strategic Property Management,21(3),273-283。  new window
10.Das, S. P.、Achary, N. S.、Padhy, S.(2016)。Novel hybrid SVM-TLBO forecasting model incorporating dimensionality reduction techniques。Applied Intelligence,45(4),1148-1165。  new window
11.Dash, R.、Samal, S.、Dash, R.、Rautray, R.(2019)。An integrated TOPSIS crow search based classifier ensemble: In application to stock index price movement prediction。Applied Soft Computing,85(6)。  new window
12.Duarte, J. J.、Montenegro González, S.、Cruz, J. C. Jr.(2021)。Predicting Stock Price Falls Using News Data: Evidence from the Brazilian Market。Computational Economics,57(1),311-340。  new window
13.Fenghua, W. E. N.、Jihong, X.、Zhifang, H. E.、Xu, G.(2014)。Stock Price Prediction based on SSA and SVM。Stock Price Prediction based on SSA and SVM. Procedia Computer Science,31,625-631。  new window
14.Hossain, M. S.、Baten, M. A.、Mukta, F. B.(2021)。Forecasting Volatility of Selected Banks of Dhaka Stock Exchange (DSE), Bangladesh with GARCH (p, q) Type Models。Journal of Economic Cooperation and Development,42(1),117-142。  new window
15.Illa, P. K.、Parvathala, B.、Sharma, A. K.(2021)。Stock price prediction methodology using random forest algorithm and support vector machine。Materials Today: Proceedings,56(4),1776-1782。  new window
16.Ince, H.(2014)。Short term stock selection with case-based reasoning technique。Applied Soft Computing,22,205-212。  new window
17.Jing, N.、Wu, Z.、Wang, H.(2021)。A hybrid model integrating deep learning with investor sentiment analysis for stock price prediction。Expert Systems with Applications,178。  new window
18.Kwan, Y. K.、Dong, J.(2014)。Stock Price Dynamics of China: What Do the Asset Markets Tell Us About the Chinese Utility Function?。Emerging Markets Finance & Trade,50(S3),77-108。  new window
19.Li, Y.、Bu, H.、Li, J.、Wu, J.(2020)。The role of text-extracted investor sentiment in Chinese stock price prediction with the enhancement of deep learning。International Journal of Forecasting,36(4),1541-1562。  new window
20.Liu, C.-F.、Yeh, C.-Y.、Lee, S.-J.(2012)。Application of type-2 neuro-fuzzy modeling in stock price prediction。Applied Soft Computing,12(4),1348-1358。  new window
21.Long, W.、Lu, Z.、Cui, L.(2019)。Deep learning-based feature engineering for stock price movement prediction。Knowledge-Based Systems,164,163-173。  new window
22.Prasad, A.、Seetharaman, A.(2021)。Importance of Machine Learning in Making Investment Decision in Stock Market。Vikalpa: The Journal for Decision Makers,46(4),209-222。  new window
23.Sadorsky, P.(2021)。A Random Forests Approach to Predicting Clean Energy Stock Prices。Journal of Risk and Financial Management,14(2),1-20。  new window
24.Suppawong, T.、Wettayakorn, P.、Ponpat, P.、Traivijitkhun, S.、Lim, S.、Thanapon, N.、Tipajin, T.(2021)。DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction。Financial Innovation,7(1),7-56。  new window
25.Tripathy, N.(2021)。How Investors Leveraging Gain In Stock Market Investments: A Predictive Analysis。Academy of Marketing Studies Journal,25(5),1-11。  new window
26.Wang, X.、Pardalos, P. M.(2015)。A Survey of Support Vector Machines with Uncertainties。Annals of Data Science,1(3/4),293-309。  new window
27.Xie, C.、Luo, C.、Yu, X.(2010)。Financial distress prediction based on SVM and MDA methods: the case of Chinese listed companies。Quality & Quantity,45(3),671-686。  new window
28.Xu, Q.、Jiang, C.、He, Y.(2015)。An exponentially weighted quantile regression via SVM with application to estimating multiperiod VaR。Statistical Methods & Applications,25(2),285-320。  new window
29.Yu, H.、Chen, R.、Zhang, G.(2014)。A SVM Stock Selection Model within PCA。Procedia Computer Science,31,406-412。  new window
30.Zhang, D.、Lou, S.(2021)。The application research of neural network and BP algorithm in stock price pattern classification and prediction。Future Generation Computer Systems,115,872-879。  new window
31.Zhao, Z.、Zhao, J.、Song, K.、Hussain, A.、Du, Q.、Dong, Y.、Yang, X.(2020)。Joint DBN and Fuzzy C-Means unsupervised deep clustering for lung cancer patient stratification。Engineering Applications of Artificial Intelligence,91。  new window
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
:::
無相關書籍
 
無相關著作
 
QR Code
QRCODE