MỘT SỐ ỨNG DỤNG LÝ THUYẾT TẬP THÔ TRONG KINH TẾ VÀ TÀI CHÍNH
Abstract
Abstract: Rough set theory provides a useful mathematical foundation for developing automated computational systems that can help understand and make use of imperfect knowledge. Recently, Rough set theory and its extensions have been widely applied to many problems, including decision analysis, data mining, intelligent control and pattern recognition, economic and financial problems: risk management, economic and financial forecasting, evaluating marketing performance, decision support... This paper presents an outline of the basic concepts of rough sets and their major extensions. It also shows the diversity of successful applications these theories in Economy and Finance.Tóm tắt: Lý thuyết tập thô cung cấp một nền tảng toán học hữu ích cho việc phát triển hệ thống tính toán tự động, khai phá và phát hiện tri thức của các hệ thống không đầy đủ. Trong thời gian gần đây, lý thuyết tập thô đã được ứng dụng rộng rãi giải quyết nhiều bài toán: phân tích ra quyết định, khai thác dữ liệu, điều khiển thông minh và nhận dạng mẫu, các bài toán kinh tế và tài chính như: quản lý rủi ro, dự báo thị trường tài chính, đánh giá năng lực hoạt động các mạng lưới tiếp thị sản phẩm, hỗ trợ ra quyết định…. Bài viết này trình bày các khái niệm cơ bản của tập thô cổ điển và mở rộng, sự ứng dụng hữu hiệu lý thuyết tập thô trong lĩnh vực kinh tế và tài chính.References
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[2] Binoy.B.Nair, V.P Mohandas, N. R. Sakthivel, “A Decision Tree- Rough Set Hybrid System for Stock Market Trend Prediction”, International Journal of Computer Applications (0975 – 8887), Volume 6– No.9, September 2010.
[3] Eylem Koç, “The Use of Rough Set Theory in Determining the Preferences of the Customers of an Insurance Agency”, European Journal of Business and Management, ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online), Vol.6, No.22, 2014.
[4] Francis E.H. Tay, Lixiang Shen, “Economic and financial prediction using rough sets model”, European Journal of Operational Research, 141, pp 641-659, 2002.
[5] Hameed Al-Qaheri, Aboul Ella Hassanien and Ajith Abraham, “Discovering Stock Price Prediction Rules Using Rough Sets”, http://www.academia.edu/2429166/
[6] HuaJiang, Junhu Ruan, “Applying Rough Set Theory to Evaluate Network Marketing Performance of China’s Agricultural Products”, Journal of Computers, Vol.5 No.8, August 2010.
[7] Mariusz Podsiadlo and Henryk Rubinski, “Rough Sets in Economy and Finance”, Transaction on Rough Sets XVII, LNCS 8375, pp. 109-173, 2014, Springer-Verlag, Berlin Heidelberg 2014.
[8] Naglaa Ragaa Saeid Hassan, “ Forecasting the Egyptian’s Market Trend Using Rough Set”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 1, January 2014, Available online at: www.ijarcsse.com.
[9] Qiang Shen, Richard Jensen, “ Rough sets, Their Extensions and Applications”, International Journal of Automation and Computing, pp 217-228, July, 2007.
[10] Saori Kawasaki, Ngoc Binh and Tu Bao Ho, (2000), “Hierachical Document Clustering Based on Tolerance Rough Set Model”, PKDD 2000, LNAI 1910, pp 458-463, Springer-Verlag, 2010.
[11] Shen Lixiang, “Data mining techniques based on rough set theory”,” Ph.D. thesis, National University of Singapore, 2001.
[12] Shweta Tiwari & Rekha Pandit, “Decision Tree-Rough Set Based System with HHMM For Predicting the Stock Market Trends”, International Conference on Computer Science and Information Technology (CSIT-2012), May 19th, 2012.
[13] Shweta Tiwari, Rekha Pandit, Vineet Richhariya, “Predicting future trends in stock market by decision tree rough-set based hybrid system with HHMM”, International Journal of Electronics and Computer Science Engineering, Available Online at www.ijecse.org.
[14] W.Ziarko, “Variable Precision Rough Set Model”, Journal of Computer and System Sciences, vol. 46, no. 1, pp. 39-59, 1993.
[15] William Zhu, Fei-Yue Wang, “Relationships among Three Type of Covering Rough Sets”, IEEE GrC, Atlanda, USA, pp:43-48, 2006.
[16] William Zhu, Properties of the Second Type of Covering-Based Rough Sets, Proceedings of the 2006 IEEE/ACM International Conference on WI-IAT 2006 Workshops.
[17] William Zhu, Fei-Yue Wang, “Reduction and axiomization of covering generalized rough sets”, Information Sciences, vol 152 , pp:217-230, 2003
[18] Z.Pawlak, “Rough sets, Theoretical Aspects of Reasoning about Data”, Kluwer Academic Publishers, London, 1991.
[2] Binoy.B.Nair, V.P Mohandas, N. R. Sakthivel, “A Decision Tree- Rough Set Hybrid System for Stock Market Trend Prediction”, International Journal of Computer Applications (0975 – 8887), Volume 6– No.9, September 2010.
[3] Eylem Koç, “The Use of Rough Set Theory in Determining the Preferences of the Customers of an Insurance Agency”, European Journal of Business and Management, ISSN 2222-1905 (Paper) ISSN 2222-2839 (Online), Vol.6, No.22, 2014.
[4] Francis E.H. Tay, Lixiang Shen, “Economic and financial prediction using rough sets model”, European Journal of Operational Research, 141, pp 641-659, 2002.
[5] Hameed Al-Qaheri, Aboul Ella Hassanien and Ajith Abraham, “Discovering Stock Price Prediction Rules Using Rough Sets”, http://www.academia.edu/2429166/
[6] HuaJiang, Junhu Ruan, “Applying Rough Set Theory to Evaluate Network Marketing Performance of China’s Agricultural Products”, Journal of Computers, Vol.5 No.8, August 2010.
[7] Mariusz Podsiadlo and Henryk Rubinski, “Rough Sets in Economy and Finance”, Transaction on Rough Sets XVII, LNCS 8375, pp. 109-173, 2014, Springer-Verlag, Berlin Heidelberg 2014.
[8] Naglaa Ragaa Saeid Hassan, “ Forecasting the Egyptian’s Market Trend Using Rough Set”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 1, January 2014, Available online at: www.ijarcsse.com.
[9] Qiang Shen, Richard Jensen, “ Rough sets, Their Extensions and Applications”, International Journal of Automation and Computing, pp 217-228, July, 2007.
[10] Saori Kawasaki, Ngoc Binh and Tu Bao Ho, (2000), “Hierachical Document Clustering Based on Tolerance Rough Set Model”, PKDD 2000, LNAI 1910, pp 458-463, Springer-Verlag, 2010.
[11] Shen Lixiang, “Data mining techniques based on rough set theory”,” Ph.D. thesis, National University of Singapore, 2001.
[12] Shweta Tiwari & Rekha Pandit, “Decision Tree-Rough Set Based System with HHMM For Predicting the Stock Market Trends”, International Conference on Computer Science and Information Technology (CSIT-2012), May 19th, 2012.
[13] Shweta Tiwari, Rekha Pandit, Vineet Richhariya, “Predicting future trends in stock market by decision tree rough-set based hybrid system with HHMM”, International Journal of Electronics and Computer Science Engineering, Available Online at www.ijecse.org.
[14] W.Ziarko, “Variable Precision Rough Set Model”, Journal of Computer and System Sciences, vol. 46, no. 1, pp. 39-59, 1993.
[15] William Zhu, Fei-Yue Wang, “Relationships among Three Type of Covering Rough Sets”, IEEE GrC, Atlanda, USA, pp:43-48, 2006.
[16] William Zhu, Properties of the Second Type of Covering-Based Rough Sets, Proceedings of the 2006 IEEE/ACM International Conference on WI-IAT 2006 Workshops.
[17] William Zhu, Fei-Yue Wang, “Reduction and axiomization of covering generalized rough sets”, Information Sciences, vol 152 , pp:217-230, 2003
[18] Z.Pawlak, “Rough sets, Theoretical Aspects of Reasoning about Data”, Kluwer Academic Publishers, London, 1991.
Published
2014-12-15
How to Cite
THUẦN, Nguyễn Đức.
MỘT SỐ ỨNG DỤNG LÝ THUYẾT TẬP THÔ TRONG KINH TẾ VÀ TÀI CHÍNH.
JBIS, [S.l.], dec. 2014.
Available at: <http://jbis.ueh.edu.vn/index.php/TSTHQL/article/view/36>. Date accessed: 23 apr. 2024.
Issue
Section
Bài viết
Keywords
Tập thô; Kinh tế; Tài chính; Quản lý rủi ro; Dự báo; Đánh giá năng lực thị trường
