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題名 模糊中位數及其在財金與經濟分析之應用
Fuzzy Median and Its Applications in Economics and Finance
作者 何曉緯
貢獻者 吳柏林<br>鄭宇庭
何曉緯
關鍵詞 二元邏輯
隸屬度函數
模糊統計
模糊中位數
binary logic
membership functions
fuzzy statistics
fuzzy median
日期 2002
上傳時間 9-五月-2016 16:23:38 (UTC+8)
摘要 　　在知識經濟之社會，多元思維逐漸取代傳統二元邏輯的思考與分析方法。過去使用單一數值的樣本來計算中位數的方法，已漸不符現今複雜多變的智慧科技時代之需求。尤其是在具有多變性、不確定性、與訊息不完整性的財金與經濟環境下，過分強調對於數值之運算及數學假設的前提，反而更容易造成與現實環境及條件的背離、甚至是脫節。故在進行財金與經濟方面問題的研究時，利用隸屬度函數與模糊統計的分析將會是一種較為進步的測度方法。本文在此提出模糊中位數的分析理論，並將其應用於財務金融的分析測度上，期望能對複雜的財金經濟現狀提供一套更有效且精確合理的分析方法。
　　In the society of economic knowledge, Multi-valued logic goes to replace binary logic gradually. In the traditional way, we usually ask the task-taker to response the answer according to the thinking of binary logic. But such kind of response is improper since the human thinking is fuzzy and uncertain. So it should be an improved measurement using membership functions and fuzzy statistics.
     　　In this paper, we will propose the definition of fuzzy median, and present some of its application. According to the above theoretical contents, we give some examples, which is used frequently in financial and economic assessment. From the explanation and discussion of fuzzy median in these examples, we can recognize that fuzzy statistics is more meaningful and proper for research of finance and economics. At last, based upon the findings of this study, certain recommendations for further research are suggested.
參考文獻 吳柏林，廖述健 (2001)。模糊統計分析及其在社會調查之應用。
     阮亨中，吳柏林 (2000)。模糊數學與統計應用。台北：俊傑書局。
     吳柏林，許毓云 (1999)。模糊統計分析在臺灣地區失業率應用。中國統計學報。37(1)，37-52。
     吳柏林，曾能芳 (1998)。模糊回歸參數估計及在景氣對策信號之分析應用。中國統計學報。36(4)，399-420。
     李雪雯 (1998)。共同基金入門。台北：原富文化。
     陳忠慶，林奇芬 (1998)。國內共同基金選購指南。台北：原富文化。
     吳柏林，楊文山 (1997)。模糊統計在社會調查分析的應用。社會科學計量方法發展與應用。楊文山主編：中央研究院中山人文社會科學研究所。289-316。
     王文俊 (1997)。認識Fuzzy。台北：全華書局。
     黃仁德，吳柏林 (1995)。臺灣短期貨幣需求函數穩定性的檢定。模糊時間數列方法之應用。臺灣經濟學會年會論文集。169-190。
     藎壚 (1991)。實用模糊數學。台北：亞東書局。
     Clymer, J., Corey, P., and Gardner, J. (1992). Discrete event fuzzy airport control. IEEE Trans. on Systems, Man, and Cybernetics, Vol.22, No.2, 343-351.
     Cutsem, B. V. and Gath, I. (1993). Detection of outliers and robust estimation using fuzzy clustering. Computational Statistics and Data Analysis, 15, 47-61.
     Dubois, D. and Prade, H. (1991). Fuzzy sets in approximate reasoning, Part 1: Inference with possibility distributions, Fuzzy Sets and Systems, 40, 143-202.
     Guariso, G. , Rizzoli, A. and Werthner, H. (1992). Identification of model structure via qualitive simulation. IEEE Trans. on Systems, Man, and Cybernetics, Vol.22, No.5, 1075-1086.
     Hathaway, R. J. and Bezdek, J. C. (1993). Switching regression models and fuzzy clustering. IEEE Transactions of Fuzzy Systems, 1,195-204.
     Kosko, B. (1993). Fuzzy thinking : the new science of fuzzy logic. Hyperion, New York.
     Lowen, R. (1990). A fuzzy language interpolation theorem. Fuzzy Sets and Systems, 34, 33-38.
     Romer, C., Kandel, A., and Backer, E. (1995). Fuzzy partitions of the sample space and fuzzy parameter hypotheses. IEEE Trans. on Systems, Man, and Cybernetics, Vol.25, No.9, 1314-1321.
     Ruspini, E. (1991). Approximate Reasoning: past, present, future. Information Sciences, 57, 297-317.
     Tseng, T. and Klein, C. (1992). A new Algorithm for fuzzy multicriteria decision making. International Journal of Approximate Reasoning, 6, 45-66.
     Tseng, F., Tzeng, G., Yu, H. and Yuan, B. (2001). Fuzzy ARIMA model for forecasting the foreign exchange market. Fuzzy Sets and Systems, 118, 9-19.
     Wu, B. and Chen, M. (1999). Use of fuzzy statistical technique in change periods detection of nonlinear time series. Applied Mathematics and Computation, 99, 241-254.
     Wu, B. and Hung, S. (1999). A fuzzy identification procedure for nonlinear time series with example on ARCH and bilinear models. Fuzzy Sets and Systems, 108, 275-287.
     Wu, B. and Sun, C. (1996). Fuzzy statistics and computation on the lexical semantics. Language, Information and Computation (PACLIC 11), 337-346. Seoul, Korea.
     Yoshinari, Y., Pedrycz, W. and Hirota, K. (1993). Construction of fuzzy models through clustering techniques. Fuzzy Sets and Systems, 54, 157-165.
     Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8, 338-353.
     Zimmermann, H. J. (1991). Fuzzy Set Theory and Its Applications. Boston: Kluwer Academic.
描述 碩士
國立政治大學
統計學系
88354006
資料來源 http://thesis.lib.nccu.edu.tw/record/#A2010000359
資料類型 thesis
dc.contributor.advisor 吳柏林<br>鄭宇庭zh_TW
dc.contributor.author (作者) 何曉緯zh_TW
dc.creator (作者) 何曉緯zh_TW
dc.date (日期) 2002en_US
dc.date.accessioned 9-五月-2016 16:23:38 (UTC+8)-
dc.date.available 9-五月-2016 16:23:38 (UTC+8)-
dc.date.issued (上傳時間) 9-五月-2016 16:23:38 (UTC+8)-
dc.identifier (其他 識別碼) A2010000359en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/95490-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計學系zh_TW
dc.description (描述) 88354006zh_TW
dc.description.abstract (摘要) 　　在知識經濟之社會，多元思維逐漸取代傳統二元邏輯的思考與分析方法。過去使用單一數值的樣本來計算中位數的方法，已漸不符現今複雜多變的智慧科技時代之需求。尤其是在具有多變性、不確定性、與訊息不完整性的財金與經濟環境下，過分強調對於數值之運算及數學假設的前提，反而更容易造成與現實環境及條件的背離、甚至是脫節。故在進行財金與經濟方面問題的研究時，利用隸屬度函數與模糊統計的分析將會是一種較為進步的測度方法。本文在此提出模糊中位數的分析理論，並將其應用於財務金融的分析測度上，期望能對複雜的財金經濟現狀提供一套更有效且精確合理的分析方法。zh_TW
dc.description.abstract (摘要) 　　In the society of economic knowledge, Multi-valued logic goes to replace binary logic gradually. In the traditional way, we usually ask the task-taker to response the answer according to the thinking of binary logic. But such kind of response is improper since the human thinking is fuzzy and uncertain. So it should be an improved measurement using membership functions and fuzzy statistics.
     　　In this paper, we will propose the definition of fuzzy median, and present some of its application. According to the above theoretical contents, we give some examples, which is used frequently in financial and economic assessment. From the explanation and discussion of fuzzy median in these examples, we can recognize that fuzzy statistics is more meaningful and proper for research of finance and economics. At last, based upon the findings of this study, certain recommendations for further research are suggested.		en_US
dc.description.tableofcontents 目錄-----1
     摘要-----2
     Abstract-----2
     1. 前言-----3
     2. 人類思維測度-----5
     　　2.1 人類思維的模糊性-----5
     　　2.2 隸屬度函數-----5
     　　2.3 模糊數-----9
     3. 模糊中位數的引進與應用-----10
     　　3.1 模糊中位數-----10
     　　3.2 模糊風險-----20
     　　3.3 有關模糊中位數的一些性質-----22
     4. 模糊中位數應用於股票型基金持股內容之探討-----24
     　　4.1 資料分析-----25
     　　4.2 股價之模糊中位數-----26
     　　4.3 成交股數之模糊中位數-----28
     　　4.4 取出結果分析-----31
     5. 結論-----35
     參考文獻-----36		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#A2010000359en_US
dc.subject (關鍵詞) 二元邏輯zh_TW
dc.subject (關鍵詞) 隸屬度函數zh_TW
dc.subject (關鍵詞) 模糊統計zh_TW
dc.subject (關鍵詞) 模糊中位數zh_TW
dc.subject (關鍵詞) binary logicen_US
dc.subject (關鍵詞) membership functionsen_US
dc.subject (關鍵詞) fuzzy statisticsen_US
dc.subject (關鍵詞) fuzzy medianen_US
dc.title (題名) 模糊中位數及其在財金與經濟分析之應用zh_TW
dc.title (題名) Fuzzy Median and Its Applications in Economics and Financeen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 吳柏林，廖述健 (2001)。模糊統計分析及其在社會調查之應用。
     阮亨中，吳柏林 (2000)。模糊數學與統計應用。台北：俊傑書局。
     吳柏林，許毓云 (1999)。模糊統計分析在臺灣地區失業率應用。中國統計學報。37(1)，37-52。
     吳柏林，曾能芳 (1998)。模糊回歸參數估計及在景氣對策信號之分析應用。中國統計學報。36(4)，399-420。
     李雪雯 (1998)。共同基金入門。台北：原富文化。
     陳忠慶，林奇芬 (1998)。國內共同基金選購指南。台北：原富文化。
     吳柏林，楊文山 (1997)。模糊統計在社會調查分析的應用。社會科學計量方法發展與應用。楊文山主編：中央研究院中山人文社會科學研究所。289-316。
     王文俊 (1997)。認識Fuzzy。台北：全華書局。
     黃仁德，吳柏林 (1995)。臺灣短期貨幣需求函數穩定性的檢定。模糊時間數列方法之應用。臺灣經濟學會年會論文集。169-190。
     藎壚 (1991)。實用模糊數學。台北：亞東書局。
     Clymer, J., Corey, P., and Gardner, J. (1992). Discrete event fuzzy airport control. IEEE Trans. on Systems, Man, and Cybernetics, Vol.22, No.2, 343-351.
     Cutsem, B. V. and Gath, I. (1993). Detection of outliers and robust estimation using fuzzy clustering. Computational Statistics and Data Analysis, 15, 47-61.
     Dubois, D. and Prade, H. (1991). Fuzzy sets in approximate reasoning, Part 1: Inference with possibility distributions, Fuzzy Sets and Systems, 40, 143-202.
     Guariso, G. , Rizzoli, A. and Werthner, H. (1992). Identification of model structure via qualitive simulation. IEEE Trans. on Systems, Man, and Cybernetics, Vol.22, No.5, 1075-1086.
     Hathaway, R. J. and Bezdek, J. C. (1993). Switching regression models and fuzzy clustering. IEEE Transactions of Fuzzy Systems, 1,195-204.
     Kosko, B. (1993). Fuzzy thinking : the new science of fuzzy logic. Hyperion, New York.
     Lowen, R. (1990). A fuzzy language interpolation theorem. Fuzzy Sets and Systems, 34, 33-38.
     Romer, C., Kandel, A., and Backer, E. (1995). Fuzzy partitions of the sample space and fuzzy parameter hypotheses. IEEE Trans. on Systems, Man, and Cybernetics, Vol.25, No.9, 1314-1321.
     Ruspini, E. (1991). Approximate Reasoning: past, present, future. Information Sciences, 57, 297-317.
     Tseng, T. and Klein, C. (1992). A new Algorithm for fuzzy multicriteria decision making. International Journal of Approximate Reasoning, 6, 45-66.
     Tseng, F., Tzeng, G., Yu, H. and Yuan, B. (2001). Fuzzy ARIMA model for forecasting the foreign exchange market. Fuzzy Sets and Systems, 118, 9-19.
     Wu, B. and Chen, M. (1999). Use of fuzzy statistical technique in change periods detection of nonlinear time series. Applied Mathematics and Computation, 99, 241-254.
     Wu, B. and Hung, S. (1999). A fuzzy identification procedure for nonlinear time series with example on ARCH and bilinear models. Fuzzy Sets and Systems, 108, 275-287.
     Wu, B. and Sun, C. (1996). Fuzzy statistics and computation on the lexical semantics. Language, Information and Computation (PACLIC 11), 337-346. Seoul, Korea.
     Yoshinari, Y., Pedrycz, W. and Hirota, K. (1993). Construction of fuzzy models through clustering techniques. Fuzzy Sets and Systems, 54, 157-165.
     Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8, 338-353.
     Zimmermann, H. J. (1991). Fuzzy Set Theory and Its Applications. Boston: Kluwer Academic.		zh_TW