標題: A general piecewise necessity regression analysis based on linear programming
作者: Yu, JR
Tzeng, GH
Li, HL
運輸與物流管理系 註:原交通所+運管所
資訊管理與財務金融系 註:原資管所+財金所
Department of Transportation and Logistics Management
Department of Information Management and Finance
關鍵字: piecewise regression;necessity area;fuzzy linear regression
公開日期: 1-八月-1999
摘要: In possibilistic regression analysis proposed by Tanaka and Ishibuchi (1992), linear programming (LP) formulation of necessity analysis has no feasible solution under the enormous variation of the given data. This work proposes a general piecewise necessity regression analysis based on LP rather than a non-linear interval model that they recommended to obtain the necessity area of the given data. In addition to maintaining a linear property, the proposed method prevents the necessity analysis from having no feasible solution. The problematic univariate example and a multivariate example with respect to different number of change-points are demonstrated by the general piecewise necessity regression. The proposed method characteristic is that, according to data distribution, practitioners can specify the number and the positions of change-points. The proposed method maintains the linear interval model and the order of necessity regression function does not need to be determined. (C) 1999 Elsevier Science B.V. All rights reserved.
URI: http://hdl.handle.net/11536/31186
ISSN: 0165-0114
期刊: FUZZY SETS AND SYSTEMS
Volume: 105
Issue: 3
起始頁: 429
結束頁: 436
顯示於類別:期刊論文


文件中的檔案:

  1. 000080634100011.pdf