MARC状态：审校 文献类型：西文图书 浏览次数：60
- 题名/责任者:
- Conventional and fuzzy regression : theory and engineering applications / Vlassios Hrissanthou and Mike Spiliotis, editors.
- 出版发行项:
- New York : Nova Science Publishers, [2018]
- ISBN:
- 9781536137989
- 载体形态项:
- x,332 pages : illustrations ; 23 cm.
- 附加个人名称:
- Hrissanthou, Vlassios, editor.
- 附加个人名称:
- Spiliotis, Mike, editor.
- 论题主题:
- Engineering mathematics.
- 论题主题:
- Fuzzy statistics.
- 论题主题:
- Regression analysis.
- 中图法分类号:
- TB11
- 书目附注:
- Includes bibliographical references and index.
- 摘要附注:
- "Aims to present both conventional and fuzzy regression analyses from theoretical aspects followed by application examples. The present book contains chapters originating from different scientific fields. The first deals with both crisp (conventional) linear or nonlinear regression and fuzzy linear or nonlinear regression. The application example refers to the relationship between sediment transport rates on the one hand and stream discharge and rainfall intensity on the other hand. Second chapter refers to the crisp linear or nonlinear regression of six heavy metals between different soft tissues and shells of Telescopium telescopium and its habitat surface sediments. Third describes the crisp linear, multiple linear, nonlinear and Gaussian process regressions. The fourth is confronted with a classic regression model, named Geographically Weighted Regression (GWR), which constitutes a spatial statistics method. The fifth chapter regards fuzzy linear regression based on symmetric triangular fuzzy numbers. The sixth chapter treats fuzzy linear regression based on trapezoidal membership functions. The main application of this chapter concerns the dependence of rainfall records between neighboring rainfall stations for a small sample of data. The next chapter refers to the multivariable crisp and fuzzy linear regression. The eighth chapter deals with the fuzzy linear regression, with crisp input data and fuzzy output data. All the chapters offer a proper foundation of either widely used or new techniques upon regression. Among the new techniques, several innovated fuzzy regression based methodologies are developed for real problems, and useful conclusions are drawn"--
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