PEDOMODELS FITTING WITH FUZZY LEAST SQUARES REGRESSION

نویسندگان

  • JAHANGARD MOHAMMADI SOIL SCIENCE DEPARTMENT, COLLEGE OF AGRICULTURE, SHAHREKORD UNIVERSITY, SHAHREKORD, IRAN.
  • SYED MAHMOUD TAHERI SCHOOL OF MATHEMATICAL SCIENCES, ISFAHAN, UNIVERSITY OF TECHNOLOGY, ISFAHAN 84156, IRAN.
چکیده مقاله:

Pedomodels have become a popular topic in soil science and environmentalresearch. They are predictive functions of certain soil properties based on other easily orcheaply measured properties. The common method for fitting pedomodels is to use classicalregression analysis, based on the assumptions of data crispness and deterministic relationsamong variables. In modeling natural systems such as soil system, in which the aboveassumptions are not held true, prediction is influential and we must therefore attempt toanalyze the behavior and structure of such systems more realistically. In this paper weconsider fuzzy least squares regression as a means of fitting pedomodels. The theoretical andpractical considerations are illustrated by developing some examples of real pedomodels.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

pedomodels fitting with fuzzy least squares regression

pedomodels have become a popular topic in soil science and environmentalresearch. they are predictive functions of certain soil properties based on other easily orcheaply measured properties. the common method for fitting pedomodels is to use classicalregression analysis, based on the assumptions of data crispness and deterministic relationsamong variables. in modeling natural systems such as s...

متن کامل

Multidimensional Least-squares Fitting of Fuzzy Models

We describe a new method for the fitting of differentiable fuzzy model functions to crisp data. The model functions can be either scalar or multidimensional and need not be linear. The data are n-component vectors. An efficient algorithm is achieved by restricting the fuzzy model functions to sets which depend on a fuzzy parameter vector and assuming that the vector has a conical membership fun...

متن کامل

Fuzzy regression and least squares regression: the relationship between two different fitting criteria

Nell’analisi della dipendenza di una o più variabili quantitative da un set di predittori il metodo dei Minimi Quadrati gioca un ruolo fondamentale. La Teoria delle Probabilità e l’Inferenza classica consentono di valutare l’incertezza delle stime ottenute, mediante la costruzione di opportuni intervalli di confidenza, imponendo al modello ipotesi restrittive spesso difficili da soddisfare. Ino...

متن کامل

Least squares fitting

Technical Note: Review of methods for linear least-squares fitting of data and application to atmospheric chemistry problems C. A. Cantrell National Center for Atmospheric Research, Atmospheric Chemistry Division, 1850 Table Mesa Drive, Boulder, CO 80305, USA Received: 13 February 2008 – Accepted: 21 February 2008 – Published: 1 April 2008 Correspondence to: C. A. Cantrell ([email protected]) P...

متن کامل

Tutorial: Least-Squares Fitting

Least-squares fitting, first developed by Carl Friedrich Gauss, is arguably the most widely used technique in statistical data analysis. It provides a method through which the parameters of a model can be optimised in order to obtain the best fit to a data set through the minimisation of the squared differences between the model and the data. This tutorial document describes the closely associa...

متن کامل

Fuzzy least-squares algorithms for interactive fuzzy linear regression models

Fuzzy regression analysis can be thought of as a fuzzy variation of classical regression analysis. It has been widely studied and applied in diverse areas. In general, the analysis of fuzzy regression models can be roughly divided into two categories. The 0rst is based on Tanaka’s linear-programming approach. The second category is based on the fuzzy least-squares approach. In this paper, new t...

متن کامل

منابع من

با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ذخیره در منابع من قبلا به منابع من ذحیره شده

{@ msg_add @}


عنوان ژورنال

دوره 1  شماره 2

صفحات  45- 61

تاریخ انتشار 2004-10-22

با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.

میزبانی شده توسط پلتفرم ابری doprax.com

copyright © 2015-2023