Statistical-Like Validation of Fuzzy Logic Models Using Distributional Fitting

Armin Shmilovici; Haim Shore; Oded Maimon

Statistical-Like Validation of Fuzzy Logic Models Using Distributional Fitting

Armin Shmilovici, Haim Shore, Oded Maimon

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

A statistical-like validation procedure is developed for fuzzy logic models. The procedure is based on approximating the unknown probability distribution of the model's residual errors, and the similarity measures of the errors, using a new distributional fitting procedure. The fuzzy logic models are validated using critical ratios generated from the fitted distribution.

Original language	English
Title of host publication	Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU'96)
Pages	629-634
Volume	Proceedings
State	Published - 4 Jul 1996

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@inproceedings{2ae416a64f1242e7a01b5722067ab66c,

title = "Statistical-Like Validation of Fuzzy Logic Models Using Distributional Fitting",

abstract = "A statistical-like validation procedure is developed for fuzzy logic models. The procedure is based on approximating the unknown probability distribution of the model's residual errors, and the similarity measures of the errors, using a new distributional fitting procedure. The fuzzy logic models are validated using critical ratios generated from the fitted distribution.",

author = "Armin Shmilovici and Haim Shore and Oded Maimon",

year = "1996",

month = jul,

day = "4",

language = "English",

volume = "Proceedings",

pages = "629--634",

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T1 - Statistical-Like Validation of Fuzzy Logic Models Using Distributional Fitting

AU - Shmilovici, Armin

AU - Shore, Haim

AU - Maimon, Oded

PY - 1996/7/4

Y1 - 1996/7/4

N2 - A statistical-like validation procedure is developed for fuzzy logic models. The procedure is based on approximating the unknown probability distribution of the model's residual errors, and the similarity measures of the errors, using a new distributional fitting procedure. The fuzzy logic models are validated using critical ratios generated from the fitted distribution.

AB - A statistical-like validation procedure is developed for fuzzy logic models. The procedure is based on approximating the unknown probability distribution of the model's residual errors, and the similarity measures of the errors, using a new distributional fitting procedure. The fuzzy logic models are validated using critical ratios generated from the fitted distribution.

M3 - Conference contribution

VL - Proceedings

SP - 629

EP - 634

BT - Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU'96)

ER -

Statistical-Like Validation of Fuzzy Logic Models Using Distributional Fitting

Abstract

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