✦ LIBER ✦

Inference with a single fuzzy conditional proposition

✍ Scribed by Dimiter Driankov

Publisher: Elsevier Science
Year: 1987
Tongue: English
Weight: 696 KB
Volume: 24
Category: Article
ISSN: 0165-0114
DOI: 10.1016/0165-0114(87)90113-8

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

A new kind of fuzzy regression modeling

A new kind of fuzzy regression modeling and its combination with fuzzy inference

✍ Rajan Alex 📂 Article 📅 2005 🏛 Springer 🌐 English ⚖ 81 KB

Water bath temperature control with a ne

Water bath temperature control with a neural fuzzy inference network

✍ Chin-Teng Lin; Chia-Feng Juang; Chung-Ping Li 📂 Article 📅 2000 🏛 Elsevier Science 🌐 English ⚖ 355 KB

Human posture estimation method from a s

Human posture estimation method from a single image using genetic algorithm and fuzzy inference

✍ Hiroshi Kitajima; Masafumi Hagiwara 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 474 KB 👁 1 views

In this paper, we propose a method for estimating the observation direction of a person by applying fuzzy inference to the features obtained when a genetic algorithm is used to recognizee human posture from a natural image. Posture recognition uses the constraints obtained by representing the human

Regularizing the problem of monitoring t

Regularizing the problem of monitoring the technical state of complex technical objects using program complexes for fuzzy conditional inference systems

✍ S. A. Galaev; A. Yu. Potyupkin 📂 Article 📅 2011 🏛 Springer US 🌐 English ⚖ 382 KB

A branch-and-bound algorithm with fuzzy

A branch-and-bound algorithm with fuzzy inference for a permutation flowshop scheduling problem

✍ Jinliang Cheng; Hiroshi Kise; Hironori Matsumoto 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 697 KB

This paper considers an m-machine permutation flowshop scheduling problem of minimizing the makespan. This classical scheduling problem is still important in modem manufacturing systems, and is well known to be intractable (i.e., NP-hard). In fact branch-and-bound algorithms developed so far for thi

TWNFI — a transductive neuro-fuzzy infer

TWNFI — a transductive neuro-fuzzy inference system with weighted data normalization for personalized modeling

✍ Qun Song; Nikola Kasabov 📂 Article 📅 2006 🏛 Elsevier Science 🌐 English ⚖ 504 KB

This paper introduces a novel transductive neuro-fuzzy inference model with weighted data normalization (TWNFI). In transductive systems a local model is developed for every new input vector, based on a certain number of data that are selected from the training data set and the closest to this vecto