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» The importance of learning in fuzzy systems
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CIMCA
2005
IEEE
14 years 2 months ago
NEFCOP: A Neuro-Fuzzy Vehicle Collision Prediction System
Given that road accidents occur in a real-time environment, simple crisp functions would barely provide an estimate of the gravity of the life situation. Fuzzy-based systems are a...
K. Venkatesh, Archana Ramesh, M. Alagusundaram, J....
EWCBR
2008
Springer
13 years 10 months ago
ColibriCook: A CBR System for Ontology-Based Recipe Retrieval and Adaptation
In this paper we present ColibriCook: a CBR system for ontology-based cooking recipe retrieval and adaptation. The system's purpose is to participate in the 1st Computer Cooki...
Juan DeMiguel, Laura Plaza, Belén Dí...
RSFDGRC
2009
Springer
14 years 3 months ago
Fuzzy Sets and Rough Sets for Scenario Modelling and Analysis
Abstract. Both fuzzy set theory and rough set theory play an important role in data-driven, systems modelling and analysis. They have been successfully applied to building various ...
Qiang Shen
ICIP
2003
IEEE
14 years 10 months ago
Adaptive rule-based recognition of events in video sequences
Knowledge-based fuzzy inference and neural learning are used in this paper in order to model the event recognition task in semantic video analysis. The advantage of their use is t...
Vassilis Tzouvaras, Gabriel Tsechpenakis, Giorgos ...
FSKD
2006
Springer
190views Fuzzy Logic» more  FSKD 2006»
14 years 13 days ago
A Maximum Entropy Model Based Answer Extraction for Chinese Question Answering
We regard answer extraction of Question Answering (QA) system as a classification problem, classifying answer candidate sentences into positive or negative. To confirm the feasibil...
Ang Sun, Minghu Jiang, Yanjun Ma