Projection of Fuzzy Knowledge Over X-Axis for a Unified Multi-valued Framework

2018 ◽  
Vol 44 (4) ◽  
pp. 3061-3082
Author(s):  
Soumaya Moussa ◽  
Saoussen Bel Hadj Kacem
Keyword(s):  
Fuzzy Knowledge

scholarly journals Short-Term Fuzzy Load Forecasting Model Using Genetic–Fuzzy and Ant Colony–Fuzzy Knowledge Base Optimization

2018 ◽  
Vol 8 (6) ◽  
pp. 864 ◽  
Author(s):  
Murat Luy ◽  
Volkan Ates ◽  
Necaattin Barisci ◽  
Huseyin Polat ◽  
Ertugrul Cam
Keyword(s):  
Knowledge Base ◽  
Load Forecasting ◽  
Ant Colony ◽  
Forecasting Model ◽  
Short Term ◽  
Fuzzy Knowledge

scholarly journals The use of fuzzy databases and knowledge bases for aiding engineering projects

2013 ◽  
Vol 12 (1) ◽  
pp. 069-076
Author(s):  
Janusz Szelka ◽  
Zbigniew Wrona
Keyword(s):  
Decision Making ◽  
Database Systems ◽  
Knowledge Bases ◽  
Fuzzy Data ◽  
Fuzzy Knowledge Bases ◽  
Decision Making Processes ◽  
Engineering Projects ◽  
Fuzzy Knowledge

The IT tools that are widely used for aiding information and decision-making tasks in engineering activities include classic database systems, and in the case of problems with poorly-recognised structure – systems with knowledge bases. The uniqueness of these categories of systems allows, however, neither to represent the approximate or imprecise nature of available data or knowledge nor to process fuzzy data. Since so far there have been no solutions related to the use of fuzzy databases or fuzzy knowledge bases in engineering projects, it seems necessary to make an attempt to assess the possible employment of these technologies to aid analytical and decision-making processes.

scholarly journals A Fuzzy Control Heuristic Applied to Non-linear Dynamic System Using a Fuzzy Knowledge Representation

2010 ◽  
Vol 5 (5) ◽  
pp. 664 ◽  
Author(s):  
Felisa M. Cordova ◽  
Guillermo Leyton
Keyword(s):  
Knowledge Representation ◽  
Fuzzy Control ◽  
Dynamic Systems ◽  
Nonlinear Dynamic ◽  
Nonlinear Dynamic Systems ◽  
System State ◽  
Specific Level ◽  
Base Matrix ◽  
Different Levels ◽  
Fuzzy Knowledge

This paper presents the design of a fuzzy control heuristic that can be applied for modeling nonlinear dynamic systems using a fuzzy knowledge representation. Nonlinear dynamic systems have been modeled traditionally on the basis of connections between the subsystems that compose it. Nevertheless, this model design does not consider some of the following problems: existing dynamics between the subsystems; order and priority of the connection between subsystems; degrees of influence or causality between subsystems; particular state of each subsystem and state of the system on the basis of the combination of the diverse states of the subsystems; positive or negative influences between subsystems. In this context, the main objective of this proposal is to manage the whole system state by managing the state combination of the subsystems involved. In the proposed design the diverse states of subsystems at different levels are represented by a knowledge base matrix of fuzzy intervals (KBMFI). This type of structure is a fuzzy hypercube that provides facilities operations like: insert, delete, and switching. It also allows Boolean operations between different KBMFI and inferences. Each subsystem in a specific level and its connectors are characterized by factors with fuzzy attributes represented by membership functions. Existing measures the degree of influence among the different levels are obtained (negatives, positives). In addition, the system state is determined based on the combination of the statements of the subsystems (stable, oscillatory, attractor, chaos). It allows introducing the dynamic effects in the calculation of each output level. The control and search of knowledge patterns are made by means of a fuzzy control heuristic. Finally, an application to the co-ordination of the activities among different levels of the operation of an underground mine is developed and discussed.

Real-time fuzzy-knowledge-based control of Baker's yeast production

1995 ◽  
Vol 45 (2) ◽  
pp. 135-143 ◽  
Author(s):  
Terhi Siimes ◽  
Pekka Linko ◽  
Camilla von Numers ◽  
Mikio Nakajima ◽  
Isao Endo
Keyword(s):  
Real Time ◽  
Baker’S Yeast ◽  
Baker's Yeast ◽  
Knowledge Based ◽  
Yeast Production ◽  
Fuzzy Knowledge
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