scholarly journals On Efficient Representation of Expert Knowledge by Fuzzy Logic: Towards an Optimal Combination of Granularity and Higher-Order Approaches

2003 ◽  
pp. 107-132 ◽  
Author(s):  
Hung T. Nguyen ◽  
Vladik Kreinovich
Keyword(s):  
Fuzzy Logic ◽  
Expert Knowledge ◽  
Higher Order ◽  
Optimal Combination ◽  
Efficient Representation

Implementation of Fuzzy Logic Control on Battery Charging System

2019 ◽  
Vol 3 (1) ◽  
pp. 118-126 ◽  
Author(s):  
Prihangkasa Yudhiyantoro
Keyword(s):  
Complex System ◽  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Expert Knowledge ◽  
Experimental Result ◽  
Rule Base ◽  
Battery Charging ◽  
Charging System ◽  
Logic Control ◽  
Charging Control

This paper presents the implementation fuzzy logic control on the battery charging system. To control the charging process is a complex system due to the exponential relationship between the charging voltage, charging current and the charging time. The effective of charging process controller is needed to maintain the charging process. Because if the charging process cannot under control, it can reduce the cycle life of the battery and it can damage the battery as well. In order to get charging control effectively, the Fuzzy Logic Control (FLC) for a Valve Regulated Lead-Acid Battery (VRLA) Charger is being embedded in the charging system unit. One of the advantages of using FLC beside the PID controller is the fact that, we don’t need a mathematical model and several parameters of coefficient charge and discharge to software implementation in this complex system. The research is started by the hardware development where the charging method and the combination of the battery charging system itself to prepare, then the study of the fuzzy logic controller in the relation of the charging control, and the determination of the parameter for the charging unit will be carefully investigated. Through the experimental result and from the expert knowledge, that is very helpful for tuning of the  embership function and the rule base of the fuzzy controller.

scholarly journals Experts versus Algorithms? Optimized Fuzzy Logic Energy Management of Autonomous PV Hybrid Systems with Battery and H2 Storage

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1777
Author(s):  
Lisa Gerlach ◽  
Thilo Bocklisch
Keyword(s):  
Fuzzy Logic ◽  
Energy Management ◽  
Fuzzy Logic Controller ◽  
Expert Knowledge ◽  
Large Power ◽  
Hybrid Energy ◽  
Knowledge Based ◽  
Long Term Storage ◽  
Fuzzy Logic Approach

Off-grid applications based on intermittent solar power benefit greatly from hybrid energy storage systems consisting of a battery short-term and a hydrogen long-term storage path. An intelligent energy management is required to balance short-, intermediate- and long-term fluctuations in electricity demand and supply, while maximizing system efficiency and minimizing component stress. An energy management was developed that combines the benefits of an expert-knowledge based fuzzy logic approach with a metaheuristic particle swarm optimization. Unlike in most existing work, interpretability of the optimized fuzzy logic controller is maintained, allowing the expert to evaluate and adjust it if deemed necessary. The energy management was tested with 65 1-year household load datasets. It was shown that the expert tuned controller is more robust to changes in load pattern then the optimized controller. However, simple readjustments restore robustness, while largely retaining the benefits achieved through optimization. Nevertheless, it was demonstrated that there is no one-size-fits-all tuning. Especially, large power peaks on the demand-side require overly conservative tunings. This is not desirable in situations where such peaks can be avoided through other means.

Expert Knowledge-Based Traction Control of a Truck Using Fuzzy Logic

1996 ◽  
Vol 29 (1) ◽  
pp. 7867-7872
Author(s):  
Ka C. Cheok ◽  
Kazuyuki Kobayashi ◽  
Francis B. Hoogterp
Keyword(s):  
Fuzzy Logic ◽  
Expert Knowledge ◽  
Traction Control ◽  
Knowledge Based

scholarly journals Gaudii: An Automated Graphic Design Expert System

2021 ◽  
Vol 24 (2) ◽  
pp. 1775-1780
Author(s):  
Carlos Glez-Morcillo ◽  
Victor Martin ◽  
David Vallejo Fernandez ◽  
Jose Castro-Schez ◽  
Javier Albusac
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Evolutionary Computation ◽  
Graphic Design ◽  
Expert Knowledge ◽  
Trial And Error ◽  
Design Elements ◽  
Design Expert ◽  
Novel Approach ◽  
Design Activities

Graphic design is the process of creating graphics to meet specific commercial needs based on knowledge of layout principles and esthetic concepts. This is usually an iterative trial and error process which requires a lot of time even for expert designers. This expert knowledge can be modelled, represented and used by a computer to perform design activities. This paper describes a novel approach named Gaudii (standing for "Intelligent Automated Graphic Design Generator") which utilizes principles and techniques known from the fields of Evolutionary Computation and Fuzzy Logic to automatically obtain design elements. Experimental results that demonstrate the potential of the proposed approach are presented in the area of poster design.

scholarly journals DETERMINATION OF COST OF PRODUCTION IN CONDITIONS OF UNCERTAINTY OF ORDERS

2016 ◽  
Vol 4 (4) ◽  
pp. 499-504
Author(s):  
Ольга Глод ◽  
Olga Glod ◽  
Виктор Ланкин ◽  
Viktor Lankin
Keyword(s):  
Fuzzy Logic ◽  
Expert Knowledge ◽  
Small Enterprises ◽  
Methodological Basis ◽  
Cost Of Production ◽  
The Cost

The purpose of this paper is to examine the model to determine the cost of production of small enterprises. The methodological basis for the model is a fuzzy logic based on expert knowledge. As a result, in this paper we consider an example of the model, determined the cost of production of confectionery

Comparison of Linguistic Summaries and Fuzzy Functional Dependencies Related to Data Mining

2014 ◽  
pp. 174-203 ◽  
Author(s):  
Miroslav Hudec ◽  
Miljan Vučetić ◽  
Mirko Vujošević
Keyword(s):  
Data Mining ◽  
Fuzzy Logic ◽  
Relational Databases ◽  
Missing Values ◽  
Expert Knowledge ◽  
Real Data ◽  
Research Area ◽  
Functional Dependencies ◽  
Useful Knowledge ◽  
Important Research Area

Data mining methods based on fuzzy logic have been developed recently and have become an increasingly important research area. In this chapter, the authors examine possibilities for discovering potentially useful knowledge from relational database by integrating fuzzy functional dependencies and linguistic summaries. Both methods use fuzzy logic tools for data analysis, acquiring, and representation of expert knowledge. Fuzzy functional dependencies could detect whether dependency between two examined attributes in the whole database exists. If dependency exists only between parts of examined attributes' domains, fuzzy functional dependencies cannot detect its characters. Linguistic summaries are a convenient method for revealing this kind of dependency. Using fuzzy functional dependencies and linguistic summaries in a complementary way could mine valuable information from relational databases. Mining intensities of dependencies between database attributes could support decision making, reduce the number of attributes in databases, and estimate missing values. The proposed approach is evaluated with case studies using real data from the official statistics. Strengths and weaknesses of the described methods are discussed. At the end of the chapter, topics for further research activities are outlined.

scholarly journals How Can Climate Resilience Be Measured and Visualized? Assessing a Vague Concept Using GIS-Based Fuzzy Logic

2020 ◽  
Vol 12 (2) ◽  
pp. 635 ◽  
Author(s):  
Mathias Schaefer ◽  
Nguyen Xuan Thinh ◽  
Stefan Greiving
Keyword(s):  
Fuzzy Logic ◽  
Expert Knowledge ◽  
Ecological Factors ◽  
Climate Resilience ◽  
Urban Core ◽  
Essential Components ◽  
Local Expert ◽  
Vague Concept ◽  
Negative Impacts ◽  
The City

As negative impacts of climate change tend to increase in the future, densely-populated cities especially need to take action on being robust against natural hazards. Consequently, there is a growing interest from scientists in measuring the climate resilience of cities and regions. However, current measurements are usually assessed on administrative levels, not covering potential hotspots of hazardous or sensitive areas. The main aim of this paper focusses on the measurement of climate resilience in the City of Dortmund, Germany, using Geographic Information Systems (GIS). Based on a literature review, we identified five essential components of climate resilience and initially designed a theoretical framework of 18 indicators. Since climate resilience is still a vague concept in scientific discourses, we implemented local expert knowledge and fuzzy logic modelling into our analysis. The benefit of this study not only lies in the fine-scale application, but also in the relevance for multiple disciplines by integrating social and ecological factors. We conclude that climate resilience varies within the city pattern, with the urban core tending to be less resilient than its surrounding districts. As almost the entire geodata set used is freely available, the presented indicators and methods are to a certain degree applicable to comparable cities.

scholarly journals PROTECTION OF SCIENTIFIC AND EDUCATIONAL RESOURCES IN INFORMATION AND LIBRARY SYSTEMS

2019 ◽  
Vol 2 (2) ◽  
pp. 121-128
Author(s):  
M. A. Rakhmatullaev ◽  
Sh. B. Normatov
Keyword(s):  
Fuzzy Logic ◽  
Knowledge Base ◽  
Information Technologies ◽  
Expert Knowledge ◽  
Fuzzy Model ◽  
Educational Resources ◽  
Electronic Library ◽  
Unauthorized Access ◽  
Degree Of Protection ◽  
Corporate Network

Introduction. The authors of the article highlight the results of research on the development of methods and tools for ensuring the information security of scientific and educational resources in information library systems and corporate information networks. The analysis of the state of the problem and the existing approaches on this topic are given too.Materials and Methods. The approach justifies the need to protect scientific resources from unauthorized access and the use of fuzzy logic to solve the problem. As a model and solution method, a fuzzy model correspondences is proposed, which makes it possible to comprehensively solve the problem of identifying threats in the event of a situation, as well as provide recommendations on how to eliminate them. For the formation of a knowledge base, experts are involved who determine the functions of belonging to knowlege base “Situation — Threats — Actions to eliminate the threats”.Results. The research results are being implemented as part of the ARMAT++ information library system of the corporate network of electronic libraries of 63 Uzbekistan universities for the protection of scientific and educational information from unauthorized access. Testing of the methods, programs of the subsystem and the expert knowledge base are carried out on the basis of information and resource centers under the project “Virtual electronic library of the Tashkent University of Information Technologies named after Muhammad Al-Khorezmi and its five branches”.Discussion and Conclusions. The use of the apparatus of fuzzy logic for the formation of a knowledge base of the “Situation — Threats — Actions to eliminate the threats” type in information library systems significantly increases the degree of protection of valuable information resources from unauthorized access.

Sign in / Sign up

Export Citation Format

Share Document