Evolutionary Multi-objective Optimization for Evolving Hierarchical Fuzzy System
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86099114" target="_blank" >RIV/61989100:27240/15:86099114 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/15:86099114
Result on the web
<a href="http://dx.doi.org/10.1109/CEC.2015.7257284" target="_blank" >http://dx.doi.org/10.1109/CEC.2015.7257284</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CEC.2015.7257284" target="_blank" >10.1109/CEC.2015.7257284</a>
Alternative languages
Result language
angličtina
Original language name
Evolutionary Multi-objective Optimization for Evolving Hierarchical Fuzzy System
Original language description
In this paper, a Multi-Objective Extended Genetic Programming (MOEGP) algorithm is developed to evolve the structure of the Hierarchical Flexible Beta Fuzzy System (HFBFS). The proposed algorithm allows finding the best representation of the hierarchical fuzzy system while trying to attain the desired balance of accuracy/interpretability. Furthermore, the free parameters (Beta membership functions and the consequent parts of rules) encoded in the best structure are tuned by applying the hybrid Bacterial Foraging Optimization Algorithm (the hybrid BFOA). The proposed methodology interleaves both MOEGP and the hybrid BFOA for the structure and the parameter optimization respectively until a satisfactory HFBFS is found. The performance of the approach is evaluated using several classification datasets with low and high input dimensions. Results prove the superiority of our method as compared with other existing works.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: IT4Innovations Centre of Excellence</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2015 IEEE Congress on Evolutionary Computation (CEC) : proceedings : May 25-28, 2015, Sendai, Japan
ISBN
978-1-4799-7492-4
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
3163-3170
Publisher name
IEEE
Place of publication
New York
Event location
Sendai
Event date
May 25, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000380444803027