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Improving Transparency in Approximate Fuzzy Modeling Using Multi-objective Immune-Inspired Optimisation
2012
International Journal of Computational Intelligence Systems
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The proposed mechanism adopts a multistage modeling procedure and a variable length coding scheme to account for the enlarged search space due to simultaneous optimisation of the rule-base structure and ...
We claim here that IMOFM can account for both Singleton and Mamdani Fuzzy Rule-Based Systems (FRBS) due to the carefully chosen output membership functions, the inference scheme and the defuzzification ...
When similar fuzzy sets are merged, rules may become similar so that they will be merged consequently, a consideration which makes the rule-base more compact. ...
doi:10.1080/18756891.2012.685311
fatcat:jxxmr6arybhpte46e5ntm63drm
Ontology optimisation-Problematics & methodology, with a first step of formalism
2005
Progress in Informatics
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Computational Mathematics on the Semantic Web: Feasibility and Application Perspectives ...
7: Fuzzy Logic Framework, stack 8: Fuzzy Proof, and even -sometimes, for some specific applications-Fuzzy Trust, as in Fuzzy Vaults ; 13 also in. 14 A second unavoidable one is on Fuzzy Optimisation related ...
A first section of our coming paper related to this research will be on "Fuzzification" of the 9-stack Semantic Web Model recalled above, section 4 : Stack 5: Fuzzy Ontology, stack 6: Fuzzy Rules, stack ...
doi:10.2201/niipi.2005.2.7
fatcat:ujozilgknrchzohe4exlceiwhm
Multi-objective optimisations for a superscalar architecture with selective value prediction
2012
IET Computers & Digital Techniques
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We implemented a domain ontology consisting of some micro-architectural restrictions and expert knowledge expressed through fuzzy rules, in order to accelerate the design space exploration. ...
approach. ...
Also we would like to thank Camil Bancioiu for his support with the M-SIM connector and to Ciprian Radu for his useful comments. ...
doi:10.1049/iet-cdt.2011.0116
fatcat:rcfxf6clqrembfiy6crbwc5tka
Controller tuning using evolutionary multi-objective optimisation: Current trends and applications
2014
Control Engineering Practice
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A traditional approach to calculate a solution with the desired trade-off is to define an optimisation statement. ...
In this paper, this design procedure based on evolutionary multiobjective optimisation (EMO) is presented and significant applications on controller tuning are commented on. ...
Ministry of Economy and Competitiveness. ...
doi:10.1016/j.conengprac.2014.03.003
fatcat:fnimabw6q5dvbfbdhmm7xilf2i
Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation
2019
Applied Mathematics and Computation
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2019 pre-print arXiv:1911.13011v1 fatcat:asv5ngcbsrdpzmohrwvfstxjieOther Versions
This paper provides a systematic review and meta-analysis that emphasise on reviewing the related studies and recent developments on BSA. ...
The experiments conducted in previous studies demonstrated the successful performance of BSA and its non-sensitivity toward the several types of optimisation problems. ...
This paper's technical content has significantly improved based on their suggestions. ...
doi:10.1016/j.amc.2019.124919
fatcat:w53m6amd7rdgbk4cfhtyk6jovu
Perpetual Learning Framework based on Type-2 Fuzzy Logic System for a Complex Manufacturing Process
2016
IFAC-PapersOnLine
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The proposed method relies on the creation of new fuzzy rules which are updated and optimised during the incremental learning process. ...
The rule growing/pruning strategy is used to guarantee that the proposed structure can be used in a perpetual learning mode. ...
UK for the financial support and for providing expert knowledge and data for the case study, and also The University of Sheffield for the financial support. ...
doi:10.1016/j.ifacol.2016.10.111
fatcat:wmwsnf65d5c2dcnrih4l3r63w4
Evolutionary multi-objective optimisation with preferences for multivariable PI controller tuning
2016
Expert systems with applications
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to enhance convergence and diversity. ...
Abstract Multi-objective optimisation design procedures have shown to be a valuable tool for control engineers. ...
Such tools range from neural networks, fuzzy logic systems and evolutionary algorithms (Albertos, 2007; Ruano, 2007; Tzafestas, 2007) to rule-based and knowledge-based systems (Liao, 2005) . ...
doi:10.1016/j.eswa.2015.11.028
fatcat:q42jm472pbbitirr6xjgufdlxy
MCS—A new algorithm for multicriteria optimisation in constraint programming
2006
Annals of Operations Research
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It is implemented in CP in a dedicated framework and can be specialised for either complete or partial search. ...
In this paper we propose a new algorithm called MCS for the search for solutions to multicriteria combinatorial optimisation problems. ...
Acknowledgments We would like to thank our anonymous reviewers for their valuable and detailed comments. ...
doi:10.1007/s10479-006-0064-1
fatcat:372cboxntrdb3hfzajs4eznsbm
The Application of Hybrid Evolving Connectionist Systems to Image Classification
2000
Journal of Advanced Computational Intelligence and Intelligent Informatics
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EFuNNS merge three supervised classification methods: connectionism, fuzzy logic, and case-based reasoning. ...
This paper presents a methodology for image classification of both spatial and spectral data with the use of hybrid evolving fuzzy neural networks (EFuNNS). ...
The SPOT imagery was purchased through a grant from the New Zealand Lottery Board. The fruit image data is owned by HortResearch, New Zealand. The authors thank Dr. ...
doi:10.20965/jaciii.2000.p0057
fatcat:rkmqqjmnvvcdflc3jan5okz4yi
Neuro-fuzzy Modeling and Fuzzy Rule Extraction Applied to Conflict Management
[chapter]
2006
Lecture Notes in Computer Science
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Furthermore, it found that the fuzzy model offers high levels of transparency in the form of fuzzy rules. It is then shown how these rules can be translated in order to validate the fuzzy model. ...
The Takagi-Sugeno model is found to be suitable for interstate modeling as it demonstrates good forecasting ability while offering a transparent interpretation of the modeled rules. ...
Setnes et al [13] present a similarity measure for fuzzy rule based simplification. Two methods of simplifying rules that are proposed are the removal and/or merging of similar fuzzy sets. ...
doi:10.1007/11893295_120
fatcat:jpayp45v3vbnhnif63iiww7xde
Evolving fuzzy neural networks in adaptive knowledge bases to support task-oriented decision making for sensor management
2007
2007 10th International Conference on Information Fusion
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Several rule-learning algorithms [4-7] do not readily fulfil the identified requirements and selecting a more suitable alternative constitutes the focus of this paper. ...
This paper selects the adaptive online-learning Evolving Fuzzy Neural Network (EFUNN) [8, 9] and details two algorithmic and one qualitative contribution that enhance EFUNN's ability to realize the construction ...
Merge function The merge function is facilitated by EFUNN's rule aggregation feature to merge or combine two dissimilar knowledge bases by allowing rule-sets from one knowledge base to merge with those ...
doi:10.1109/icif.2007.4408088
dblp:conf/fusion/KongNTT07
fatcat:4m7gn6z6gvcuvkcy4efjinn7tq
Synthesis and optimisation of an integrated water and membrane network framework with multiple electrodialysis regenerators
2016
Computers and Chemical Engineering
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To demonstrate the proposed approach, the model is applied to a pulp and paper plant case study. ...
In this regard, the model developed is for the simultaneous optimisation of water and energy. ...
Optimisation under uncertainty, either based on flexibility, fuzzy programming or on stochastic programming, allows water network synthesis under both normal and disturbance conditions (Feng et al., 2010 ...
doi:10.1016/j.compchemeng.2015.11.005
fatcat:o62pjl5x7nb4lebtm4dxgxi7re
Adaptive, Evolving, Hybrid Connectionist Systems for Image Pattern Recognition
[chapter]
2000
Studies in Fuzziness and Soft Computing
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The systems are based on dynamically evolving fuzzy neural networks that are neural architectures to realise connectionist learning, fuzzy logic inference, and case-based reasoning. ...
The department offers courses of study leading to a major in Information Science within the BCom, BA and BSc degrees. ...
Acknowledgements This work was partially supported by the research grants UOO808 and HR0809 funded by t h e F oundation of Research, Science and Technology of New Zealand. ...
doi:10.1007/978-3-7908-1858-1_13
fatcat:4jp7rxdqvfgybjxi6tiu7wax4q
An Incremental Learning of Concept Drifts Using Evolving Type-2 Recurrent Fuzzy Neural Networks
2017
IEEE transactions on fuzzy systems
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The eT2RFNN adopts a holistic concept of evolving systems, where the fuzzy rule can be automatically generated, pruned, merged and recalled in the single pass learning mode. eT2RFNN is capable of coping ...
The new recurrent network architecture evolves a generalized interval type-2 fuzzy rule, where the rule premise is built upon the interval type-2 multivariate Gaussian function, while the rule consequent ...
modules: rule merging, pruning, etc, which warrants the rule base complexity at a low level and avoids the overfitting case. ...
doi:10.1109/tfuzz.2016.2599855
fatcat:6pvyhj22e5dsviht6aznjdqdzq
An overview on subgroup discovery: foundations and applications
2010
Knowledge and Information Systems
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Subgroup discovery is a data mining technique which extracts interesting rules with respect to a target variable. ...
An important characteristic of this task is the combination of predictive and descriptive induction. An overview related to the task of subgroup discovery is presented. ...
Her research interests include fuzzy rule-based systems, fuzzy and linguistic modelling, fuzzy classification, machine learning, genetic fuzzy systems, and data mining. ...
doi:10.1007/s10115-010-0356-2
fatcat:7o6opddi4bfbpnutkghq7i335u
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