Search Results - (( java adaptation optimization algorithm ) OR ( trust classification modeling algorithm ))
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1
A Voting Technique Of Multilayer Perceptron Ensemble For Classification Application
Published 2014“…In order to choose the final output of MLPE, a new voting algorithm named Trust-Sum Voting (TSV) is proposed. …”
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2
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
3
Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Published 2014“…Focused on computational intelligence models, this thesis describes in-depth investigations on two possible directions to design robust and flexible pattern classification models with high performance. …”
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4
BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK
Published 2011“…Secondly, specification language, system design, mathematical and computational models for IPS and SH system are established, which are based upon nonlinear classification, prevention predictability trust, analysis, self-adaptation and self-healing algorithms. …”
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Hybrid Models Of Fuzzy Artmap And Qlearning For Pattern Classification
Published 2015“…As a result, an agent-based QFAM ensemble model with a new trust measurement and negotiation method is proposed. …”
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7
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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8
Classification and visualization of e-commerce product reviews comparison using support vector machine / Nuwairah Aimi Ahmad Kushairi
Published 2023“…Afterward, the system recommends the best shop to purchase from and visualizes the reviews to compare products from different shops. The SVM classifier model successfully classified the reviews with an accuracy of 96.8% during the testing stage of the classification. …”
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