Search Results - (( using normalization bat algorithm ) OR ( basic selection methods algorithm ))
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
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In silico gene knockout prediction using a hybrid of Bat algorithm and minimization of metabolic adjustment
Published 2021“…Metabolic and genetic engineering is important in producing the chemicals of interest as, without them, the product yields of many microorganisms are normally low. As a result, the aim of this paper is to propose a combination of the Bat algorithm and the minimization of metabolic adjustment (BATMOMA) to predict which genes to knock out in order to increase the succinate and lactate production rates in Escherichia coli (E. coli).…”
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Optimal operation of multi-reservoir systems for increasing power generation using a seagull optimization algorithm and heading policy
Published 2021“…The Seagull Optimization Algorithm was subsequently benchmarked against the Salp Swarm Algorithm (SSA), Bat Algorithm (BA) and the Shark Optimization Algorithm (SOA). …”
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An ensemble feature selection method to detect web spam
Published 2018“…In addition, it improves classification metrics in comparison to basic feature selection methods.…”
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Enhanced Distributed Learning Classifier System For Simulated Mobile Robot Behaviours
Published 2010“…This thesis proposes methods that can overcome the problems of good behaviour selection and good behaviour deletion. …”
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Thesis -
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Development Of Double Stage Filter (DSF) On Stereo Matching Algorithm For 3D Computer Vision Applications
Published 2016“…Based on the results of evaluations, the results obtained by DSF is better than the algorithms, basic block matching and dynamic programming.…”
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Improved Multi-Verse Optimizer In Text Document Clustering For Topic Extraction
Published 2021“…To achieve this aim: First, A new feature selection method for TDC, that is, binary multi-verse optimizer algorithm (BMVO) is proposed to eliminate irrelevantly, redundant features and obtain a new subset of more informative features. …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus
Published 2003“…A systematic method for selecting the ANN's input variables was developed using Matlab Programming language.…”
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Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches
Published 2015“…Artificial Bee Colony (ABC) algorithm is one of the methods used to solve the flowshop scheduling problem but only a few researches have been found using this method in this area. …”
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Robust correlation feature selection based support vector machine approach for high dimensional datasets
Published 2025“…Correlation-based feature selection methods are popular tools used to select the most important variables to include the true model in the analysis of sparse and high-dimensional models. …”
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Static image of hand gesture for numerical sign language recognition system using backfrofagation neural network / Erman Ibrahim
Published 2007“…Finally, the BP algorithm has been prove as a method that can be used for recognizing hand gesture for sign language and the successful task of recognition also dependent an the hnage processing. …”
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A phonetically rich and balanced lexical corpus using zipfian distribution for an under resourced language / Aminath Farshana
Published 2018“…The performance of the proposed method was also evaluated by comparing the results with an existing benchmark method (greedy algorithm). …”
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The advantages of genetic algorithm and neural networks to forecast air pollution trend in Malaysia: an overview / Mohamad Idham Md Razak … [et al.]
Published 2012“…Genetic Algorithms (GAs) are adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. …”
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An Improved Evolutionary Algorithm in Formulating a Diet for Grouper
Published 2023“…Hence, in this paper, an improved EA method known as the SR-SD-EA is proposed highlighting three important EA operators, which are initialization, selection and mutation. …”
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