Search Results - (( yield selection methods algorithm ) OR ( using optimization method algorithm ))
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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024“…Thus, this study proposed an Opposition-based Learning Binary Bat Algorithm as the feature selection technique in the T-method. …”
Conference Paper -
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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3
Hybrid binary grey Wolf with Harris hawks optimizer for feature selection
Published 2021“…The proposed hybrid method outperforms the BGWO algorithm in terms of accuracy, selected feature size, and computational time. …”
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Hybrid Binary Grey Wolf with Harris Hawks Optimizer for Feature Selection
Published 2021“…The proposed hybrid method outperforms the BGWO algorithm in terms of accuracy, selected feature size, and computational time. …”
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Hybrid binary grey Wolf with Harris hawks optimizer for feature selection
Published 2021“…The proposed hybrid method outperforms the BGWO algorithm in terms of accuracy, selected feature size, and computational time. …”
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Optimization of stiffened panel fatigue life by using finite element analysis
Published 2020“…The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…After the variable selection process using the proposed method, the optimal prediction model is now formulated with a lesser variable, making it less complex and computationally fast. ? …”
Conference paper -
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Development of committee machine models for multiple response optimization problems
Published 2014“…Responses of Taguchi are restricted to be selected from defined levels of input variables and newer hybrid methods use only one ANN in modeling. …”
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9
Feature fusion using a modified genetic algorithm for face and signature recognition system
Published 2015“…Results show that the proposed method yield optimal recognition with the highest accuracy of 97.50%. …”
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10
Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction
Published 2024“…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2023“…Calculations of the optimized tilt and surface azimuth angles on monthly, seasonal and yearly basis were conducted, with the genetic algorithm being used for this purpose. …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…The research endeavors to develop a web-based system specifically designed to create personalized university timetables for Universiti Teknologi MARA (UiTM) students using genetic algorithms, aiming to address the urgent need for a customizable timetable solution catering to the diverse scheduling requirements of both repeater and non-repeater students while optimizing course group selection to minimize conflicts and enhance scheduling flexibility. …”
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Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk
Published 2019“…Meanwhile, based on the fuzzy simulation technique, the model adapted to a series of different distributed fuzzy variable, an improved particle swarm optimization algorithm (IPSO) is used for numerical simulations. …”
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Optimization of operational policies for the Minab Reservoir, Southern Iran
Published 2012“…Rule curve for five possible scenarios were optimized by using Genetic Algorithms. The agricultural management optimization was applied to optimize the parameters like area, relative yield water requirements and irrigation efficiency. …”
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15
Analysis and evaluation of various aspects of solar radiation in the Palestinian territories
Published 2013“…Calculations of the optimized tilt and surface azimuth angles on monthly, seasonal and yearly basis were conducted, with the genetic algorithm being used for this purpose. …”
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Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements
Published 2022“…Moreover, the improvements of different QoS metrics values achieved by using a minimum-weight-based multi-objective algorithm (MOS-MWO) for scheduling scientific workflows are better than those of the previous work which used the Pareto optimization method. …”
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Multi-objectives process optimization in end milling process of aluminium alloy 6061-T6 using genetic algorithm
Published 2024“…However, only a final solution was selected according to the multi-objective optimization of each insert used in the experiments. …”
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Using genetic algorithms to optimise land use suitability
Published 2012“…The Erosion Potential Method (EPM) used in erosion estimation and sediment yield of the study. …”
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20
Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…Experimentally observed responses were used to train, map and optimize the network algorithms before the best architecture was selected. …”
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