Search Results - (( molecular _ optimization algorithm ) OR ( molecular colony optimization algorithm ))*
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
Published 2024journal::journal article -
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A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation
Published 2022“…Binary whale optimization algorithm (BWOA) is a recently proposed metaheuristic optimization algorithm that has been efficiently applied in feature selection. …”
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Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification
Published 2021“…For this purpose, the binary version of swarm algorithms facilitated with the S-shaped or sigmoid transfer function known as binary whale optimization algorithm (BWOA), binary particle swarm optimiza-tion algorithm (BPSO), and new binary manta-ray foraging opti-mization algorithm (BMRFO) are developed for feature selection. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…This study is primarily aimed at investigating two issues in genetic algorithm (GA) and one issue in conformational search (CS) problems. …”
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Improving amphetamine-type stimulants drug classification using chaotic-based time-varying binary whale optimization algorithm
Published 2022“…A new chaotic time-varying binary whale optimization algorithm (CBWOATV) is introduced in this paper to optimize the feature selection process in Amphetamine-type Stimulants (ATS) and non-ATS drugs classification. …”
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Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification
Published 2022“…In this article, a new time-varying modified Sigmoid transfer function with two time-varying updating schemes is proposed as the binarization method for particle swarm optimization (PSO), grey wolf optimization algorithm (GWO), whale optimization algorithm (WOA), harris hawk optimization (HHO), and manta-ray foraging optimization (MRFO). …”
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Dual-head marking performance optimisation via evolutionary solutions
Published 2023Subjects:Conference paper -
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Potential of data minimization techniques approach in improving DNA sequences alignment and comparison / Syed Abdul Mutalib Al Junid … [et al.]
Published 2012“…Specifically, the research objectives are i) to study various DNA sequences alignment algorithms characteristics, architectures and techniques such as scoring functions, optimal alignment and gap; and ii) to investigate the potential of data minimization approach in minimizing the size of data towards discovering the region of similarity in DNA sequences alignment and comparison and iii) to analyze the optimal sequences alignment properties for molecular biology and bioinformatics application. …”
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Research Reports -
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Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis
Published 2011“…So,this optimization method can help to save time and cost of the process. …”
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Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review
Published 2023“…This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. The research articles published between 2020 and 2023 on machine learning and constraintbased modeling have been collected, synthesized, and analyzed. …”
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Biological-based semi-supervised clustering algorithm to improve gene function prediction
Published 2011“…However, commonclustering algorithms do not provide a comprehensive approach that look into the three categories of annotations; biologicalprocess, molecular function, and cellular component, and were not tested with different functional annotation database formats.Furthermore, the traditional clustering algorithms use random initialization which causes inconsistent cluster generation and areunable to determine the number of clusters involved. …”
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Effective adsorption of metolachlor herbicide by MIL-53(Al) metal-organic framework: Optimization, validation and molecular docking simulation studies
Published 2022“…Effective removal and optimization models of metolachlor (MET) adsorption was carried out using MIL-53(Al) metalâ��organic framework (MOF), response surface methodology (RSM), artificial neural network (ANN) and molecular docking simulation. …”
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Effective adsorption of metolachlor herbicide by MIL-53(Al) metal-organic framework: Optimization, validation and molecular docking simulation studies
Published 2022“…Effective removal and optimization models of metolachlor (MET) adsorption was carried out using MIL-53(Al) metalâ��organic framework (MOF), response surface methodology (RSM), artificial neural network (ANN) and molecular docking simulation. …”
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Optimization of emulsion polymerization of styrene and methyl methacrylate (MMA)
Published 2013“…The determination of optimal profile for control variables used for emulsion polymerization of styrene and MMA that yielded desired conversion with fixed batch time and fixed number average molecular weight in batch reactor respectively were carried out in batch reactor. …”
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Undergraduates Project Papers -
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Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…Initially, the heuristics needs user intervention to select optimal values, which give poor results. To overcome this problem, fuzzy memberships have been employed to find optimal parameters. …”
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