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1
Development of support vector machine-based model and comparative analysis with artificial neural network for modeling the plant tissue culture procedures: effect of plant growth regulators on somatic embryogenesis of chrysanthemum, as a case study
Development of support vector machine-based model and comparative analysis with artificial neural network for modeling the plant tissue culture procedures: effect of plant growth regulators on somatic embryogenesis of chrysanthemum, as a case study
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Development of support vector machine-based model and comparative analysis with artificial neural network for modeling the plant tissue culture procedures: effect of plant growth regulators on somatic embryogenesis of chrysanthemum, as a case study

Plant methods, 2020-08, Vol.16 (1), p.112-112, Article 112 [Peer Reviewed Journal]

The Author(s) 2020. ;COPYRIGHT 2020 BioMed Central Ltd. ;2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2020 ;ISSN: 1746-4811 ;EISSN: 1746-4811 ;DOI: 10.1186/s13007-020-00655-9 ;PMID: 32817755

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2
An Adaptive Ensemble Machine Learning Model for Intrusion Detection
An Adaptive Ensemble Machine Learning Model for Intrusion Detection
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An Adaptive Ensemble Machine Learning Model for Intrusion Detection

IEEE access, 2019, Vol.7, p.82512-82521 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2019.2923640 ;CODEN: IAECCG

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3
Application of artificial intelligence models and optimization algorithms in plant cell and tissue culture
Application of artificial intelligence models and optimization algorithms in plant cell and tissue culture
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Application of artificial intelligence models and optimization algorithms in plant cell and tissue culture

Applied microbiology and biotechnology, 2020-11, Vol.104 (22), p.9449-9485 [Peer Reviewed Journal]

Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;COPYRIGHT 2020 Springer ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;ISSN: 0175-7598 ;EISSN: 1432-0614 ;DOI: 10.1007/s00253-020-10888-2 ;PMID: 32984921

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4
Predicting Compressive Strength of Concrete Containing Recycled Aggregate Using Modified ANN with Different Optimization Algorithms
Predicting Compressive Strength of Concrete Containing Recycled Aggregate Using Modified ANN with Different Optimization Algorithms
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Predicting Compressive Strength of Concrete Containing Recycled Aggregate Using Modified ANN with Different Optimization Algorithms

Applied sciences, 2021-01, Vol.11 (2), p.485 [Peer Reviewed Journal]

2021. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2076-3417 ;EISSN: 2076-3417 ;DOI: 10.3390/app11020485

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5
Multi-Sequence LSTM-RNN Deep Learning and Metaheuristics for Electric Load Forecasting
Multi-Sequence LSTM-RNN Deep Learning and Metaheuristics for Electric Load Forecasting
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Multi-Sequence LSTM-RNN Deep Learning and Metaheuristics for Electric Load Forecasting

Energies (Basel), 2020-01, Vol.13 (2), p.391 [Peer Reviewed Journal]

2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en13020391

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6
Hyperparameter Search for Machine Learning Algorithms for Optimizing the Computational Complexity
Hyperparameter Search for Machine Learning Algorithms for Optimizing the Computational Complexity
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Hyperparameter Search for Machine Learning Algorithms for Optimizing the Computational Complexity

Processes, 2023-02, Vol.11 (2), p.349 [Peer Reviewed Journal]

COPYRIGHT 2023 MDPI AG ;2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2227-9717 ;EISSN: 2227-9717 ;DOI: 10.3390/pr11020349

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7
A Novel Evolutionary Arithmetic Optimization Algorithm for Multilevel Thresholding Segmentation of COVID-19 CT Images
A Novel Evolutionary Arithmetic Optimization Algorithm for Multilevel Thresholding Segmentation of COVID-19 CT Images
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A Novel Evolutionary Arithmetic Optimization Algorithm for Multilevel Thresholding Segmentation of COVID-19 CT Images

Processes, 2021-07, Vol.9 (7), p.1155 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2227-9717 ;EISSN: 2227-9717 ;DOI: 10.3390/pr9071155

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8
Multi-objective optimization of building energy performance and indoor thermal comfort by combining artificial neural networks and metaheuristic algorithms
Multi-objective optimization of building energy performance and indoor thermal comfort by combining artificial neural networks and metaheuristic algorithms
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Multi-objective optimization of building energy performance and indoor thermal comfort by combining artificial neural networks and metaheuristic algorithms

Energy and buildings, 2021-05, Vol.239 [Peer Reviewed Journal]

Attribution - NonCommercial ;ISSN: 0378-7788 ;DOI: 10.1016/j.enbuild.2021.110839

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9
FNN for Diabetic Prediction Using Oppositional Whale Optimization Algorithm
FNN for Diabetic Prediction Using Oppositional Whale Optimization Algorithm
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FNN for Diabetic Prediction Using Oppositional Whale Optimization Algorithm

IEEE access, 2024, Vol.12, p.20396-20408 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2024.3357993 ;CODEN: IAECCG

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10
Performance optimization of salp swarm algorithm for multi-threshold image segmentation: Comprehensive study of breast cancer microscopy
Performance optimization of salp swarm algorithm for multi-threshold image segmentation: Comprehensive study of breast cancer microscopy
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Performance optimization of salp swarm algorithm for multi-threshold image segmentation: Comprehensive study of breast cancer microscopy

Computers in biology and medicine, 2021-12, Vol.139, p.105015-105015, Article 105015 [Peer Reviewed Journal]

2021 Elsevier Ltd ;Copyright © 2021 Elsevier Ltd. All rights reserved. ;2021. Elsevier Ltd ;ISSN: 0010-4825 ;EISSN: 1879-0534 ;DOI: 10.1016/j.compbiomed.2021.105015 ;PMID: 34800808

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11
Combining Evolutionary Algorithms and Machine Learning Models in Landslide Susceptibility Assessments
Combining Evolutionary Algorithms and Machine Learning Models in Landslide Susceptibility Assessments
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Combining Evolutionary Algorithms and Machine Learning Models in Landslide Susceptibility Assessments

Remote sensing (Basel, Switzerland), 2020-12, Vol.12 (23), p.3854 [Peer Reviewed Journal]

2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs12233854

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12
A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems
A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems
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A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems

Sustainability, 2021-10, Vol.13 (19), p.10778 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2071-1050 ;EISSN: 2071-1050 ;DOI: 10.3390/su131910778

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13
A new fruit fly optimization algorithm enhanced support vector machine for diagnosis of breast cancer based on high-level features
A new fruit fly optimization algorithm enhanced support vector machine for diagnosis of breast cancer based on high-level features
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A new fruit fly optimization algorithm enhanced support vector machine for diagnosis of breast cancer based on high-level features

BMC bioinformatics, 2019-06, Vol.20 (Suppl 8), p.290-290, Article 290 [Peer Reviewed Journal]

COPYRIGHT 2019 BioMed Central Ltd. ;2019. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s). 2019 ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-019-2771-z ;PMID: 31182028

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14
Adaptive Chaotic Marine Predators Hill Climbing Algorithm for Large-scale Design Optimisations
Adaptive Chaotic Marine Predators Hill Climbing Algorithm for Large-scale Design Optimisations
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Adaptive Chaotic Marine Predators Hill Climbing Algorithm for Large-scale Design Optimisations

IEEE access, 2023-01, Vol.11, p.1-1 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2023 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2023.3266991 ;CODEN: IAECCG

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15
Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study
Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study
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Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study

Energies (Basel), 2017, Vol.10 (2), p.245-245 [Peer Reviewed Journal]

Copyright MDPI AG 2017 ;ISSN: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en10020245

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16
A novel and innovative cancer classification framework through a consecutive utilization of hybrid feature selection
A novel and innovative cancer classification framework through a consecutive utilization of hybrid feature selection
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A novel and innovative cancer classification framework through a consecutive utilization of hybrid feature selection

BMC bioinformatics, 2023-12, Vol.24 (1), p.479-479, Article 479 [Peer Reviewed Journal]

2023. The Author(s). ;COPYRIGHT 2023 BioMed Central Ltd. ;2023. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-023-05605-5 ;PMID: 38102551

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17
An Efficient Intrusion Detection Model Based on Hybridization of Artificial Bee Colony and Dragonfly Algorithms for Training Multilayer Perceptrons
An Efficient Intrusion Detection Model Based on Hybridization of Artificial Bee Colony and Dragonfly Algorithms for Training Multilayer Perceptrons
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An Efficient Intrusion Detection Model Based on Hybridization of Artificial Bee Colony and Dragonfly Algorithms for Training Multilayer Perceptrons

IEEE access, 2020-01, Vol.8, p.1-1 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2020.3009533 ;CODEN: IAECCG

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18
A Model-Assisted Combined Machine Learning Method for Ionospheric TEC Prediction
A Model-Assisted Combined Machine Learning Method for Ionospheric TEC Prediction
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A Model-Assisted Combined Machine Learning Method for Ionospheric TEC Prediction

Remote sensing (Basel, Switzerland), 2023-06, Vol.15 (12), p.2953 [Peer Reviewed Journal]

COPYRIGHT 2023 MDPI AG ;2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs15122953

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19
A Novel Hybrid MPPT Approach for Solar PV Systems Using Particle-Swarm-Optimization-Trained Machine Learning and Flying Squirrel Search Optimization
A Novel Hybrid MPPT Approach for Solar PV Systems Using Particle-Swarm-Optimization-Trained Machine Learning and Flying Squirrel Search Optimization
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A Novel Hybrid MPPT Approach for Solar PV Systems Using Particle-Swarm-Optimization-Trained Machine Learning and Flying Squirrel Search Optimization

Sustainability, 2023-03, Vol.15 (6), p.5575 [Peer Reviewed Journal]

COPYRIGHT 2023 MDPI AG ;2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2071-1050 ;EISSN: 2071-1050 ;DOI: 10.3390/su15065575

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20
Design deep neural network architecture using a genetic algorithm for estimation of pile bearing capacity
Design deep neural network architecture using a genetic algorithm for estimation of pile bearing capacity
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Design deep neural network architecture using a genetic algorithm for estimation of pile bearing capacity

PloS one, 2020-12, Vol.15 (12), p.e0243030-e0243030 [Peer Reviewed Journal]

COPYRIGHT 2020 Public Library of Science ;COPYRIGHT 2020 Public Library of Science ;2020 Pham et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 Pham et al 2020 Pham et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0243030 ;PMID: 33332377

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