Photovoltaic Generation Integration with Radial Feeders Using GA and GIS by Elias Mandefro Getie, Belachew Bantyirga Gessesse, Tewodros Gera Workneh

“…The optimal allocation of PV has been done using the Genetic Algorithm (GA) for optimization of a multiobjective function with different constraints. …”
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Assessing chemical exposure risk in breastfeeding infants: An explainable machine learning model for human milk transfer prediction by Xiaojie Huang, Jiajia Chen, Peineng Liu

“…The balanced random forest classifier, optimized using the genetic algorithm for feature selection, achieved an area under the receiver operating characteristic curve (AUC) of 0.8708 and an accuracy of 82.67 % on the internal test set, with an accuracy of 86.36 % on the external validation set. …”
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RSM-, ANN-, and GA-Based Process Optimization for Acid Centrifugation Treatment of Cane Molasses Toward Mitigating Calcium Oxide Fouling in Ethanol Plant Heat Exchanger by Lata Deso Abo, Sintayehu Mekuria Hailegiorgis, Mani Jayakumar, Sundramurthy Venkatesa Prabhu, Gadissa Tokuma Gindaba, Abas Siraj Hamda, B. S. Naveen Prasad

“…Furthermore, the implementation of an artificial neural network (ANN) provided a better prediction model for CaO reduction, with a substantial R-squared value of 0.99866. However, the genetic algorithm (GA) optimization resulted in an actual CaO reduction of 66.21 wt.% with a t-test value of 0.497726.…”
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Research on Optimization of Injection Molding Process Parameters of Automobile Plastic Front-End Frame by Kai Yang, Lingfeng Tang, Peng Wu

“…A back propagation (BP) neural network model with input as a process parameter and output as an evaluation index is established by MATLAB and optimized by a genetic algorithm (GA). Finally, the optimized neural network model was used to predict the combination of process parameters with the minimum volume shrinkage and warpage amount. …”
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Metaheuristics Approach for Hyperparameter Tuning of Convolutional Neural Network by Hindriyanto Purnomo, Tad Gonsalves, Evangs Mailoa, Fian Julio Santoso, Muhammad Rizky Pribadi

“…Three metaheuristic methods are used in this research: ant colony optimization (ACO), genetic algorithm (GA), and Harmony Search (HS). The metaheuristics methods are used to find the best combination of 8 hyperparameters with 8 options each which creates 1.6. 107 of solution space. …”
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Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions by Xiaomin Xu, Dongxiao Niu, Yan Li, Lijie Sun

“…Finally, the nondominated sorting genetic algorithm (NSGA-II) is introduced to solve the above optimization problems. …”
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Retrieval of water quality parameters based on IOA-ML models and their response to short-term hydrometeorological factors by Wentong Hu, Donghao Miao, Chi Zhang, Zixian He, Wenquan Gu, Dongguo Shao

“…The best IOA-ML model for total phosphorus (TP), total nitrogen (TN), and permanganate index (CODMn) was extreme gradient boosting optimized by genetic algorithm (GA-XGB), while that for dissolved oxygen (DO) and turbidity was categorical boosting regression optimized by GA (GA-CBR). …”
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Evaluation of the Effectiveness of Multiple Machine Learning Methods in Remote Sensing Quantitative Retrieval of Suspended Matter Concentrations: A Case Study of Nansi Lake in Nort... by Xiuyu Liu, Zhen Zhang, Tao Jiang, Xuehua Li, Yanyi Li

“…Then, seven methods such as linear regression, BP neural network (BP), KNN, random forest (RF), and random forest based on genetic algorithm optimization (GA_RF) are used to construct the inversion model of TSM concentration. …”
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Optimization of Irrigation and Fertilization in Maize–Soybean System Based on Coupled Water–Carbon–Nitrogen Interactions by Aizheng Yang, Shuyuan Luo, Yaowen Xu, Pingan Zhang, Zhenyi Sun, Kun Hu, Mo Li

“…A multi-objective optimization model, integrating experimental data and mechanistic insights, was constructed and refined using the NSGA-III genetic algorithm to identify the optimal water and nitrogen application ratios. …”
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Claim Amount Forecasting and Pricing of Automobile Insurance Based on the BP Neural Network by Wenguang Yu, Guofeng Guan, Jingchao Li, Qi Wang, Xiaohan Xie, Yu Zhang, Yujuan Huang, Xinliang Yu, Chaoran Cui

“…This paper uses a genetic algorithm to optimize the structure of the BP neural network at first, and the calculation speed is significantly improved. …”
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Hot deformation physical mechanisms and a unified constitutive model of a solid solution Ti55511 alloy deformed in the two-phase region by Huijie Zhang, Y.C. Lin, Gang Su, Yongfu Xie, Wei Qiu, Ningfu Zeng, Song Zhang, Guicheng Wu

“…Material constants are determined using a genetic algorithm (GA), and the experimental data align well with the predicted data. …”
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Application of Extreme Gradient Boosting Based on Grey Relation Analysis for Prediction of Compressive Strength of Concrete by Liyun Cui, Peiyuan Chen, Liang Wang, Jin Li, Hao Ling

“…Another highlight is that its performance was compared with the frequently used artificial neural network (ANN) and genetic algorithm-artificial neural network (GA-ANN) by using random dataset and the same testing datasets. …”
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Research on Simulation and Performance Optimization of Mach 4 Civil Aircraft Propulsion Concept by Min Chen, Zihao Jia, Hailong Tang, Yi Xiao, Yonghang Yang, Feijia Yin

“…Finally, a multiobjective optimization tool made up of a response surface method and a genetic algorithm was developed to optimize the design parameters and the control law of the TBCC engine, in order to make the Mach 4 supersonic civil aircraft engine with better performance, lower noise, and lower emissions. …”
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Multi-objective optimization of SUS430C steel turning process using hybrid machine learning and evolutionary algorithm approach by Nguyen Van-Canh, Nguyen Anh-Thang, Pham Ngoc-Linh, Nguyen Thuy-Duong

“…A hybrid approach combining Extreme Gradient Boosting (XGBoost) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was employed to optimize three critical machining objectives: surface roughness (Ra), material removal rate (MRR), and tool wear (Vb). …”
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Design and Profit Allocation in Two-Echelon Heterogeneous Cooperative Logistics Network Optimization by Yong Wang, Yingying Yuan, Kevin Assogba, Ke Gong, Haizhong Wang, Maozeng Xu, Yinhai Wang

“…First, a mixed integer linear programing model is introduced to minimize the total operating cost of nonempty coalitions. Thus, the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm are hybridized to propose GA-PSO heuristics. …”
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Exploring the Orca Predation Algorithm for Economic Dispatch Optimization in Power Systems by Vivi Aida Fitria, Arif Nur Afandi, Aripriharta

“…This research shows that Orca Predation Algorithm consistently does better than other bio-inspired algorithms like Particle Swarm Optimization, Whale Optimization Algorithm, Grey Wolf Optimizer, the Bat Algorithm, Genetic Algorithm and Ant Colony Optimization in terms of minimum cost, average cost, and solution stability. …”
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Enhancing Pan evaporation predictions: Accuracy and uncertainty in hybrid machine learning models by Khabat Khosravi, Aitazaz A. Farooque, Amir Naghibi, Salim Heddam, Ahmad Sharafati, Javad Hatamiafkoueieh, Soroush Abolfathi

“…The models investigated include M5 Prime (M5P), M5Rule (M5R), Kstar, as well as their hybridized versions employing Bagging (BA), the adaptive neuro-fuzzy inference system (ANFIS), ANFIS-GA (genetic algorithm), and long short-term memory (LSTM) networks. …”
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Enhancing Campus Mobility: Simulated Multi-Objective Optimization of Electric Vehicle Sharing Systems Within an Intelligent Transportation System Frameworks by Omar S. Aba Hussen, Shaiful J. Hashim, Nasri Sulaiman Member, S.A.R. Alhaddad, Bassam Y. Ribbfors, Masanobu Umeda, Keiichi Katamine

“…A simulation model was developed in MATLAB, utilizing the Non-dominated Sorting Genetic Algorithm (NSGA-II), a powerful multi-objective optimization technique that balances conflicting objectives to achieve the best trade-offs for operational efficiency. …”
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An efficient binary spider wasp optimizer for multi-dimensional knapsack instances: experimental validation and analysis by Mohamed Abdel-Basset, Reda Mohamed, Karam M. Sallam, Ibrahim Alrashdi, Ibrahim A. Hameed

“…The experimental findings demonstrate that BSWO-RO4 can achieve exceptional results for the small and medium-scale instances, while the genetic algorithm integrated with RO4 can be superior for the large-scale instances. …”
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Construction and application of a physically-based constitutive model for superplastic deformation of near-α TNW700 titanium alloy by Lixia Ma, Dingyong He, Bangjian Yang, Xiuquan Han, Jichun Zhang, Weidong Li

“…Material constants are calibrated using a genetic algorithm combined with multi-objective optimization. …”
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