Optimizing Locations of Primary Schools in Rural Areas of China by Yulong Chen

“…Finally, a practical case study was used to illustrate the application of the proposed mathematical model. The results showed that the traffic network has an important influence on the optimization location of rural schools, and the improvement of traffic network conditions can greatly reduce the time required for students to travel to school.…”
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Optimal distributed generation placement and sizing using modified grey wolf optimization and ETAP for power system performance enhancement and protection adaptation by Nasreddine Bouchikhi, Fethi Boussadia, Riyadh Bouddou, Ayodeji Olalekan Salau, Saad Mekhilef, Chaima Gouder, Sarra Adiche, Abdallah Belabbes

“…The MGWO algorithm is an improved version of the conventional GWO algorithm, which is based on a hierarchical model inspired by the social behavior of grey wolves. …”
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Sustainable closed-loop supply chain network design: heuristic hybrid approach with considering inflation and carbon emission policies by Saeid Kalantari, Hamed Kazemipoor, Farzad Movahedi Sobhani, Seyyed Mohammad Hadji Molana

“…Also, due to the complexity of the model and its multi-objective, a new combined method of Heuristic algorithm (HA) and Multi-Choice Goal Programming with Utility Function (MCGP-UF) is used. …”
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Research progress in globular fruit picking recognition algorithm based on deep learning by LI Hui, ZHANG Jun, YU Shuochen, LI Zhixin

“…It is required to enhance data processing, improve model generalization by preprocessing and synthesizing data, and optimize model adaptability in changing environments. …”
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Optimizing power network expansion with pumped hydro energy storage using a multi-objective enhanced spider wasp optimizer approach by Mohamed M. Refaat, Saad F. Al-Gahtani, Hussain Bassi, Ziad M. Ali, Shady H. E. Abdel Aleem

“…The problem is framed as a comprehensive multi-objective optimization model designed to minimize the cost of network expansion while maximizing the benefits of integrating various PHES technologies. …”
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Performance of machine learning algorithms to evaluate the physico-mechanical properties of nanoparticle panels by Derrick Mirindi, James Hunter, David Sinkhonde, Tajebe Bezabih, Frederic Mirindi

“…This review analyzes secondary data on nanoparticle integration in board production, aiming to evaluate the relationships among physical (water absorption (WA) and thickness swelling (TS)) and mechanical (modulus of rupture (MOR), modulus of elasticity (MOE); and internal bond (IB) strength) properties and to predict performance using machine learning (ML) algorithms. These algorithms include Pearson correlation, hierarchical clustering, and decision tree (DT) models. …”
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Research of Online Error Prediction and Parallel Algorithm for Voltage Transformer in Smart Grid by Xin Xianfeng, Chen Rongye, Lin Cong, Liu Qingchan, He Zhaolei, Li Tengbin, Yang Guangrun, Kochan Orest, Karpa Mykhailo

“…This article mainly focuses on the online error prediction and the parallelization method of voltage transformers. First, an optimized multi-layer perceptron model based on the sparrow search algorithm (SSA) is proposed. …”
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Combined use of near infrared spectroscopy and chemometrics for the simultaneous detection of multiple illicit additions in wheat flour by Xinyi Dong, Ying Dong, Jinming Liu, Siting Wu

“…Compared to regression models built with competitive adaptive reweighted sampling and genetic algorithm for feature wavelength selection, the performance improved significantly, enhancing generalization capability. …”
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A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling by Ruochen Liu, Chenlin Ma, Wenping Ma, Yangyang Li

“…The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. …”
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Artificial Intelligence Algorithms for Hybrid Electric Powertrain System Control: A Review by Dawei Zhong, Bolan Liu, Liang Liu, Wenhao Fan, Jingxian Tang

“…In recent years, artificial intelligence algorithms have provided new solutions for the intelligent control of hybrid electric powertrain systems with their powerful nonlinear modeling capabilities, data-driven optimization, and adaptive learning capabilities. …”
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Anomaly detection using unsupervised machine learning algorithms: A simulation study by Edmund Fosu Agyemang

“…Future work should explore parameter optimization, the impact of dataset characteristics on model performance, and the application of these models to real-world datasets to validate their efficacy in practical anomaly detection scenarios.…”
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Defense Methods for Adversarial Attacks Against Power CPS Data-Driven Algorithms by Weiping ZHU, Yi TANG, Xingshen WEI, Zengji LIU

“…In response to the potential adversarial attacks on data-driven algorithms in power CPS, this paper proposes corresponding defense methods from such three aspects as abnormal data filtering and recovery, algorithm vulnerability mining and optimization, and algorithm self interpretability improvement: abnormal data filter, GAN-based vulnerability mining and optimization method, data knowledge fusion model and its training method. …”
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Optimal Integration of Multiple Shunt Reactive Compensators in Radial Distribution Systems for Loss Reduction using Modified Mountain Gazelle Optimizer (MMGO) by A. F. S. Yussif, E. Twumasi, E. A. Frimpong

“…This approach reduces the search space and improves the efficiency of the optimization process. …”
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Simulation of automatic intrusion detection in university networks by using neural network algorithms by Houdun Xu

“…Using appropriate training methods and optimization algorithms, train and optimize the neural network model to achieve high accuracy and robustness. …”
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Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

“…The ensemble learning algorithm combines multiple prediction models to improve the prediction accuracy and stability. …”
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Machine learning to improve HIV screening using routine data in Kenya by Jonathan D. Friedman, Jonathan M. Mwangi, Kennedy J. Muthoka, Benedette A. Otieno, Jacob O. Odhiambo, Frederick O. Miruka, Lilly M. Nyagah, Pascal M. Mwele, Edmon O. Obat, Gonza O. Omoro, Margaret M. Ndisha, Davies O. Kimanga

“…We generated a stratified 60‐20‐20 train‐validate‐test split to assess model generalizability. We trained four machine learning algorithms including logistic regression, Random Forest, AdaBoost and XGBoost. …”
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Application of Particle Swarm Algorithm in Nanoscale Damage Detection and Identification of Steel Structure by Ying Zhang

“…Second, two test functions are used to compare and analyze, which shows that the improved particle swarm algorithm has better optimization performance. …”
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Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database by Hongyi Chen, Haiyang Song, Hongyu Huang, Xiaojun Fang, Huang Chen, Qingqing Yang, Junyu Zhang, Wenjun Ding, Zheng Gong, Jun Ke

“…To address class imbalance, we implemented feature engineering with SMOTE and under-sampling techniques. Model optimization was performed via Bayesian hyperparameter tuning. …”
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Train adaptive energy saving strategy based on iterative induced genetic algorithm by MEI Wenqing, SHI Ke, ZHANG Zhengfang

“…Then, to overcome the difficulty of traditional genetic algorithms in solving continuous sub-interval optimization problems due to discrete independence, an iterative induced genetic algorithm was designed to calculate the Pareto optimal solution set for the energy-saving objective function. …”
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The necessity of the Black Sea region transport structure improvement by L.V. Nazarova

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