Shuffled Puma Optimizer for Parameter Extraction and Sensitivity Analysis in Photovoltaic Models by En-Jui Liu, Rou-Wen Chen, Qing-An Wang, Wan-Ling Lu

“…To address this challenge, a novel metaheuristic algorithm called shuffled puma optimizer (SPO) is deployed to perform parameter extraction and optimal configuration identification across four PV models. …”
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Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorith... by Mojgan Bordbar, Khabat Khosravi, Changhyun Jun, Dongkyun Kim, Sayed M Bateni, Mahmood Safarzadeh, Hamid Kardan Moghaddam, Shohreh Azizi

“…The LSTM model was optimized using the particle swarm optimizer (PSO) and equilibrium optimizer (EO) metaheuristic algorithms. …”
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An Improved LEACH Protocol for Optimizing Cluster Head Selection and In-cluster Selection by SHIBing, GAOZelin, SUNYueping, HUANJuan, SUNTao

“…This protocol initially employs the root mean square (RMS) of distance within the energy consumption model to determine the optimal number of cluster heads. …”
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Wind energy resource assessment based on joint wolf pack intelligent optimization algorithm. by Jiayuan Wang

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Optimization model of electricity metering management based on MOPSO by Sheng Li, Xiaodan Zhou

“…Abstract In response to the difficulty of balancing economy and accuracy in traditional energy metering management methods, an improved particle swarm optimization model is designed to optimize energy metering management based on multi-objective particle swarm optimization, thereby achieving optimal resource allocation and maximizing management efficiency. …”
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RELIABILITY OPTIMIZATION DESIGN ON SHEARER’S RANGING ARM GEAR TRANSMISSION SYSTEM by LI FengJiang, ZHANG Jie, LIAO YingHua, LI QingChen

“…In the process of design shearer ’s ranging arm gear transmission system,by using the method of reliability design theory,derived gear strength and stress assumed to obey normal distribution when tooth surface contact fatigue strength and tooth root bending fatigue strength were taken as constraint conditions,and the volume of gear system as objective function,then genetic algorithm optimization toolbox of MATLAB was used to solve the optimization mathematic model. …”
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Structural Optimization-Based Enhancement of the Dynamic Performance for Horizontal Axis Wind Turbine Blade by Ahmed Zarzoor, Alaa Jaber, Ahmed Shandookh

“…It employs a complex optimization framework that combines aerodynamics and structural analysis via MATLAB and a genetic algorithm. …”
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Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements by Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen

“…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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Optimization of air conditioning mechanical ventilation using simulated annealing for enhanced energy efficiency and cost reduction by Enio Pedone Bandarra Filho, Gleyzer Martins, Muhammad Bilal Riaz, Sardar Muhammad Bilal, Oscar Saul Hernandez Mendonza

“…The methodology integrates principles of fluid mechanics with computational modeling to perform mass and pressure balances, combined with a simulated annealing algorithm for system optimization. The results demonstrate notable reductions in energy consumption, installation costs, and root mean square deviation of airflow rates from design targets. …”
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Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line by Sahatsawat Wainiphithapong, Chana Phutthananon, Sompote Youwai, Pitthaya Jamsawang, Phattarawan Malaisree, Ochok Duangsano, Pornkasem Jongpradist

“…This integrated framework, which combines the non-dominated sorting genetic algorithm (NSGA-II) with LSTM neural networks, is applied to MOO to identify the optimal SOPs, while accounting for their influence on S variation as a time-series over 11 timesteps, as considered in this study. …”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…Results demonstrate that the CNN-LSTM-BMO achieves superior performance with the lowest Root Mean Square Error (RMSE) of 0.5523 and highest R² value of 0.9435, showing statistically significant improvements over other optimization methods as confirmed by paired t-tests (P < 0.05). …”
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Research on rock strength prediction model based on machine learning algorithm by Xiang Ding, Mengyun Dong, Wanqing Shen

“…By selecting different features, the optimal feature combination for predicting rock compressive strength was obtained, and the optimal parameters for different models were obtained through the Sparrow Search Algorithm (SSA). …”
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Identification of soil texture and color using machine learning algorithms and satellite imagery by Jiyang Wang

“…For future research, it is recommended to explore the combination of SVR with optimization techniques such as genetic algorithms to further improve the accuracy of soil texture and color predictions.…”
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Visual SLAM algorithm for underground robots in coal mines based on point-line features by Li WANG, Tianxiang ZANG, Bo SU

“…Therefore, a binocular vision localization algorithm SL-SLAM for underground mobile robots in coal mines based on the improved ORB (Oriented Fast and Rotated Brief)-SLAM3 algorithm is proposed. …”
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Application of deep reinforcement learning in parameter optimization and refinement of turbulence models by Zhan Zhang

“…The aim of this study is to improve the accuracy of simulations by optimizing turbulence model parameters, in order to address the cost and time limitations of traditional wind tunnel tests and on-site measurements. …”
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Advancing sustainable renewable energy: XGBoost algorithm for the prediction of water yield in hemispherical solar stills by Salwa Ahmad Sarow, Hasan Abbas Flayyih, Maryam Bazerkan, Luttfi A. Al-Haddad, Zainab T. Al-Sharify, Ahmed Ali Farhan Ogaili

“…Initially explored was the effect of different sand types and bed heights on HSS performance, with the findings indicating that black sand, especially at a height of 1 cm combined with reflectors and a fan, markedly improved efficiency and production. An economic analysis revealed a significant reduction in water treatment costs with the optimized system. …”
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Forecasting Wind Farm Production in the Short, Medium, and Long Terms Using Various Machine Learning Algorithms by Gökhan Ekinci, Harun Kemal Ozturk

“…These findings provide practical insights for optimizing wind energy forecasting models, which can improve energy trading strategies, enhance grid stability, and support informed decision making in renewable energy investments. …”
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Technique on Vehicle Damage Assessment After Collisions Using Optical Radar Technology and Iterative Closest Point Algorithm by Shih-Lin Lin, Yi-Hsuan Chen

“…The contributions of this study lie in integrating LiDAR technology with advanced point cloud processing algorithms and a deep learning optimization model for vehicle damage assessment, demonstrating high precision and cost-effectiveness. …”
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Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems by Lihui Zheng, Xu Fan, Zongshan Kang, Xinjun Jin, Wenchao Zheng, Xiaofen Fang

“…The optimized VToMe-BiGRU algorithm combines the Transformer model and the BiGRU network, which effectively captures the critical features in the electric drive system data, thus improving the fault prediction performance. …”
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Enhancing Sustainable Manufacturing in Industry 4.0: A Zero-Defect Approach Leveraging Effective Dynamic Quality Factors by Rouhollah Khakpour, Ahmad Ebrahimi, Seyed Mohammad Seyed Hosseini

“…The empirical insights, drawn from the real-life case study of this research, indicate the challenges and complexities that arise in the path of achieving zero defect product and sustainability improvement. The extended view on effective root causes of product quality and the focus on improving TBL sustainability criteria in this research as well as its analytical approach offer practitioners valuable insights for improving their ZDM approaches in a more comprehensive way. …”
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