Sperm swarm optimization for many objective power flow problems with enhanced performance evaluation in power systems by Wulfran Fendzi Mbasso, Ambe Harrison, Pradeep Jangir, Idriss Dagal, Hossam Kotb, Njimboh Henry Alombah, Raman Kumar, Aseel Smerat, Emmanuel Fendzi Donfack, Saad F. Al-Gahtani, Z. M. S. Elbarbary

“…Abstract This research presents an advanced optimization framework motivated from biological sources using the Sperm Swarm Optimization (SSO) algorithm to specifically deal with the Many-Objective Optimal Power Flow (MaO-OPF) problem in power systems. …”
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A Deep Learning-Based Framework for Bearing RUL Prediction to Optimize Laser Shock Peening Remanufacturing by Yuchen Liang, Yuqi Wang, Anping Li, Chengyi Gu, Jie Tang, Xianjuan Pang

“…The fruit fly optimization (FFO) algorithm was employed to optimize the remanufacturing parameters; a 29.33% improvement was achieved in fitness compared to the baseline. (3) The DNN model predictions were validated against Finite Element Analysis (FEA) simulations, with a low relative error of 2.5% to 5.8%; the model showed good accuracy in capturing the effects of optimized LSP parameters on bearing life extension.…”
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Optimizing precision farming: enhancing machine learning efficiency with robust regression techniques in high-dimensional data by Nour Hamad Abu Afouna, Majid Khan Majahar Ali

“…To overcome these obstacles, reducing retraining time and resolving the complexity issue is essential for improving the machine learning algorithm’s performance, scalability, and efficiency, especially when dealing with large or high-dimensional datasets. …”
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Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes by Zhaoyang Wang, Shuo Wang, Damien Ernst, Chenguang Xiao

“…Then, these surrogate models with prior optimization knowledge are combined with the Expected Hypervolume Improvement (EHVI) acquisition function in a Bayesian optimization framework to efficiently discover Pareto-optimal configurations for the target task, which enables AutoCIL-FMOBO to jointly optimize key components, such as resampling methods, classifiers, and their hyperparameters, under a multi-objective setting. …”
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GRADIENT DESCENT METHOD AND PARAMETER SELECTION FOR IMAGE RESTORATION PROBLEM by Nguyen Dinh Dung

“…Image restoration is often considered one of the data processing steps before the training process for machine learning models is performed. Image restoration problems are often solved by iterative algorithms, where the choice of iteration parameters plays an important role in improving the algorithm's convergence rate. …”
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Optimizing Random Forest Parameters with Hyperparameter Tuning for Classifying School-Age KIP Eligibility in West Java by Silfiana Lis Setyowati, Asyifah Qalbi, Rafika Aristawidya, Bagus Sartono, Aulia Rizki Firdawanti

“…Random Forest is an ensemble learning algorithm that combines multiple decision trees to generate a more stable and accurate classification model. …”
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Optimization of Hand Gesture Object Detection Using Fine-Tuning Techniques on an Integrated Service of Smart Robot by Faikul Umam, Hanifudin Sukri, Ach Dafid, Firman Maolana, Mycel Natalis Stopper Ndruru

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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. …”
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Artificial Intelligence-Based Tools for Process Optimization: Case Study—Bromocresol Green Decolorization with Active Carbon by Gabriel Dan Suditu, Elena Niculina Drăgoi, Alexandra Georgiana Apostică, Andra Maria Mănăilă, Veronica Mădălina Radu, Adrian Cătălin Puițel, Mircea Teodor Nechita

“…The study emphasizes that adsorption on active carbon is an effective method for bromocresol green decolorization in wastewater that can be further improved using advanced optimization methods.…”
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Multi-objective optimization of the heating oil circuit inside the calendering roller for the lithium battery pole piece by Shuangqiu Sun, Junqiang Wang, Rongying Zhang, Zhenchao Si, Zhijie Yang

“…Then, the improved NSGA-II algorithm is selected to execute the optimization loop. …”
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Automatic Detection and Classification of Dental Anomalies and Tooth Types Using Transformer-Based Yolo With GA Optimization by Sanabam Bineshwor Singh, Anuradha Laishram, Khelchandra Thongam, Khumanthem Manglem Singh

“…In addition, the system employs Genetic Algorithm (GA) optimization for hyperparameter tuning, which fine-tunes model parameters to maximize performance metrics and enhance accuracy and robustness in dental diagnostics. …”
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Method and Optimization of Key Parameters of Soil Organic Matter Detection Based on Pyrolysis Coupled with Artificial Olfaction by Mingwei Li, Xiao Li, Xuexun Li, Wenjun Wang, Yulong Chen, Long Zhou, Xiaomeng Xia

“…Finally, the Back-Propagation Neural Network (BPNN) and Partial Least-Squares Regression (PLSR) algorithms were used to establish an SOM prediction model after obtaining soil pyrolysis gases under the optimal combination of pyrolysis parameters. …”
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Optimal Pre-disaster and Post-disaster Scheduling of Mobile Energy Storage Considering the Influence of Transportation Network by XIE Peikun, LI Liang, SHI Yuanjie, SHENG Qing, LI Zhenkun

“…Following the disaster， a dynamic optimization scheduling model of the MES was developed for determine the optimal dynamic scheduling scheme of the MES. …”
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Explainable AI-Based Skin Cancer Detection Using CNN, Particle Swarm Optimization and Machine Learning by Syed Adil Hussain Shah, Syed Taimoor Hussain Shah, Roa’a Khaled, Andrea Buccoliero, Syed Baqir Hussain Shah, Angelo Di Terlizzi, Giacomo Di Benedetto, Marco Agostino Deriu

“…To address these limitations, this study proposes a comprehensive pipeline combining transfer learning, feature selection, and machine-learning algorithms to improve detection accuracy. Multiple pretrained CNN models were evaluated, with Xception emerging as the optimal choice for its balance of computational efficiency and performance. …”
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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

“…However, despite this promise, translation into clinical settings remains difficult due to regulatory hurdles, scalability issues, and inconsistent reproducibility in human models. At the same time, artificial intelligence (AI), with its powerful algorithms for data analysis and predictive modeling, is transforming how we design, evaluate, and monitor advanced therapies, including the optimization of manufacturing processes. …”
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Optimization and prediction of corporate credit rating through advanced feature selection based on AI and deep learning by Jumanah Ahmed Darwish

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Optimization of MXene-based aqueous ionic liquids for solar systems using conventional and AI-based techniques by Mohamed Bechir Ben Hamida, Ali B. M. Ali, Narinderjit Singh Sawaran Singh, Loghman Mostafa

“…Response surface methodology (RSM) is used for predictive modeling, while enhanced hill climbing (EHC), non-dominated sorting genetic algorithm II (NSGA-II), and the multi-objective generalized normal distribution optimizer (MOGNDO) are applied for multi-objective optimization. …”
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CFD-based optimization of dynamic cyclones with variable vortex length using GMDH artificial neural network by Hamed Safikhani, Somayeh Davoodabadi Farahani, Lakhbir Singh Brar, Faroogh Esmaeili

“…The final step involves optimizing the cyclone designs through the non-dominated sorting genetic algorithm (NSGA). …”
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Route Optimization of Hazardous Material Railway Transportation Based on Conditional Value-at-Risk Considering Risk Equity by Liping Liu, Shilei Sun, Shuxia Li

“…Findings also show that direct transportation improves risk equity over transfer-based routes, highlighting the importance of strategic route planning. …”
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A binary gridding path-planning method for plant-protecting UAVs on irregular fields by Wang-ying XU, Xiao-bing YU, Xin-yu XUE

“…In this study, we proposed a binarization multi-objective model for the irregular field area, specifically an improved non-dominated sorting genetic algorithm–II based on the knee point and plane measurement (KPPM-NSGA-ii). …”
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