Prediction of heat transfer in a rotor-stator cavity cooled by multiple jets: Integration of CFD models and machine learning for performance optimization by Abdellatif EL hannaoui, Rachid Boutarfa

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Optimization and modeling of sulfur removal from liquid fuel using carbon-based adsorbents through synergistic application of RSM and machine learning by Karim Maghfour Sarkarabad, Mohsen Shayanmehr, Ahad Ghaemi

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Quantifying optimal inner limiting membrane peeling in macular hole surgery: a machine learning framework for predictive modeling and schematic visualization by Xiang Zhang, Hongjie Ma, Song Lin, Ledong Zhao, Lu Chen, Zetong Nie, Zhaoxiong Wang, Chang Liu, Xiaorong Li, Wenbo Li, Bojie Hu

“…Abstract Purpose Internal limiting membrane (ILM) peeling in macular hole (MH) surgery is critical but challenging, and current practices lack standardized tools for quantifying and visualizing optimal peeling dimensions.This study aimed to develop a machine learning framework to recommend surgeon-specific ILM peeling radius during macular hole surgery, integrating predictive modeling with schematic visualization to guide operative planning. …”
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Editorial Note: Machine learning model for predicting the optimal depth of tracheal tube insertion in pediatric patients: A retrospective cohort study

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Optimizing chickpea yield prediction under wilt disease through synergistic integration of biophysical and image parameters using machine learning models by RN Singh, P. Krishnan, C. Bharadwaj, Sonam Sah, B. Das

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A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization by Songping He, Xiangxi Li, Fangyu Peng, Jiazhi Liao, Xia Lu, Hui Guo, Xin Tan, Yanyan Chen

“…Finally, five kinds of machine learning methods, random forest, extreme gradient boosting, light gradient boosting machine, linear support vector classifier and support vector machine, were used to establish classification prediction models, and error-correcting output codes were used to optimize each model. …”
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Optimizing Machine Learning Models with Data-level Approximate Computing: The Role of Diverse Sampling, Precision Scaling, Quantization and Feature Selection Strategies by Ayad M. Dalloo, Amjad J. Humaidi

“…This paper investigates the application of approximate computing techniques as a viable solution to reduce computational complexity and optimize machine learning models, focusing on two widely used supervised machine learning models: k-nearest neighbors (KNN) and support vector machines (SVM). …”
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Unveiling the optimal factor model in Pakistan: a machine learning approach using support vector regression and extreme gradient boosting algorithms by Rizwan Ullah, Muhammad Naveed Jan, Muhammad Tahir

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Exergy efficiency optimization of a water-based titanium dioxide nanofluid hybrid solar collector using advanced machine learning models by Poyyamozhi Natesan, M.P. Rajakumar, Sreevidya R C, Srimanickam B, Suresh Vellaiyan, Nguyen Van Minh

“…This study investigates the exergy efficiency of a hybrid solar collector using water and water-based titanium dioxide (TiO2) nanofluids, employing advanced machine learning (ML) models to optimize performance evaluation. …”
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Analysis of Weak Links in the Mechanized Mining of Underground Metal Mines: Insights from Machine Learning and SHAP Explainability Models by Chengye Yang, Keping Zhou, Jielin Li

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Machine learning and optimization in hybrid energy storage systems: Integrating MPC, PSO, MILP, and ANN for grid stability and efficiency by Rajesh M. Bhagat, Dilendra B. Jasutkar, Amitkumar B. Ranit, Vikrant S. Vairagade, Balram Yelamasetti, Sagar D. Shelare, Shubham Sharma, Abinash Mahapatro, V.K. Bupesh Raja, Quadri Noorulhasan Naveed, Naoufel Kraiem, Saiful Islam, Jasmina Lozanovic

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A novel prediction of the PV system output current based on integration of optimized hyperparameters of multi-layer neural networks and polynomial regression models by Hussein Mohammed Ridha, Hashim Hizam, Seyedali Mirjalili, Mohammad Lutfi Othman, Mohammad Effendy Ya’acob, Noor Izzri Bin Abdul Wahab, Masoud Ahmadipour

Subjects: “…PV model…”
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Dynamic Pricing Models in E-Commerce: Exploring Machine Learning Techniques to Balance Profitability and Customer Satisfaction by Xiaochen Guo, Lei Zhang

“…Future work may explore hybrid models and multi-objective optimization techniques to further refine these models.…”
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Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples by Abdullahi G. Usman, Sagiru Mati, Hanita Daud, Ahmad Abubakar Suleiman, Sani I. Abba, Hijaz Ahmad, Taha Radwan

“…This study proposed the use of a support vector regression (SVR) predictive model improved by two metaheuristic algorithms used for optimization namely, Harris Hawks Optimization (HHO) and Particle Swarm Optimization (PSO) to predict chromatographic retention time of various food mycotoxin groups. …”
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Acoustic modelling of machines using the inversion method for the purposes of the acoustic assessment of machines by Dariusz PLEBAN

“…Issues related to the development of acoustic models of machines are important factors both in the design of low-noise machines and in the prediction of machines noise. …”
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Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning by Shijin Li, Fucai Wang

“…Extreme Learning Machine (ELM) algorithm model is introduced to accelerate Improved Gray Wolf Optimization (IGWO) optimization and improve convergence speed. …”
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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…Grid search optimization was employed to fine-tune the hyperparameters of each model, while model evaluation was conducted using 10-fold cross-validation and six performance metrics. …”
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Optimization of heat and mass transfer in chemically radiative nanofluids using Cattaneo-Christov fluxes and advanced machine learning techniques by Shazia Habib, Saleem Nasir, Zeeshan Khan, Abdallah S. Berrouk, Waseem Khan, Saeed Islam

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Best practices for developing microbiome-based disease diagnostic classifiers through machine learning by Peikun Li, Min Li, Wei-Hua Chen

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Efficient Short-Term Wind Power Prediction Using a Novel Hybrid Machine Learning Model: LOFVT-OVMD-INGO-LSSVR by Zhouning Wei, Duo Zhao

“…The proposed model was compared with traditional machine learning models, deep learning models, and other hybrid models. …”
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