Analysis of a nonsteroidal anti inflammatory drug solubility in green solvent via developing robust models based on machine learning technique by Lijie Jiang, Qi Li, Huiqing Liao, Hourong Liu, Bowen Tan

“…Abstract This study develops and evaluates advanced hybrid machine learning models—ADA-ARD (AdaBoost on ARD Regression), ADA-BRR (AdaBoost on Bayesian Ridge Regression), and ADA-GPR (AdaBoost on Gaussian Process Regression)—optimized via the Black Widow Optimization Algorithm (BWOA) to predict the density of supercritical carbon dioxide (SC-CO2) and the solubility of niflumic acid, critical for pharmaceutical processes. …”
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Long-term comparative analysis of machine learning models: A deep dive into applications of artificial intelligence for enhancing photovoltaic performance prediction by Ali Akbar Yaghoubi, Mahdi Gandomzadeh, Aslan Gholami, Roghayeh Gavagsaz-Ghoachani, Majid Zandi

“…This study tackles a key research gap by applying comparative analysis on several well-known classic machine learning models to predict photovoltaic performance under variable environmental conditions and dust levels. …”
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Exploring explainable machine learning algorithms to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023 by Mequannent Sharew Melaku, Nebebe Demis Baykemagn, Lamrot Yohannes, Adem Tsegaw Zegeye

“…Hyperparameter optimization was performed using Randomized Search with tenfold cross-validation, enhancing model performance. …”
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Integrative Machine Learning, Virtual Screening, and Molecular Modeling for BacA-Targeted Anti-Biofilm Drug Discovery Against Staphylococcal Infections by Ahmad Almatroudi

“…This study investigates the application of machine learning models to identify potential phytochemical inhibitors against BacA, a target related to Staphylococcal infections. …”
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A Computational Intelligence Framework Integrating Data Augmentation and Meta-Heuristic Optimization Algorithms for Enhanced Hybrid Nanofluid Density Prediction Through Machine and... by Priya Mathur, Hammad Shaikh, Farhan Sheth, Dheeraj Kumar, Amit Kumar Gupta

“…The research analyzed fourteen predictive models, employing advanced hyperparameter optimization methods facilitated by Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). …”
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Interpretable Machine Learning for High-Accuracy Reservoir Temperature Prediction in Geothermal Energy Systems by Mohammadali Ahmadi

“…Accurate prediction of reservoir temperature is critical for optimizing geothermal energy systems, yet the complexity of geothermal data poses significant challenges for traditional modeling approaches. …”
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Comprehensive assessment and energetic-exergetic performance optimization of a new solar thermal electricity system based on Scheffler-type receivers combined with screw-type volum... by Paolo Iodice, Amedeo Amoresano, Giuseppe Langella, Francesco Saverio Marra

“…For this purpose, specific numerical models and basic criteria fixed for the screw expanders and Scheffler receivers part-load behavior are combined with thermodynamic formulations established for energetic-exergetic performance optimization of the entire solar thermal electricity plant. …”
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Prediction of true critical temperature and pressure of binary hydrocarbon mixtures: A Comparison between the artificial neural networks and the support vector machine by M. Etebarian, k. movagharnejad

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Development of hybrid computational model for simulation of heat transfer and temperature prediction in chemical reactors by Kamal Y. Thajudeen, Mohammed Muqtader Ahmed, Saad Ali Alshehri

“…The model is hybrid by combining heat transfer and machine learning in simulation of the process. …”
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Performance Comparison of Genomic Best Linear Unbiased Prediction and Four Machine Learning Models for Estimating Genomic Breeding Values in Working Dogs by Joseph A. Thorsrud, Katy M. Evans, Kyle C. Quigley, Krishnamoorthy Srikanth, Heather J. Huson

“…This study investigates the efficacy of various genomic prediction models—Genomic Best Linear Unbiased Prediction (GBLUP), Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGB), and Multilayer Perceptron (MLP)—in predicting genomic breeding values (gEBVs). …”
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Emerging Trends in the Integrating Remote Sensing and Machine Learning for Groundwater Resources Management: A Bibliometric Study by Abolfazl Akbarpour, Moein Tosan, Raziyeh Shamshirgaran

“…This convergence will pave the way for developing more reliable prediction models, accurate uncertainty analysis, and the provision of optimal groundwater resources management solutions under various climatic and land-use scenarios. …”
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Performance assessment and optimization of Ti6Al4V helical hole milling process by Gururaj Bolar, Vikas Marakini, Raviraj Shetty, Sawan Shetty, Adithya Hegde

“…Moreover, for dry helical milling of Ti6Al4V alloy, a 75 m min ^−1 cutting speed, tangential feed of 0.03 mm z ^−1 , and axial feed of 0.2 mm rev ^−1 were determined as the optimal setting for achieving lower TF, RF, MT, and Sr The findings show that the proposed predictive models and optimization technique can achieve the best outcomes when machining difficult-to-machine material like Ti6Al4V alloy.…”
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Risk prediction of hyperuricemia based on particle swarm fusion machine learning solely dependent on routine blood tests by Min Fang, Chengjie Pan, Xiaoyi Yu, Wenjuan Li, Ben Wang, Huajian Zhou, Zhenying Xu, Genyuan Yang

“…Subsequently, a risk prediction model is constructed based on the parameter optimization of five machine learning models using the PSO algorithm. …”
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A novel cascade heat integration configuration for electricity/freshwater/hydrogen outputs using SOFC-GT, multi-effect desalination, and PEM electrolysis using machine learning opt... by Zhaoyang Zuo, Junhua Wang, Sarminah Samad, Nashwan Adnan Othman, Ahmad Almadhor, Raymond Ghandour, Ibrahim A. Alsayer, Dilsora Abduvalieva, Salem Alkhalaf, Samah G. Babiker

“…Hence, a real-time machine learning framework is implemented to optimize key operational parameters dynamically, ensuring efficient fuel utilization, energy distribution, and load balancing across the system. …”
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Hybrid Models for Forecasting Allocative Localization Error in Wireless Sensor Networks by Guo Li, Hongyu Sheng

“…The approach utilizes Radial Basis Function (RBF) models enhanced with advanced optimization algorithms, including Coot Optimization Algorithm (COA), Smell Agent Optimization (SAO), and Northern Goshawk Optimization (NGO) to improve ALE prediction accuracy. …”
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Predicting periprosthetic joint infection in primary total knee arthroplasty: a machine learning model integrating preoperative and perioperative risk factors by Yuk Yee Chong, Chun Man Lawrence Lau, Tianshu Jiang, Chunyi Wen, Jiang Zhang, Amy Cheung, Michelle Hilda Luk, Ka Chun Thomas Leung, Man Hong Cheung, Henry Fu, Kwong Yuen Chiu, Ping Keung Chan

“…Six of them were selected after univariate and multivariate analysis. Five machine learning models were trained with stratified 10-fold cross-validation and assessed by discrimination and calibration analysis to determine the optimal predictive model. …”
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Among Artificial Intelligence/Machine Learning Methods, Automated Gradient-Boosting Models Accurately Score Intraoral Plaque in Non-Standardized Images by Eric Coy, William Santo, Bonnie Jue, Helen Betts, Francisco Ramos-Gomez, Stuart A. Gansky

“…Models were tuned with 80:20 train:test split, stratified 5-fold cross-validation (5-CV) (unstratified in regression models), and hyperparameter optimization. …”
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A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI. by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md Mehedi Hassan

“…Moreover, to enhance the efficacy of the predictions made by hyperparameter-optimized machine learning models, an ensemble model is proposed using a stacking classifier. …”
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Simulation and optimization of CNC cylindrical grinder Performance based on equivalent analysis of joints spring-damping characteristics by Qi Mingzheng, Wang Han, Sun Xizhi, Li Tianjian, Guo Yang, Wu Tao

“…This paper focuses on the MKE1620A CNC cylindrical grinder, using an equivalent analysis of the joint spring-damping characteristics to investigate the overall performance of the grinder and propose directions for design optimization. A total of 168 spring-damper elements were established to model the fixed, movable, and bearing joints. …”
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A New Maintenance Optimization Model Based on Three-Stage Time Delay for Series Intelligent System with Intermediate Buffer by Xiaolei Lv, Qinming Liu, Zhinan Li, Yifan Dong, Tangbin Xia, Xiang Chen

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