Can digital economy improve urban ecological development? evidence based on double machine learning analysis by Yuchen Jiang, Lei Li, Yue Xu

“…Additionally, traditional causal inference models encounter several challenges, such as model misspecification and the “curse of dimensionality.” …”
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Integrating artificial intelligence for sustainable waste management: Insights from machine learning and deep learning by Son V.T. Dao, Tuan M. Le, Hieu M. Tran, Hung V. Pham, Minh T. Vu, Tuan Chu

“…By automating processes such as waste classification, sorting, and transportation, AI-driven models have the potential to optimize operational efficiency and reduce environmental impact. …”
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Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model by Shengli Wang, Xiaolong Guo, Tianle Sun, Lihui Xu, Jinfeng Zhu, Zhicai Li, Jinjiang Zhang

“…The model’s hyperparameters are optimized using the IDBO. …”
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Class-aware contrastive optimization for imbalanced text classification by Grigorii Khvatskii, Nuno Moniz, Khoa D. Doan, Nitesh V. Chawla

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Integrating explainable artificial intelligence and light gradient boosting machine for glioma grading by Teuku Rizky Noviandy, Ghalieb Mutig Idroes, Irsan Hardi

“…Results: The optimized LightGBM model demonstrated exceptional performance, achieving an overall accuracy of 89.88 %, which surpassed the other compared ML models. …”
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Optimization and Torque Improvement of a Salient-Pole Permanent Magnet Synchronous Machine by Three-step Skewed Pole Shoe Method by Hossein Parivar, Ahmad Darabi

“…The simulation results ensure the electromagnetic performance of the initial model of the machine under any operating conditions. …”
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Pharmacist-led surgical medicines prescription optimization and prediction service improves patient outcomes - a machine learning based study by Xianlin Li, Xianlin Li, Xiunan Yue, Lan Zhang, Xiaojun Zheng, Nan Shang

“…To enhance medication safety and improve patient outcomes by introducing a machine learning (ML)-based warning model integrated into a pharmacist-led Surgical Medicines Prescription Optimization and Prediction (SMPOP) serviceMethodA retrospective cohort design with a prospective implementation phase was used in a tertiary hospital. …”
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Calibration of Electron Microscopes Through Deep Learning and Bayesian Optimization by Jilles S. van Hulst, Roy A. C. van Zuijlen, Narges Javaheri, Maurits Diephuis, Duarte J. Antunes, W. P. M. H. Heemels

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Applying a Machine Learning Method to Detect Changing Neuronal Activity in Seizure Disorders by Cengiz Gunay, Krishan Bhalsod

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Optimizing data and voice service delivery for mobile phones based on clients' demand and location using affinity propagation machine learning by Emmanuel C. Ukekwe, Adaora A. Obayi, Akpa Johnson, Daniel A. Musa, Jonathan C. Agbo

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Metaheuristic optimization of extreme gradient boosting machine for enhanced prediction of lateral strength of reinforced concrete columns under cyclic loadings by Phu-Anh-Huy Pham, Nhat-Duc Hoang

“…Since model selection is critical for constructing a reliable prediction mode, this study relies on utilizing metaheuristic approaches, including Genetic Algorithm, Particle Swarm Optimization, Artificial Bee Colony, and Ant Colony Optimization, to optimize the performance of the XGBoost model. …”
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Blood Glucose Concentration Prediction Based on Double Decomposition and Deep Extreme Learning Machine Optimized by Nonlinear Marine Predator Algorithm by Yang Shen, Deyi Li, Wenbo Wang, Xu Dong

“…To enhance the prediction accuracy, a new short-term glucose prediction model that integrates the double decomposition technique, nonlinear marine predator algorithm (NMPA) and deep extreme learning machine (DELM) is proposed. …”
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Predicting Tropical Cyclone Extreme Rainfall in Guangxi, China: An Interpretable Machine Learning Framework Addressing Class Imbalance and Feature Optimization by Yuexing Cai, Cuiyin Huang, Fengqin Zheng, Guangtao Li, Sheng Lai, Liyun Zhu, Qiuyu Zhu

“…Results showed that the optimized XGBoost model exhibited outstanding performance, integrating 18 predictors across dynamic, thermodynamic, moisture, and precursor variables, with a Threat Score of 0.41 for the classification of TCER occurrence and a Threat Score of 0.49 for the regression of rainfall magnitude, outperforming the TIGGE ensemble data in case studies of typhoons Chaba (2022) and Doksuri (2023). …”
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OPTIMIZING THE PLACEMENT OF A WORK-PIECE AT A MULTI-POSITION ROTARY TABLE OF TRANSFER MACHINE WITH VERTICAL MULTI-SPINDLE HEAD by N. N. Guschinski, V. E. Zdanovich, B. M. Rozin

“…To solve this problem the mathematical model and heuristic particle swarm optimization algorithm are proposed. …”
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Non-destructive identification of commercial jerky types based on multi-band hyperspectral imaging with machine learning by Yuanxi Han, Liang Li, Siyuan Jiang, Pengpeng Sun, Wenliang Wu, Zhendong Liu

“…This study provides reference for the band, model selection, and optimization of jerky type identification.…”
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Machine learning-based prediction method for open-pit mining truck speed distribution in manned operation by Changyou XU, Gang CHEN, Qiuxia ZHANG, Bo WANG, Hongwang ZHANG, Hongrui LI, Weiwei QIN, Muyang LI

“…The purpose is to develop and apply a machine learning-based approach for the prediction and scheduling optimization of open-pit mining truck speeds. …”
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Reliability analysis of landing gear operation based on improved support vector machine-based decomposed-coordinated by ZHANG Lei, CHEN Junyu, FENG Jun, FENG Yunwen, LIU Lei

“…The improved support vector machine aims to optimize the performance of the limit state function in each sub-mathematical model by applying multi-stage adaptive point position control of hyperparameters. …”
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Simulation-Based Design and Machine Learning Optimization of a Novel Liquid Cooling System for Radio Frequency Coils in Magnetic Hyperthermia by Serhat Ilgaz Yöner, Alpay Özcan

“…A dataset of 300 simulation cases was generated to train a Gaussian Process Regression-based machine learning model. The performance index was also developed and modeled using Gaussian Process Regression, enabling rapid performance prediction without requiring extensive numerical studies. …”
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Machine learning assisted CFD optimization of fuel-staging natural gas burners for enhanced combustion efficiency and reduced NOx emissions by Muhammad Mubashir, Dekui Shen, Habib Kraiem, Aymen Flah, Nahar F. Alshammari, Muhammad Mubashar Hanif

“…Using Computational Fluid Dynamics (CFD) simulations combined with Machine Learning (ML)-assisted predictive modeling, the burner geometry, fuel–air mixing behavior, and heat transfer dynamics were systematically optimized. …”
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Machine-Learning-Guided Design of Nanostructured Metal Oxide Photoanodes for Photoelectrochemical Water Splitting: From Material Discovery to Performance Optimization by Xiongwei Liang, Shaopeng Yu, Bo Meng, Yongfu Ju, Shuai Wang, Yingning Wang

“…This review highlights recent progress in the machine learning (ML)-assisted development of nanostructured metal oxide photoanodes, focusing on bridging materials discovery and device-level performance optimization. …”
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