Exploring the process—structure–property relationship of nylon aramid 3D printed composites and parameter optimization using supervised machine learning techniques by Mohammed Raffic Noor Mohamed, Ganesh Babu Karuppiah, Dharani Kumar Selvan, Rajasekaran Saminathan, Shubham Sharma, Shashi Prakash Dwivedi, Sandeep Kumar, Mohamed Abbas, Dražan Kozak, Jasmina Lozanovic

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A multi-strategy improved snake optimizer and its application to SVM parameter selection by Hong Lu, Hongxiang Zhan, Tinghua Wang

“…The mirror opposition-based learning mechanism (MOBL) improved the population quality to enhance the optimization speed. The novel evolutionary population dynamics model (NEPD) was beneficial for searching accurately. …”
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Optimized Coupling Coil Geometry for High Wireless Power Transfer Efficiency in Mobile Devices by Fahad M. Alotaibi

“…The framework integrates a hybrid sequential neural network and multivariate regression model to optimize coil winding and ferrite core geometry. …”
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Predictive modelling of air pollution affecting human tuberculosis risk on Mainland China by Boli Qin, Rongqing He, Xiaopeng Qin, Jiayan Jiang, Chenxing Zhou, Songze Wu, Jichong Zhu, Shaofeng Wu, Jiarui Chen, Jiang Xue, Kechang He, Chong Liu, Jie Ma, Xinli Zhan

“…SHapley Additive exPlanations analysis helped interpret the RF model’s predictions. Seasonal and lag analyses identified a 10-month optimal lag period. …”
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Bayesian-optimized stacking ensemble with multimodal feature selection for tobacco leaf maturity classification by Yunpeng Lu, Yang Wu, Lu Zhang, Jinguo Huang, Guangwei Sun, Jing Liu

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Advanced machine learning techniques for predicting compressive strength and ultrasonic pulse velocity of concrete incorporating industrial by-products by Ehsan Mohsennia, Alireza Javid, Vahab Toufigh

“…A robust dataset, comprising 162 structured IBP concrete samples and 524 data points from existing literature, enabled rigorous training and validation of sophisticated ML models. Among the models tested, the CatBoost (CB) algorithm, optimized with the Whale Optimization Algorithm (WOA), exhibited outstanding predictive performance. …”
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Data mining-based optimal assignment of apparel size for mass customization by Zhujun Wang, Cheng Chi, Mengyun Zhang, Xianyi Zeng, Pascal Bruniaux, Jianping Wang, Yingmei Xing

“…Lastly, the solution based on support machine was considered as the optimal solution for pants mass customization after being comprehensively assessed by the aggregate loss of fit, the number of poor fit, accommodation rate of ideal fit, and the number of garment size employed, since it employed only 48 sizes to reach the accommodation rate of the target population up to 82%. …”
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Predicting Atmospheric Dispersion of Industrial Chemicals Using Machine Learning Approaches by Maria Valle, Jairo A. Cardona, Cesar Viloria-Nunez, Christian G. Quintero M.

“…Atmospheric and contextual variables, such as wind speed, air temperature, tank specifications, and chemical release parameters, were thoroughly characterized to construct a robust database using experimental data and software simulations. Machine learning techniques were rigorously trained and tested to predict atmospheric dispersion, emphasizing hyperparameter optimization to enhance model performance. …”
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Optimizing the utilization of Metakaolin in pre-cured geopolymer concrete using ensemble and symbolic regressions by Kennedy C. Onyelowe, Viroon Kamchoom, Ahmed M. Ebid, Shadi Hanandeh, José Luis Llamuca Llamuca, Fabián Patricio Londo Yachambay, José Luis Allauca Palta, M. Vishnupriyan, Siva Avudaiappan

“…Abstract The optimization of metakaolin (MK) in pre-cured geopolymer concrete involves developing predictive models to capture the interplay of various influencing factors and guide mix design for improved compressive strength and sustainability. …”
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Enhancing knee osteoarthritis detection with AI, image denoising, and optimized classification methods and the importance of physical therapy methods by Burak Bugday, Harun Bingol, Muhammed Yildirim, Bilal Alatas

“…As a result, a high accuracy rate of 85% was achieved in the developed system of the support vector machine (SVM) classifier. The proposed model was more successful than the other models used in the study.…”
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Chronic liver disease detection using ranking and projection-based feature optimization with deep learning by Sumaiya Noor, Salman A. AlQahtani, Salman Khan

“…Our experimental results demonstrate that this proposed model outperforms traditional machine learning algorithms, achieving superior accuracy. …”
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A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses by Zixuan Zhou, Lihua Li, Hao Xue, Yuchen Jia, Yao Yu, Zongkui Xie, Yuhan Gu

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The use of artificial intelligence to analyze and optimize financial flows by М. А. Miakisheva

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Comprehensive quality detection method for tomatoes combining machine vision and spectral techniques by GUO Dechao, RAO Yuanli, ZHANG Hao, LI Chunfeng, ZHAO Qiang

“…Complete tomato internal quality grading through preprocessing methods, feature extraction methods, and improved particle swarm optimization using least squares support vector machine. …”
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Predicting 3-year all-cause mortality in rectal cancer patients based on body composition and machine learning by Xiangyong Li, Zeyang Zhou, Xiaoyang Zhang, Xinmeng Cheng, Chungen Xing, Yong Wu

“…The optimal model was determined based on the area under the receiver operating characteristic curve (AUROC). …”
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Optimization of waste plastic fiber concrete with recycled coarse aggregate using RSM and ANN by Sumant Nivarutti Shinde, Sharon Christa, Rakesh Kumar Grover, Nadeem Pasha, D. Harinder, G. Nakkeeran, George Uwadiegwu Alaneme

“…The modified mortar exhibited a 30% increase in compressive strength, reaching 38.62 MPa compared to 33.05 MPa in conventional mortar, with an additional 0.6% plastic fiber incorporation. Furthermore, machine learning models, including Response Surface Methodology (RSM) and Artificial Neural Networks (ANN), were used for optimization and prediction, showing high accuracy. …”
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Optimizing blood glucose predictions in type 1 diabetes patients using a stacking ensemble approach by Vincent B. Liu, Laura Y. Sue, Oscar Madrid Padilla, Yingnian Wu

“…Using the DiaTrend dataset, this study used stacking machine learning optimized by Grey Wolf Optimizer to construct and assess prediction models for blood glucose levels in type 1 diabetes patients. …”
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LightEnsemble-Guard: An Optimized Ensemble Learning Framework for Securing Resource-Constrained IoT Systems by Muhammad Usama Tanveer, Kashif Munir, Madiha Amjad, Hasan J. Alyamani, Amine Bermak, Atiq Ur Rehman

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A Surrogate Piecewise Linear Loss Function for Contextual Stochastic Linear Programs in Transport by Qi Hong, Mo Jia, Xuecheng Tian, Zhiyuan Liu, Shuaian Wang

“…Rather than directly incorporating decision loss into the learning objective based on specific problem, PLLF serves as a general feedback mechanism that guides the prediction model based on the structure and sensitivity of the downstream optimization task. …”
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Improving the prediction of bitumen’s density and thermal expansion by optimizing artificial neural networks with Optuna and TensorFlow by Eli I. Assaf, Xueyan Liu, Sandra Erkens

“…Beyond simply replacing RFRs, we develop a fully automated framework for constructing Machine Learning Models (MLMs) to predict density and thermal expansion coefficients of bitumen. …”
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