Research on the Simulation Model of Dynamic Shape for Forest Fire Burned Area Based on Grid Paths from Satellite Remote Sensing Images by Xintao Ling, Gui Zhang, Ying Zheng, Huashun Xiao, Yongke Yang, Fang Zhou, Xin Wu

“…The hyper-parameters of each model were optimized using grid search method. …”
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Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence by Manish Sharma Timilsina, Yuvraj Chaudhary, Prikshya Bhattarai, Bibek Uprety, Dilip Khatiwada

“…This study assists industries and policymakers to assess and understand the viability of co-pyrolysis, optimal design parameters, and process impacts.…”
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Estimation of Cation Exchange Capacity for Low-Activity Clay Soil Fractions Using Experimental Data from South China by Jun Zhu, Zhong-Xiu Sun

“…Four covariate datasets were combined based on available soil data and environmental variables and various parameters for machine learning techniques including an artificial neural network, a deep belief network, support vector regression and random forest were optimized. …”
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A Comparative Analysis of Different Algorithms for Estimating Evapotranspiration with Limited Observation Variables: A Case Study in Beijing, China by Di Sun, Hang Zhang, Yanbing Qi, Yanmin Ren, Zhengxian Zhang, Xuemin Li, Yuping Lv, Minghan Cheng

“…Remote sensing (RS) technology presents an efficient approach for estimating ET at regional scales; however, existing RS retrieval algorithms for ET are intricate and necessitate a multitude of parameters. The land surface temperature–vegetation index (LST-VI) space method and statistical regression by machine learning (ML) offer the benefits of simplicity and straightforward implementation. …”
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A novel early stage drip irrigation system cost estimation model based on management and environmental variables by Masoud Pourgholam-Amiji, Khaled Ahmadaali, Abdolmajid Liaghat

“…Support vector machine (SVM) and optimization algorithms (Wrapper) were found to be the best learner and feature selection techniques, respectively, out of all the available feature selection algorithms. …”
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Association between atherogenicity indices and prediabetes: a 5-year retrospective cohort study in a general Chinese physical examination population by Xianli Qiu, Yong Han, Changchun Cao, Yuheng Liao, Haofei Hu

“…This study aimed to comprehensively evaluate the associations between six atherogenicity indices and prediabetes risk in a Chinese population, and explore the predictive value of these atherosclerotic parameters for prediabetes. Methods This retrospective cohort study included 97,151 participants from 32 healthcare centers across China, with a median follow-up of 2.99 (2.13, 3.95) years. …”
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Population-based colorectal cancer risk prediction using a SHAP-enhanced LightGBM model by Guinian Du, Hui Lv, Yishan Liang, Jingyue Zhang, Qiaoling Huang, Guiming Xie, Xian Wu, Hao Zeng, Lijuan Wu, Jianbo Ye, Wentan Xie, Xia Li, Yifan Sun

“…Seven ML algorithms were systematically compared, with Light Gradient Boosting Machine (LightGBM) ultimately selected as the optimal framework. …”
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Integrated diagnostics and time series sensitivity assessment for growth monitoring of a medicinal plant (Glycyrrhiza uralensis Fisch.) based on unmanned aerial vehicle multispectr... by Ao Zhang, Haibin Guan, Zhiheng Dong, Xin Jia, Yan Xue, Fengyu Han, Lingjiang Meng, Xiuling Yu, Xiaoqin Wang, Yang Cao

“…Models were constructed using backpropagation neural network (BP), support vector machine (SVM), and random forest (RF) to evaluate PIs to predict yield and monitor growth dynamics. …”
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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

“…The integration of ensemble and symbolic regression models enables researchers to derive valuable predictions and optimize critical performance parameters efficiently. In this research work, 235 records were collected from extensive literature search for compressive strength for different mixing ratios of pre-cured metakaolin-based geopolymer concrete with concrete at different ages. …”
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Artificial intelligence for prediction of atrial fibrillation in the stroke unit: a retrospective derivation validation cohort studyResearch in context by Maximilian Schoels, Laura Krumm, Alexander Nelde, Manuel C. Olma, Christian H. Nolte, Jan F. Scheitz, Markus G. Klammer, Christoph Leithner, Andreas Meisel, Franziska Scheibe, Michael Krämer, Karl Georg Haeusler, Matthias Endres, Christian Meisel

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Dynamic conditioning of porcine kidney grafts with extracellular vesicles derived from urine progenitor cells: A proof‐of‐concept study by Perrine Burdeyron, Sébastien Giraud, Maryne Lepoittevin, Nina Jordan, Sonia Brishoual, Maïté Jacquard, Virginie Ameteau, Nadège Boildieu, Estelle Lemarie, Jonathan Daniel, Frédéric Martins, Nicolas Mélis, Marine Coué, Raphaël Thuillier, Henri Leuvenink, Luc Pellerin, Thierry Hauet, Clara Steichen

“…Kidneys were subjected to warm ischemia (32 min) and then preserved by hypothermic machine perfusion (HMP) for 24 h before 5 h of normothermic machine perfusion (NMP). …”
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Research into the Dynamic Characteristics of the Planetary Cob­Separating Device by V. M. Pogosyan, M. E. Chaplygin

“…The authors found out that the machine dynamics research problems are rather diverse due to the complexity of the dynamic processes occurring in them. …”
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Study on Predicting Blueberry Hardness from Images for Adjusting Mechanical Gripper Force by Hao Yin, Wenxin Li, Han Wang, Yuhuan Li, Jiang Liu, Baogang Li

“…Additionally, considering practical applications, a simple and efficient two-parameter method was proposed, removing the weight parameter and predicting fruit hardness using only diameter and thickness. …”
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Forças de corte ortogonal 90-90 em três espécies de madeira de eucalipto do estado de São Paulo Orthogonal 90-90 cutting forces for three wood species of Eucalyptus by Antônio Carlos Néri, Raquel Gonçalves, Roger E. Hernandez

“…The results show the influence of the machining parameters in the cutting forces and indicate its relevance in order to optimize the wood machining process.…”
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Three-Stage Optimization of Surface Finish in WEDM of D2 Tool Steel via Taguchi Design and ANOVA Analysis by Thanh Tan Nguyen, Bui Phuoc Phi, Van Tron Tran, Van-Thuc Nguyen, Van Thanh Tien Nguyen

“…Each machining step directly affects the accuracy and machining time, and the preceding machining step influences the subsequent machining step parameters. …”
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A Step Towards Real-Time Release Testing of Pharmaceutical Tablets: Utilization of CIELAB Color Space by René Brands, Trieu Nam Le, Jens Bartsch, Markus Thommes

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Penerapan Feature Engineering dan Hyperparameter Tuning untuk Meningkatkan Akurasi Model Random Forest pada Klasifikasi Risiko Kredit by Nadea Putri Nur Fauzi, Siti Khomsah, Aditya Dwi Putra Wicaksono

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Fast Bayesian inference for neutrino non-standard interactions at dark matter direct detection experiments by Dorian W P Amaral, Shixiao Liang, Juehang Qin, Christopher Tunnell

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Thermodynamic properties of L-menthol in crystalline and gaseous states by A. V. Blokhin, Ya. N. Yurkshtovich

“…The temperature dependence of L-menthol’s heat capacity in the range of 5–370 K and the melting (fusion) parameters were determined using adiabatic calorimetry. …”
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Elucidating thermal phenomena of non-Newtonian experimental data based copper-alumina-ethylene glycol hybrid nanofluid in a cubic enclosure with central heated plate by machine lea... by Md. Mamun Molla, Md Farhad Hasan, Md. Mahadul Islam

“…Finally, a cross-validation performance analysis was conducted using a machine learning model and good accuracy was obtained. …”
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