Traffic congestion forecasting using machine learning methods by Ramil R. Zagidullin, Almaz N. Khaybullin

“…Additionally, to compare and validate the results, the ensemble method Random Forest was used, configured with the following hyperparameters: 200 trees, maximum depth of 12, minimum samples per leaf of 2. …”
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Field assessments on the impact of CO₂ concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forests by D. Teng, D. Teng, J. Zhu, J. Zhu, J. Zhu, T. Gao, T. Gao, T. Gao, F. Yu, F. Yu, Y. Zhu, Y. Zhu, X. Zhou, X. Zhou, B. Yang

“…However, estimating <span class="inline-formula"><i>F</i>_s</span> remains challenging due to the frequent gusts and random fluctuations in boundary-layer flows that lead to tremendous difficulties in capturing the true trend of CO<span class="inline-formula">₂</span> changes for use in storage estimation from eddy covariance along with atmospheric profile techniques. …”
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Probabilistic analysis of ground settlement induced by soil and rock composite foundation excavation considering spatial variability by Yongjun Zhang, Zhenfu Zhang, Sijia Liu, Mingzhong Gao, Jintao Wang, Jinfeng Cao

“…This study proposes a probabilistic framework applicable to braced excavations in composite soil-rock layers, designed to quantitatively evaluate the impact of variability on these excavations and to explore its potential implications. …”
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Rapid generation of secondary fibroblasts through teratoma formation by Sang Mi Cho, Jung Sun Park, Byungkuk Min, Sujin Kwon, Yong-Kook Kang

“…The use of secondary or reprogrammable cells in the production of induced pluripotent stem cells (iPSCs) circumvents random infection by various viral particles and random, uncontrollable integrations of the viral genomes into different genomic loci. …”
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Climate change impacts on the predicted geographic distribution of Betula tianschanica Rupr by Hang Zhou, Hang Zhou, Ao Li, Ao Li, Xuequn Luo, Xuequn Luo, Jiafeng Wang, Jiafeng Wang, Yihong Xie, Zhongping Lin, Donglai Hua

“…The MaxEnt model showed that the percentage of gravel volume in the lower soil layer and elevation are the most significant, while the RF model considered elevation and precipitation of the wettest quarter to be the most crucial. …”
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A Multi-Algorithm Machine Learning Model for Predicting the Risk of Preterm Birth in Patients with Early-Onset Preeclampsia by Xu Y, Zu Y, Zhang Y, Liang Z, Xu X, Yan J

“…Univariate analysis, random forest importance assessment, lasso regression combined with multivariate regression analysis were used for feature evaluation. …”
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Machine learning-based quantification and separation of emissions and meteorological effects on PM2.5 in Greater Bangkok by Nishit Aman, Sirima Panyametheekul, Ittipol Pawarmart, Di Xian, Ling Gao, Lin Tian, Kasemsan Manomaiphiboon, Yangjun Wang

“…Six ML models namely random forest (RF), adaptive boosting (ADB), gradient boosting (GB), extreme gradient boosting (XGB), light gradient boosting machine (LGBM), and cat boosting (CB) were used with meteorological factors, fire activity, land use, and socio-economic data as predictor variables. …”
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Integrated deep vertical rotary tillage and subsurface pipe drainage techniques for sustainable soil salinization management and cotton production in arid regions by Zhijie Li, Qiang Meng, Ling Li, Zhentao Bai, Yanjie Li, Hongguang Liu, Pengfei Li, Tangang Wang

“…Meanwhile, the total nitrogen (TN), phosphorus (TP), and potassium (TK) contents in the 0–20 cm soil layer were significantly reduced by 3–8 %, 3–6 %, and 9–19 %, respectively, compared to the CT treatment. …”
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Development and External Validation of [18F]FDG PET-CT-Derived Radiomic Models for Prediction of Abdominal Aortic Aneurysm Growth Rate by Simran Singh Dhesi, Pratik Adusumilli, Nishant Ravikumar, Mohammed A. Waduud, Russell Frood, Alejandro F. Frangi, Garry McDermott, James H. F. Rudd, Yuan Huang, Jonathan R. Boyle, Maysoon Elkhawad, David E. Newby, Nikhil Joshi, Jing Yi Kwan, Patrick Coughlin, Marc A. Bailey, Andrew F. Scarsbrook

“…Recursive feature elimination (RFE) reduced features for model optimisation. A multi-layer perceptron (MLP) was developed for AAA growth prediction and compared against Random Forest (RF), XGBoost, and Support Vector Machine (SVM). …”
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Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning by Chenbo Yang, Chenbo Yang, Meichen Feng, Juan Bai, Hui Sun, Rutian Bi, Lifang Song, Chao Wang, Yu Zhao, Wude Yang, Lujie Xiao, Meijun Zhang, Xiaoyan Song

“…Hyperspectral monitoring models for winter wheat ChD were constructed using 8 machine learning algorithms, including partial least squares regression, support vector regression, multi-layer perceptron regression, random forest regression, extra-trees regression (ETsR), decision tree regression, K-nearest neighbors regression, and gaussian process regression, based on the full spectrum band and the band selected by competitive adaptive reweighted sampling (CARS). …”
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Development of Machine Learning Prediction Models to Predict ICU Admission and the Length of Stay in ICU for COVID‑19 Patients Using a Clinical Dataset Including Chest Computed Tom... by Seyed Salman Zakariaee, Negar Naderi, Hadi Kazemi-Arpanahi

“…For predicting the ICU admission of COVID-19 patients, k-nearest neighbors (k-NN) yielded better performance than J48, support vector machine, multi-layer perceptron, Naïve Bayes, logistic regression, random forest (RF), and XGBoostbased ML models. …”
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Experimental Study of Modified Videman Method to Replicate Knee Osteoarthritis in Rabbits by Jing LIU, Qiaoxuan LIN, Liming LU, Zexing GUO, Hong LIU, Liangzhi ZHANG, Zhongbiao XIU

“…Objective:To establish a convenient, stable and efficient rabbit model of knee osteoarthritis (KOA).Methods:Sixty male New Zealand rabbits were selected as the normal group, traditional Videman method group (traditional group) and modified Videman method group (improved group) according to the random number table method, with twenty cases in each group. …”
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Application of attention mechanism-based LSTM neural network in stratigraphy identification by Cunde Jia, Xiangdong Kong, Minghui Wang, Zhuowei Yu, Haipeng Li, Yunhong Jiang, Jianliang Hu, Chao Ai

“…Subsequently, the decoder combines the time-series features extracted from each Transformer encoder layer using a one-dimensional Convolutional Neural Network (1D-CNN) and inputs them into the LSTM neural network for formation prediction. …”
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Resin infiltrant protects deproteinized dentin against erosive and abrasive wear by Ana Theresa Queiroz de Albuquerque, Bruna Oliveira Bezerra, Isabelly de Carvalho Leal, Maria Denise Rodrigues de Moraes, Mary Anne S. Melo, Vanara Florêncio Passos

“…ObjectivesThis study aimed to investigate the anti-erosive/abrasive effect of resin infiltration of previous deproteinized dentin.Materials and MethodsDentin slabs were randomly assigned to 3 groups (n = 15): Control (no deproteinization; no resin infiltrant applied), RI (no deproteinization; resin infiltrant applied), and DRI (deproteinization; resin infiltrant applied). …”
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Response of leaf area and dry matter of crop, weeds and cover crops to competition and fertilizer resources by Fahimeh DADASHI, Faezeh ZAEFARIAN, Rahmat ABBASI, Mohammad Ali BAHMANYAR, Mohammad REZVANI

“…Plasticity of plants to allocate leaf area and dry matter to upper layer of canopy play important role in canopy architecture and competition. …”
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Relationship between serum uric acid level and triglyceride in middle-aged and elderly population in Hotan district of Xinjiang by Nuerguli·Abulaiti, CHEN Feng-hui, CHENG Zu-heng, QIU Chang-chun, Mayila·Wufuer

“…Methods Stratified sampling and complete randomization were used to select 1356 long-term residents aged over 40 in Hotan District of Xinjiang. …”
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Co-Optimization Operation of Distribution Network-Containing Shared Energy Storage Multi-Microgrids Based on Multi-Body Game by Hao Wu, Ge Cao, Rong Jia, Yan Liang

“…The model is solved based on an outer-layer genetic algorithm nested with an inner-layer solver to determine the electricity purchase and sale prices among the distribution network, multi-microgrids, and shared energy storage at various time periods, thereby minimizing operational costs. …”
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Machine learning-driven design of wide-angle impedance matching structures for wide-angle scanning arrays by Sina Hasibi Taheri, Javad Mohammadpour, Ali Lalbakhsh, Slawomir Koziel, Stanislaw Szczepanski

“…Abstract This paper introduces a versatile and efficient design methodology for optimizing wide-angle impedance matching (WAIM) configurations, enhancing the scanning range of arbitrary antenna arrays. The three-layered structure is modeled using the generalized scattering matrices (GSMs) of the layers, incorporating sufficient excited modes for efficient input impedance calculation. …”
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EXPERIMENTAL STUDY OF EFFECTIVENESS OF DEEP FLUORIDATION OF ENAMEL DURING SECONDARY MINERALIZATION OF THE PERMANENT TEETH ENAMEL by H. V. Sorochenko

“…The chemical composition of the superficial layer of tooth enamel changed after using of methods of deep fluoridation of enamel. …”
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Combine photosynthetic characteristics and leaf hyperspectral reflectance for early detection of water stress by Linbao Li, Linbao Li, Linbao Li, Guiyun Huang, Guiyun Huang, Guiyun Huang, Jinhua Wu, Jinhua Wu, Jinhua Wu, Yunchao Yu, Yunchao Yu, Yunchao Yu, Guangxin Zhang, Guangxin Zhang, Guangxin Zhang, Yang Su, Yang Su, Yang Su, Xiongying Wang, Xiongying Wang, Xiongying Wang, Huiyuan Chen, Huiyuan Chen, Huiyuan Chen, Yeqing Wang, Di Wu, Di Wu, Di Wu

“…RF provided the best estimation accuracy for LCC compared to MLR, KNN and SVM, achieving an R2 value of 0.895 for all LCC samples. The canopy layer significantly influenced the estimation accuracy of LCC, with the middle layer yielding the highest R2 value. …”
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