Water quality evaluation in Liaoning Province large reservoirs: a new method integrating random forest-TOPSIS and Monte Carlo simulation by Chong Zhang, Mo Chen, Yi Wang

“…The model integrates the technique for order preference by similarity to ideal solution with Monte Carlo simulation and employs the random forest method for weight allocation. …”
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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

“…Accurately simulating and predicting this dynamic process can provide a scientific basis for forest fire control and suppression decisions. …”
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Research on collaboration training techniques based on virtual simulation for aviation emergency management by SHANG Yuhui, LIU Hu, YANG Shuai, ZHANG Xin, TIAN Yongliang

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The Impact of Snow Cover on River Discharge Simulation: Insights from the Barandozchay River Basin by Haleh Hashemi, Hossein Rezaie, Keivan Khalili, Amin Amini

“…The results indicate that the Random Forest model outperforms the others in accuracy and generalization, while SVM demonstrates improved predictive capabilities with the inclusion of snow cover data. …”
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Using power analysis and spatial prioritization to evaluate the design of a forest bird monitoring programme by Darren M. Southwell, Adam Smart, Samuel D. Merson, Katherine E. Selwood, Nicholas A. Macgregor

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Utilizing Forest Trees for Mitigation of Low-Frequency Ground Vibration Induced by Railway Operation by Zeyu Zhang, Xiaohui Zhang, Zhiyao Tian, Chao He

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Simulation Analysis of Temperature Field of Optical Fiber Composite Overhead Ground Wire by Lifeng ZHANG, Xiaohua LI, Wenbin ZHAO

“…On this basis, a method is proposed to monitor the forest fire by using the influence of forest fire on the temperature field of OPGW. …”
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Identification of Ion-kinetic Instabilities in Hybrid-PIC Simulations of Solar Wind Plasma with Machine Learning by Viacheslav M. Sadykov, Leon Ofman, Scott A. Boardsen, Yogesh, Parisa Mostafavi, Lan K. Jian, Kristopher Klein, Mihailo Martinović

“…We compare feature-based classifiers applied to VDF moments, such as support vector machine and random forest (RF), with DL convolutional neural networks (CNNs) applied directly to VDFs as images in the gyrotropic velocity plane. …”
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Accessing the spatial distribution of aboveground biomass in tropical mountain forests using regression kriging simulation: a geostatistical approach for local-scale estimates by Joel Carlos Rodrigues Otaviano, Cássio Freitas Pereira de Almeida

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Structural Complexity Significantly Impacts Canopy Reflectance Simulations as Revealed from Reconstructed and Sentinel-2-Monitored Scenes in a Temperate Deciduous Forest by Yi Gan, Quan Wang, Guangman Song

“…This study demonstrated that the Eradiate RTM, based on the 3D explicit representation, is capable of providing accurate radiative transfer simulations in the temperate deciduous forest and hence provides a basis for understanding tree interactions and their effects on ecosystem structure and functions.…”
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Simulating the Carbon, Nitrogen, and Phosphorus of Plant Above-Ground Parts in Alpine Grasslands of Xizang, China by Mingxue Xiang, Gang Fu, Jianghao Cheng, Tao Ma, Yunqiao Ma, Kai Zheng, Zhaoqi Wang

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Predicting forest carbon storage and identifying hotspot in the Loess Plateau under future climate change–supporting China's dual carbon strategy by Haihong Qiu, Hairong Han, Xiaoqin Cheng, Fengfeng Kang

Subjects: “…Forest remote sensing…”
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Incorporating information of causal variants in genomic prediction using GBLUP or machine learning models in a simulated livestock population by Jifan Yang, Mario P. L. Calus, Yvonne C. J. Wientjes, Theo H. E. Meuwissen, Pascal Duenk

“…The objective of this study was to assess the benefit of incorporating QTL genotypes in GBLUP and machine learning models. This study simulated a selected livestock population where QTL and their effects were known. …”
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Simulation of Spatial and Temporal Dynamics in Habitat Quality amid Rapid Urbanization based on Random Forest Algorithm: A Lingui District, Guilin City Case Study by Zhang Xiaoyan, Liu Hanxin, Yang Xin, Wu Gang, Tan Junjie

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Investigating the contribution of understory to radiative transfer simulations through reconstructing 3-D realistic temperate broadleaf forest scenes based on multi-platform laser scanning by Xiaohan Lin, Ainong Li, Jinhu Bian, Zhengjian Zhang, Xi Nan, Limin Chen, Yi Bai, Yi Deng, Siyuan Li

Subjects: “…Radiative transfer simulation…”
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Simulated nitrogen deposition reduces CH4 uptake and increases N2O emission from a subtropical plantation forest soil in southern China. by Yongsheng Wang, Shulan Cheng, Huajun Fang, Guirui Yu, Minjie Xu, Xusheng Dang, Linsen Li, Lei Wang

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Effects of temporary erosion control blanket and grass cover on the rates of runoff and sediment in the cut and fill slopes of forest roads using a rainfall simulation test by Behnaz Askari, Mehran Nasiri, Majid Lotfalian

“…Methods: The study area is the Darabkola Forest (the educational-research forest of Sari University of Agricultural Sciences and Natural Resources), with an area of  about 2612 hectares located in the southeast of Sari City between 52° 14′ E and 36° 28′ N. …”
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Snow Depth Retrieval Using Sentinel-1 Radar Data: A Comparative Analysis of Random Forest and Support Vector Machine Models with Simulated Annealing Optimization by Yurong Cui, Sixuan Chen, Guiquan Mo, Dabin Ji, Lansong Lv, Juan Fu

“…Snow depth retrieval was subsequently performed using both random forest (RF) and Support Vector Machine (SVM) models. …”
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Anomaly detection using unsupervised machine learning algorithms: A simulation study by Edmund Fosu Agyemang

“…The evaluation reveals that One-Class SVM, Isolation Forest, and Robust Covariance are more effective in identifying outliers in the synthetic simulated dataset, with Isolation Forest slightly outperforming the other algorithms in terms of balancing precision and recall. …”
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Efficacy of machine learning in simulating precipitation and its extremes over the capital cities in North Indian states by Aayushi Tandon, Amit Awasthi, Kanhu Charan Pattnayak

“…The current ML model builds on the relationship between rainfall and key climatic parameters such as dew point temperature and relative humidity, showing a strong positive correlation (CC = 0.4) significant at the 0.05 level. In simulating precipitation, Random Forest Classifier (RFC) achieved the highest accuracy (~ 83%) for Rajasthan and Uttar Pradesh, while Support Vector Classifier (SVC) performed best (79–83% accuracy) in other states. …”
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