Prediction of potential suitable habitats of Malania oleifera under future climate scenarios based on the MaxEnt model by Ye Zhang, Mimi Li, Xiaoning Zhang, Zihai Qin, Ping Wang, Hailong Liu

“…Abstract Malania oleifera is a nationally Category II protected wild plant in China and a Vulnerable species on the IUCN Red List, specifically distributed in the karst forest, playing a crucial role in maintaining biodiversity and ecological balance in karst fragile ecosystems. …”
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Assessing the performance and explainability of an avalanche danger forecast model by C. Pérez-Guillén, F. Techel, M. Volpi, A. van Herwijnen

“…This study assesses a random-forest classifier trained with weather data and physical snow-cover simulations as input for predicting dry-snow avalanche danger levels during the initial live testing in the winter season of 2020–2021 in Switzerland. …”
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Lidar DEM and Computational Mesh Grid Resolutions Modify Roughness in 2D Hydrodynamic Models by Elizabeth M. Prior, Nathan Michaelson, Jonathan A. Czuba, Thomas J. Pingel, Valerie A. Thomas, W. Cully Hession

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A Sustainability Index for Evaluating Vegetation Restoration Under Rainwater Resources Limitation by Wenjing Yang, Yong Zhao, Jianshi Zhao, Huanyu Chang

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Optimising management against dynamic threats: A spatially explicit approach based on integer programming by José Salgado‐Rojas, Virgilio Hermoso, Eduardo Álvarez‐Miranda

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The Past, Present, and Future Distribution of Sargentodoxa: Perspectives From Fossil Record and Species Distribution Models by Xuanqi Liu, Huasheng Huang, Xia Meng, Minqiao Li, Zeyu Qin

“…Ultimately, we apply a random forest model to simulate the suitable habitats of S. cuneata under past, present, and future climate scenarios and integrate fossil records to analyze its biogeographical history. …”
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Detection of focal source and arrhythmogenic substrate from body surface potentials to guide atrial fibrillation ablation. by Yingjing Feng, Caroline H Roney, Jason D Bayer, Steven A Niederer, Mélèze Hocini, Edward J Vigmond

“…ECGs and BSPMs were simulated. Equivalent atrial sources were extracted using second-order blind source separation, and their cycle length, periodicity and contribution, were used as features for random forest classifiers. …”
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The 4th Dimension in Animal Movement: The Effect of Temporal Resolution and Landscape Configuration in Habitat‐Selection Analyses by Johannes Signer, Cédric Scherer, Viktoriia Radchuk, Carolin Scholz, Florian Jeltsch, Stephanie Kramer‐Schadt

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Mathematical modeling of Elbrus glaciers in the 21st century. Part 1. Glaciological model and setup of numerical experiments. by T. N. Postnikova, O. O. Rybak, A. S. Gubanov, H. Zekollari, M. Huss

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Identification of gene signatures and potential pharmaceutical candidates linked to COVID-19-related depression based on gene expression profiles by Shaojun Chen, Yiyuan Luo, Lihua Zhang

“…Subsequently, we employed two machine learning analyses—least absolute shrinkage and selection operator (LASSO) and random forest algorithms– to pinpoint shared hub gene between the two diseases. …”
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Wind power generation prediction using LSTM model optimized by sparrow search algorithm and firefly algorithm by Wenjing Zhang, Hongjing Yan, Lili Xiang, Linling Shao

“…The model first employs a bidirectional long short-term memory network to capture the long-term dependency features of time series, and uses random forests for nonlinear modeling and feature selection. …”
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Research on autocorrelation and cross-correlation analyses in vehicular nodes positioning by Xuerong Cui, Jingzhen Li, Juan Li, Jianhang Liu, Tingpei Huang, Haihua Chen

“…At the same time, global navigation satellite system often fails to operate in non-line of sight areas, such as forests, tunnels, or downtown. IEEE 802.11p is developed for vehicle-to-vehicle (V2V) communication in order to meet the requirement for high accuracy in high speed and multipath vehicle environments. …”
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The role of antecedent conditions in translating precipitation events into extreme floods at the catchment scale and in a large-basin context by M. Staudinger, M. Kauzlaric, A. Mas, G. Evin, B. Hingray, D. Viviroli

“…</p> <p>Spatial organization within a larger area is complicated. After routing the simulated runoff, we analyzed the important patterns and drivers of extreme flooding at the outlet of the Aare River basin using a random forest. …”
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Rapid and accurate multi-phenotype imputation for millions of individuals by Lin-Lin Gu, Hong-Shan Wu, Tian-Yi Liu, Yong-Jie Zhang, Jing-Cheng He, Xiao-Lei Liu, Zhi-Yong Wang, Guo-Bo Chen, Dan Jiang, Ming Fang

“…We demonstrate by extensive simulations that PIXANT is reliable, robust and highly resource-efficient. …”
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Discovering effective policies for land-use planning with neuroevolution by Daniel Young, Olivier Francon, Elliot Meyerson, Clemens Schwingshackl, Jacob Bieker, Hugo Cunha, Babak Hodjat, Risto Miikkulainen

“…How areas of land are allocated for different uses, such as forests, urban areas, and agriculture, has a large effect on the terrestrial carbon balance and, therefore, climate change. …”
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Development of longitudinal datasets (2000–2020) with high spatiotemporal resolution for air pollution exposure assessment in CanadaFRDR) by Anas Alhusban, Yasar Burak Oztaner, Markey Johnson, Mastaneh Rezasefat, Negin Hojjatzadeh, Israa Moussa, Mahsa Soleimani, Saeed Nadi, Shunliu Zhao, Hwashin Shin, Joyce J.Y. Zhang, Amir Hakami

“…Widely used machine learning (ML) algorithms like random forest and gradient boosting were chosen and proved to be promising. …”
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Latitudinal gradient and environmental drivers of soil organic carbon in permafrost regions of the Headwater Area of the Yellow River by Mingxin Yang, Shizhen Li, Shouxin Wang, Qingdongzhi Huang, Qi Shen, Yanbin Kang, Mingming Shi, Yafei Zhang, Dongliang Luo

“…Climate warming trends resulted in increased ALT and TTOP. Random Forest analysis identified SBD as the most important predictor of SOC variability, which explains 38.20% of the variance, followed by ALT and vegetation coverage. …”
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Adaptive high frequency data streaming for Soft Real-Time Industrial AI: A scalable microservices based architecture with dynamic downsampling by Telmo Fernández De Barrena, Alcides Fernandes, Juan Luis Ferrando, Ander García, Hugo Landaluce, Ignacio Angulo

“…The proposed architecture is first tested with simulated data and then validated on an industrial conveyor belt system, demonstrating its effectiveness in predicting operational states through the integration of a Random Forest-based ML model. …”
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Strategic land management for ecosystem Sustainability: Scenario insights from the Northeast black soil region by Yufei Zhang, Zhenxing Bian, Xiaoyu Guo, Chuqiao Wang, Deyang Guan

“…The results show that: During the 30-year period, 1) Under any of the simulated scenarios, the level of ecosystem services in the NBSR tends to increase overall. 2) Rapid conversion between land use types and reduction of forest land area lead to weakening of synergies and increasing of trade-offs among ecosystem services. 3) Conversion and intensity of land use types significantly impacted on the level of ecosystem services under different scenarios (p < 0.05); the transfer out of built-up land (0.1249) and the transfer in of water area (0.1153) contributed more to the ESI. 4) The land use pattern under the sustainable development policy (SD scenario), which emphasizes ecological land conservation, effectively enhances ecosystem service levels. …”
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Data-driven predictive model of coal permeability based on microscopic fracture structure characterization by Tianhao Yan, Xiaomeng Xu, Jiafeng Liu, Yihuai Zhang, Muhammad Arif, Xiaowei Xu, Qiang Wang

“…The proposed framework encompasses data generation through the integration of three-dimensional (3D) digital core analysis and numerical simulations, followed by data-driven modeling via machine learning (ML) techniques. …”
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