Altitudinal patterns of soil and microbial C:N:P stoichiometry in subtropical forests in Daming Mountain, South China by Chunlin Huo, Zhonghua Zhang, Zhonghua Zhang, Yinghua Luo, Yinghua Luo, Gang Hu, Gang Hu

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Research on Grounding Fault Identification Method of DC 600 V Power Supply System Based on Random Forest by Zhou ZENG, Zixian LI, Wei DONG, Jian GUO, Jie CAI

“…In order to solve the problem that the current DC 600 V power supply system can only diagnose a few of fault modes and has poor universality, a simulation model of DC 600 V power supply system was built, and various fault modes of power supply system were analyzed, such as input terminal, intermediate circuit, output terminal grounding, etc.; The key features of fault waveform were selected and extracted, then the random forest classifier method was used to solve the problem that the existing diagnosis methods were not universal. …”
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Shifts in Fungal Communities and Potential Functions Under Masson Pine Forest-to-Tea Plantation Conversion in Subtropical China by Xiaofang Ma, Xiaofang Ou, Dan Chen, Yong Li, Cameron McMillan, Tida Ge, Ji Liu, Min Xue, Cong Wang, Weijun Shen

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Fatigue Detection Algorithm for Nuclear Power Plant Operators Based on Random Forest and Back Propagation Neural Networks by Yuhang Jiang, Junsong Li, Yu Zhang

“…This article proposes a fatigue detection algorithm for nuclear power plant control room operators based on random forest and BP neural networks, specifically targeting the control room scenario. …”
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Maintaining rockfall protection in mountain forests under climate change: optimizing management for sustainable stem size distributions by Ulrike Hiltner, Jonas Glatthorn, Timothy Thrippleton, Harald Bugmann

“…This study uses a simulation-based optimization approach, integrating the dynamic forest model ForClim with the Simulated Annealing optimization algorithm, to identify adaptive management strategies for Swiss forests. …”
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Simulation and assessment of the risk of carbon sink loss in Hubei Province, China by Jiang Li, Jiang Li, Baomiao Ning, Rui Shu, Rui Shu, Yixiong Xia, Guobin Yuan, Yun Shen, Yanping Yu, Xun Liang

“…Grassland management carbon sinks are highest in the ecological priority scenario. Forest management carbon emissions peak under ecological priority. …”
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Intelligent energy management of microgrids using machine learning: Leveraging random forest models for solar and wind power by Hasanur Zaman Anonto, Md Ismail Hossain, Abu Shufian, Md. Shaoran Sayem, S M Tanvir Hassan Shovon, Protik Parvez Sheikh, Sadman Shahriar Alam

“…The study at hand suggests dedicating a new type of energy management of the microgrid by using the machine-learning algorithms, namely the Random Forest (RF) regressor along with real-time forecasting the energy use and renewable-energy production. …”
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Can Thinning Foster Forest Genetic Adaptation to Drought? A Demo‐Genetic Modelling Approach With Disturbance Regimes by Victor Fririon, Hendrik Davi, Sylvie Oddou‐Muratorio, Gauthier Ligot, François Lefèvre

“…Here, we used a modelling approach to explore the interplay and feedback loops among drought regimes, natural selection and tree thinning in naturally regenerated monospecific forests. We conducted a simulation experiment spanning three nonoverlapping generations with the individual‐based demo‐genetic model Luberon2. …”
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Nonparametric quantification of uncertainty in multistep upscaling approaches: A case study on estimating forest biomass in the Brazilian Amazon by Denis Valle, Leo Haneda, Rafael Izbicki, Renan Akio Kamimura, Bruna Pereira de Azevedo, Silvio H.M. Gomes, Arthur Sanchez, Carlos A. Silva, Danilo R.A. Almeida

“…., machine learning models such as random forest), a problem that is further exacerbated if the results from multiple models are combined within a multistep upscaling methodology. …”
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Copper silicate nanoneedle arrays on reduced graphene oxide like “shelter forest” guiding Zn gradient deposition by Na Gao, Yang Wang, Zhanming Gao, Tianming Lv, Mengyu Rong, Xueying Dong, Dongzhi Chen, Changgong Meng, Yifu Zhang

“…The presence of rGO improves the electrical conductivity of CuSiO3, and the finite element simulation of the electric field and Zn2+ concentration proves that the electric field distribution can be effectively homogenized and the local current density can be reduced for the rGO@CuSi-Zn electrode with the surface presenting the shape of a protective forest. …”
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Addressing Challenges in Simulating Inter–Annual Variability of Gross Primary Production by Ranit De, Shanning Bao, Sujan Koirala, Alexander Brenning, Markus Reichstein, Torbern Tagesson, Michael Liddell, Andreas Ibrom, Sebastian Wolf, Ladislav Šigut, Lukas Hörtnagl, William Woodgate, Mika Korkiakoski, Lutz Merbold, T. Andrew Black, Marilyn Roland, Anne Klosterhalfen, Peter D. Blanken, Sara Knox, Simone Sabbatini, Bert Gielen, Leonardo Montagnani, Rasmus Fensholt, Georg Wohlfahrt, Ankur R. Desai, Eugénie Paul‐Limoges, Marta Galvagno, Albin Hammerle, Georg Jocher, Borja Ruiz Reverter, David Holl, Jiquan Chen, Luca Vitale, M. Altaf Arain, Nuno Carvalhais

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Evaluation of long-term carbon dynamics in a drained forested peatland using the ForSAFE-Peat model by D. Escobar, D. Escobar, S. Manzoni, J. Tapasco, P. Vestin, S. Belyazid

“…This study utilised the dynamic ecosystem model ForSAFE-Peat to simulate biogeochemical dynamics over two complete forest rotations (1951–2088) in a nutrient-rich drained peatland afforested with Norway spruce (<i>Picea abies</i>) in southwestern Sweden. …”
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Seedling passage times in gaps and closed canopies reveal decades of understory persistence in a New England forest by Isabella Stone, Jeffrey Mintz, Claudia J. Garnica‐Díaz, Chia‐Hao Chang‐Yang, David A. Orwig, Audrey A. Barker Plotkin, April Zee, Raelene M. Crandall, Daniel J. Johnson, Lukas J. Magee

“…To examine species‐level variation in understory persistence and passage to the sapling life stage, we followed 5236 seedlings in single‐tree canopy gaps and closed canopy conditions over three years and simulated seedling passage times and the number of seedlings required to produce one 1.5‐m tall sapling of five common tree species in a hemlock–hardwood forest of Massachusetts, USA. …”
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Centennial spatiotemporal evolution of AGC in subtropical forests and key driving factors − based on process modeling and geography detector by Lei Huang, Zihao Huang, Xuejian Li, Fangjie Mao, Meixuan Song, Yinyin Zhao, Fengfeng Ye, Lujin Lv, Jiacong Yu, Huaqiang Du

“…Therefore, this study utilized the BIOME-BGC model to simulate the spatial and temporal distribution of AGC in subtropical forests over a 100-year period (2000–2100) under four SSP-RCP scenarios, focusing on Zhejiang Province, China. …”
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Interpretable prediction of drug synergy for breast cancer by random forest with features from Boolean modeling of signaling pathways by Kittisak Taoma, Marasri Ruengjitchatchawalya, Kanthida Kusonmano, Teerasit Termsaithong, Thana Sutthibutpong, Monrudee Liangruksa, Teeraphan Laomettachit

“…In this study, we developed a random forest model using simulated protein activities derived from Boolean modeling of breast cancer signaling pathways as input features. …”
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A Terrestrial Ecosystem Carbon Sink Assessment Model Considering Forest Age Dynamics (CEVSA‐AgeD) by Mengyu Zhang, Honglin He, Li Zhang, Guirui Yu, Xiaoli Ren, Yuanyuan Huang, Wenping Yuan, Zhong'en Niu

“…The magnitude of average NEP in China estimated using this model was 0.35 ± 0.005 TgC/yr from 2001 to 2021, which was close to previous estimates, and the dynamics of forests age increased NEP by 87–92 TgC/yr. These results indicate that the CEVSA‐AgeD model performed well in simulating carbon fluxes at the site and regional scales and that it was necessary to incorporate the effect of forest age dynamics on carbon cycling processes into process‐based models.…”
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RF-SFAD: A RANDOM FOREST MODEL FOR SELECTIVE FORWARDING ATTACK DETECTION IN MOBILE WIRELESS SENSOR NETWORKS by N Usha Bhanu, Soubhagya Ranjan Mallick, Sreenivasa Rao Chappidi, K Sangeethalakshmi

“…This paper proposes a Random Forest (RF)-based SFA detection framework designed for the dynamic nature of clustered MWSNs. …”
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Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand by Yu-Huan Zhao, Delwyn Moller, Dean Meason, Mahta Moghaddam

“…A subsurface soil moisture retrieval algorithm, using a pathfinder simultaneously acquired P- and L-band radar data over forested areas, is proposed in this article. It employs a generalized radar backscattering model for forests and a second-order polynomial function for soil moisture profile. …”
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Gas pipeline leakage detection based on multiple multimodal deep feature selections and optimized deep forest classifier by Eddie Zhang, Evan Zhang

“…Hyperparameters of the base learners are then selected for an explainable and enhanced diversity tree-structured deep forest classifier, using the selected multimodal features as inputs. …”
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Effects of sample tree selection and calculation methods on the accuracy of field plot values in area-based forest inventories by Lennart Noordermeer, Terje Gobakken, Johannes Breidenbach, Rune Eriksen, Erik Næsset, Hans Ole Ørka, Ole M. Bollandsås

“…Accurate field plot data on forest attributes are crucial in area-based forest inventories assisted by airborne laser scanning, providing an essential reference for calibrating predictive models. …”
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