Machines’ Intelligent Fault Diagnosis Based on Hierarchical Refined Composite Generalized Multiscale Fluctuation Dispersion Entropy by Biwen Chen, Changsheng Chen, Zhenlai Ma, Guoping Li, Yi Zhang, Baoyue Li

“…Subsequently, a Random Forest (RF) classifier is employed for fault identification. …”
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Low-Cost Solution for Assessment of Urban Flash Flood Impacts Using Sentinel-2 Satellite Images and Fuzzy Analytic Hierarchy Process: A Case Study of Ras Ghareb City, Egypt by Mohammed Sadek, Xuxiang Li

“…Natural hazards are indeed counted as the most critical challenges facing our world, represented in floods, earthquakes, volcanoes, hurricanes, and forest fires. Among these natural hazards, the flash flood is regarded the most frequent. …”
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Incorporating climate data with machine learning can improve rice phenology estimation by Yiqing Liu, Weihang Liu, Tao Ye, Shuo Chen, Xuehong Chen, Zitong Li, Ning Zhan, Ran Sun

“…Here, we developed a hybrid model by incorporating the growth-specific climate predictors and satellite-derived phenology using random forest approach. Results showed that our hybrid model successfully reduced errors by over 60% compared to traditional satellite-based methods. …”
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Utilizing UAV and orthophoto data with bathymetric LiDAR in google earth engine for coastal cliff degradation assessment by Paweł Tysiąc, Rafał Ossowski, Łukasz Janowski, Damian Moskalewicz

“…Next, by applying Random Forest classifier within Google Earth Engine, we evaluated the importance of features in detecting these degraded zones. …”
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Estimation of aboveground biomass and carbon storage in mangroves along the coast of Banda Aceh City by Farahisah Harum, Nanda Muhammad, Haditiar Yudi, Khairunnisa

“…The coastal area of Banda Aceh has significant potential for mangrove forests as carbon stocks. This study aimed to estimate the carbon storage in mangrove vegetation along the Banda Aceh coast. …”
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Copula-Driven Learning Techniques for Physical Layer Authentication Using Multimodal Data by Sahana Srikanth, Sanjeev Gurugopinath, Sami Muhaidat

“…For the classification task, we consider some of the well-known learning algorithms including long short-term memory (LSTM), random forest, K-nearest neighbor, support vector machine and bagging tree techniques. …”
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Effect of climate on thermal response in cows of different racial groups in lower tropic by Raúl Andrés Molina-Benavides, Sandra Milena Perilla-Duque, Rómulo Campos-Gaona, Hugo Sánchez-Guerrero, Juan Camilo Rivera-Palacio, Luis Armando Muñoz-Borja, Daniel Ricardo Jiménez-Rodas

“…The information was analyzed using descriptive statistics, correlation matrices and Random Forest models, through the R software. Results. From the physiological data from automatic collection systems, the response variables that would allow the evaluation of thermoregulation processes were analyzed using big data. …”
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Innovation and Collaboration Model Based on Ecological Fiscal Transfer Approach: Case Study on Green Siak Regency Policy Development by Wicaksono Baskoro, Marta Auradian, Febrina Rury, Rafi Muhammad, Gusmansyah Gusmansyah, Hergianasari Putri

“…Substantively, the ecological fiscal transfer approach is an innovative and crucial policy instrument that needs to be adopted to maintain the sustainability of forest areas in Siak Regency while continuing to encourage increased stakeholder collaboration through fiscal transfers and intergovernmental revenue sharing schemes based on ecological indicators as awards given based on the quality-of-life index in sustainable conservation efforts in Siak Regency.…”
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Identification of Working Trucks and Critical Path Nodes for Construction Waste Transportation Based on Electric Waybills: A Case Study of Shenzhen, China by Jun Bi, Qiuyue Sai, Fujun Wang, Yakun Chen

“…The results show that the XGBoost model can improve the accuracy of the generation of waybill to 90.5% compared with the decision tree model, random forest, and GBDT. Moreover, the density clustering model can discover the hot nodes of construction waste transportation. …”
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Presenting a model for the diagnosis of heart failure using cumulative and deep learning algorithms: a case study of tehran heart center by Amir Hossein Hariri, Esmaeil Bagheri, Sayyed Mohammad Reza Davoodi

“…In the classification phase, basic techniques were used, including a decision tree, a neural network, and different cumulative techniques such as gradient boosting, random forest, and the novel deep learning method. A comparison revealed that deep learning with the accuracy of 95.33%, disease class accuracy of 95.77%, and health class accuracy of 94.74% could enhance the presentation and results of the neural network. …”
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Phytoremediation potential of green spaces in the city by E. Yu. Zaykova, S. S. Feofanova

“…The cadastral unsettledness of the research area and the creation of the specially protected area “Landscape Reserve “Forest on the Samorodinka River” in 2020 create additional opportunities for the collection of stormwater and implementation of phytoremediation technologies.Results. …”
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Enhanced framework for ensemble effort estimation by using recursive‐based classification by Azath Hussain, Maheswari Raja, Pandimurugan Vellaisamy, Sangeetha Krishnan, Lakshminarayanan Rajendran

“…From the selected features, an enhanced random forest classification is used to classify the results. …”
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Tilapia Lake Virus (TiLV): a Globally Emerging Threat to Tilapia Aquaculture by Lowia Al-Hussinee, Kuttichantran Subramaniam, Win Surachetpong, Vsevolod Popov, Kathleen Hartman, Katharine Starzel, Roy Yanong, Craig Watson, Hugh Ferguson, Salvatore Frasca Jr, Thomas Waltzek

“…., and Thomas Waltzek and published by the UF/IFAS School of Forest Resources and Conservation, Program in Fisheries and Aquatic Sciences describes this important emerging disease and explains how to prevent outbreaks and what to do if you suspect TiLV in an aquaculture facility or in the wild.  …”
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Identification of Xylem Occlusions Occurring in Cut Clematis (Clematis L., fam. Ranunculaceae Juss.) Stems during Their Vase Life by Agata Jedrzejuk, Julia Rochala, Jacek Zakrzewski, Julita Rabiza-Świder

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Modeling the effect of climate change to the potential invasion range of Piper aduncum Linnaeus by J.C. Paquit, R.I.P. Rama

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Machine learning-based urban noise appropriateness evaluation method and driving factor analysis. by Jinlin Teng, Cheng Zhang, Huimin Gong, Chunqing Liu

“…This study introduces various machine learning methods and applies the Random Forest algorithm, which performed best, to investigate noise suitability in the central urban area of Nanchang City. …”
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Geographic Distribution Patterns of Soil Microbial Community Assembly Process in Mangrove Constructed Wetlands, Southeast China by Ping Hu, Qiong Yang

“…The abundance of genera changed significantly between the treatment groups, such as the genus <i>Candidatus_Udaeobacter</i> for bacteria versus <i>Russula</i> for fungi, and the random forest model showed that rare genera (e.g., <i>Acidibacter</i>, <i>Dyella</i>, <i>Sebacina</i>, and <i>Lachnellula</i>) also play an important role in microbial community construction. …”
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Diversity of Rust Fungi with Special Emphasis on <i>Hyalopsora erlangensis</i> Causing Disease in <i>Cystopteris chinensis</i> by An Yu, Xia Zhao, Xiaohong Chen

“…A newly discovered rust fungus poses a significant threat to the survival and reproduction of the endangered plant <i>Cystopteris chinensis</i> in a forest in western Sichuan province, China. This study utilized both morphological analysis and molecular phylogenetic approaches to classify this fungal taxon. …”
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Environmental Impact of Limestone Mining Using A Life Cycle Assessment Method by Atfal Murodif, Anas Miftah Fauzi, Erizal, Lina Karlinasari

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Áreas protegidas e acesso à terra: o caso de El Chaltén no Parque Nacional Los Glaciares (Patagônia Argentina) by Sabrina Elizabeth Picone

“…For this reason, they allowed certain human activities such as livestock, forest exploitation and also human settlements. However, since 1980 these territorial units are categorized by the international standards. …”
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