Research on the Parameter Prediction Model for Fully Mechanized Mining Equipment Selection Based on RF-WOA-XGBoost by Yue Wu, Wenlong Sang, Xiangang Cao, Longlong He

“…Feature selection is performed based on the feature importance ranking obtained through the Random Forest (RF) method, thereby reducing the model complexity. …”
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Evaluation of hygienic food handling practices and associated factors among food handlers in the Amhara region, Ethiopia: a systematic review and meta-analysis by Lamenew Fenta, Kebadu Tadesse

“…Eyeball testing using forest plots, Cochrane Q test statistics and I² had been used to identify and measure heterogeneity. …”
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Township-Level Ecological Management for Enhanced Ecosystem Services in the Qinling Mountains by Yan Zhao, Yiping Chen, Wenqi Wu, Hanwen Tian, Huiwen Zhang

“…The Qinling Mountains, known for high forest cover and multiple ecosystem services (ES), present significant potential for advancing ecological management (EM) paradigms. …”
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IDMPF: intelligent diabetes mellitus prediction framework using machine learning by Leila Ismail, Huned Materwala

“…The authors implement and evaluate the decision tree (DT)-based random forest (RF) and support vector machine (SVM) learning models for diabetes prediction as the mostly used approaches in the literature using our framework. …”
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An Enhanced Deep Neural Network for Predicting Workplace Absenteeism by Syed Atif Ali Shah, Irfan Uddin, Furqan Aziz, Shafiq Ahmad, Mahmoud Ahmad Al-Khasawneh, Mohamed Sharaf

“…The efficacy of the proposed method is tested with traditional machine learning techniques, and the results indicate 90.6% performance in Deep Neural Network as compared to 73.3% performance in a single-layer Neural Network and 82% performance in Decision Tree, SVM, and Random Forest. The proposed model will provide a useful mechanism to organizations that are interested to know the behavior of employees at the time of hiring and can reduce the cost of paying to inefficient or habitually absent employees. …”
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Etude démographique du magot (Macaca sylvanus) dans le site touristique des cascades d’Ouzoud (Maroc) by Abderrazak El Alami, Abderrahman Chait

“…This species represents an excellent biological indicator of the forest quality and the Barbary macaque demography can monitor the decline of this species and the degradation of its natural habitats. …”
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Assessing chemical exposure risk in breastfeeding infants: An explainable machine learning model for human milk transfer prediction by Xiaojie Huang, Jiajia Chen, Peineng Liu

“…Our novel framework integrates ensemble resampling methods with advanced feature selection techniques, addressing data imbalance and enhancing predictive accuracy. The balanced random forest classifier, optimized using the genetic algorithm for feature selection, achieved an area under the receiver operating characteristic curve (AUC) of 0.8708 and an accuracy of 82.67 % on the internal test set, with an accuracy of 86.36 % on the external validation set. …”
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Microspatial Distributional Patterns of Vectors of Cutaneous Leishmaniasis in Pernambuco, Northeastern Brazil by Maria Rita Donalisio, A. Townsend Peterson, Pietra Lemos Costa, Fernando José da Silva, Hélio França Valença, Jeffrey J. Shaw, Sinval P. Brandão Filho

“…On the other hand, L. complexa, L. sordelli, and L. tupynambai were found almost exclusively in forested areas (𝑃<0.05), and associated positively with denser vegetation. …”
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GCL_FCS30: a global coastline dataset with 30-m resolution and a fine classification system from 2010 to 2020 by Jian Zuo, Li Zhang, Jingfeng Xiao, Bowei Chen, Bo Zhang, Yingwen Hu, M. M. Abdullah Al Mamun, Yang Wang, Kaixin Li

“…The coastline classification was performed a hybrid transect classifier that integrates a random forest algorithm with stable training samples derived from multi-source geophysical data. …”
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Implementasi Sensor Polar H10 dan Raspberry Pi dalam Pemantauan dan Klasifikasi Detak Jantung Beberapa Individu Secara Simultan dengan Pendekatan Machine Learning  by eko sakti pramukantoro, Kasyful Amron, Viera Wardhani, Putri Annisa Kamila

“…Data tersebut kemudian diprediksi menggunakan model machine learning berbasis random forest yang berjalan pada Raspberry Pi untuk prediksi 5 jenis detak jantung. …”
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Fast Ways to Detect Outliers by Emad Obaid Merza, Nashaat Jasim Mohammed

“…On the other hand, the presence of outliers ​​may be of great benefit, for example knowledge of geological activities that precede natural disasters such as (earthquakes, forest fires, floods ... etc.). Therefore, detection of outliers is of great importance in various fields. …”
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Enhancing breast cancer prediction through stacking ensemble and deep learning integration by Fatih Gurcan

“…To achieve this, the efficacy of ensemble methods such as Random Forest, XGBoost, LightGBM, ExtraTrees, HistGradientBoosting, AdaBoost, GradientBoosting, and CatBoost in modeling breast cancer diagnosis was comprehensively evaluated. …”
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Identification of Fake Comments in E-Commerce Based on Triplet Convolutional Twin Network and CatBoost Model by Juanjuan Peng

“…The benchmark experimental results show that the proposed TriCNN-CatBoost model significantly outperforms traditional Naive Bayes, Support Vector Machines, and Random Forest models in terms of accuracy, recall, and F1 score, demonstrating stronger false comment recognition ability and generalization performance. …”
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Immunocompromised Children with Severe Adenoviral Respiratory Infection by Joanna C. Tylka, Michael C. McCrory, Shira J. Gertz, Jason W. Custer, Michael C. Spaeder

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Declining extent of fen peat deposits over the past 50 years in Ogre Municipality, central Latvia by Normunds Stivrins, Davis Matskins, Ilze Ozola

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Comparison and Estimation of Surface Albedo of Various Levels of Land use by SEBAL and METRIC Methods by Mehdi Asadi, Khalil Valizadeh khamran, Mohammad Baaghdeh, Hamed Adab

“…The amount of albedo was also examined in agricultural (0.240 based on SEBAL method and 0.247 based on METRIC method) and forest lands (0.149 based on SEBAL method and 0.225 based on METRIC method). …”
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Assessment of source material for malting barley breeding by O. A. Yusova, P. N. Nikolaev, M. A. Kuzmich, L. S. Kuzmich

“…The studies were carried out from 2017 to 2020. in the southern forest-steppe of Western Siberia. The target material included 13 lines: Sasha × Getman (2 lines), Sasha × Margret, Podarok Sibiri × Getman (3 lines), Omsky 95 × Beatrice (3 lines), Omsky 95 × Despina, Omsky 95 × Viva, Omsky 100 × Margret, and Omsky 90 × Margret. …”
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Shoot complexes on the apical part of the crown of generative <i>Fraxinus excelsior</i> L. trees by I. S. Antonova, M. S. Televinova

“…Fraxinus excelsior L. is a common forest species in the Central Russian Upland, used to produce valuable lumber and for landscaping. …”
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Control y Biología del Helecho Trepador Japonés (Lygodium japonicum) by Elsa D. Chevasco, Patrick J. Minogue, Kimberly K. Bohn, Francisco Escobedo

“…Bohn, and Francisco Escobedo, and published by the UF Department of School of Forest Resources and Conservation, November 2016. …”
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Towards Circular Economy through Waste to Biomass Energy in Madagascar by Ling Qin, Mengjun Wang, Jinfu Zhu, Yuhu Wei, Xintao Zhou, Zheng He

“…This paper reviews the following: (1) a variety of available biomass wastes for energy in Madagascar including farming residuals, animal wastes, and forest wastes, as well as urban and industrial organic wastes; (2) advanced technologies, such as gasification, torrefaction, and fermentation, that can convert these wastes to biomass energy in forms with higher energy efficiency such as biogas, biocoal briquette, and ethanol fuel, which can not only help to achieve resource utilization of wastes and circular economy but also ease the energy crisis faced by Madagascar; and (3) Madagascar focused on the development of biomass energy with strategic policies and programs. …”
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