Early warning strategies for corporate operational risk: A study by an improved random forest algorithm using FCM clustering. by Xini Fang

“…To enhance the accuracy and response speed of the risk early warning system, this study develops a novel early warning system that combines the Fuzzy C-Means (FCM) clustering algorithm and the Random Forest (RF) model. Firstly, based on operational risk theory, market risk, research and development risk, financial risk, and human resource risk are selected as the primary indicators for enterprise risk assessment. …”
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Predicting autoimmune thyroiditis in primary Sjogren’s syndrome patients using a random forest classifier: a retrospective study by Jia-yun Wu, Jing-yu Zhang, Wen-qi Xia, Yue-ning Kang, Ru-yi Liao, Yu-ling Chen, Xiao-min Li, Ya Wen, Fan-xuan Meng, Li-ling Xu, Sheng-hui Wen, Hui-fen Liu, Yuan-qing Li, Jie-ruo Gu, Qing Lv, Yong Ren

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Urban growth simulation using cellular automata model and machine learning algorithms (case study: Tabriz metropolis) by Omid Ashkriz, Babak Mirbagheri, Ali Akbar Matkan, Alireza Shakiba

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The abundance and sett ecological characteristics of the Asian badger (Meles leucurus) in the Northeast Tiger and Leopard National Park (NE China) by Jiawei Li, Dongrui Li, Yanwen Fu, Yiwen Ma, Jianping Ge, Limin Feng

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Forecasting O3 and NO2 concentrations with spatiotemporally continuous coverage in southeastern China using a Machine learning approach by Zeyue Li, Jianzhao Bi, Yang Liu, Xuefei Hu

“…In this research, we adopted a forecasting model that integrates the random forest algorithm with NASA’s Goddard Earth Observing System “Composing Forecasting” (GEOS-CF) product. …”
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SIGLEC1 has the potential to be an immune-related prognostic indicator in colon adenocarcinoma: a study based on transcriptomic data and Mendelian randomization analysis by Jue Gu, Yaxuan Wang, Hui Zhang, Haijuan Gu, Haixia Zhu

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Landslide susceptibility evaluation and determination of critical influencing factors in eastern Sichuan mountainous area, China by Lin Zhang, Zhengxi Guo, Shi Qi, Tianheng Zhao, Bingchen Wu, Peng Li

“…The results shown that Random Forest Model proves to be the most accurate (95.1 %) in assessing the spatial distribution of shallow landslides susceptibility, followed by the Artificial Neural Network model (78.6 %), the Support Vector Machine model (69.8 %), the Generalized additive model (68.1 %) and the Logistic Regression model (67.6 %).The area with high susceptible landslide possibility was 25.3 km2 occupying 14.8 % of the study region, it is mainly distributed in the west of Tianchi Lake, southeast of Huaying City and west of the study area, along with Xiangyu Railway. …”
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Evaluating Feature Selection Methods for Accurate Diagnosis of Diabetic Kidney Disease by Valeria Maeda-Gutiérrez, Carlos E. Galván-Tejada, Jorge I. Galván-Tejada, Miguel Cruz, José M. Celaya-Padilla, Hamurabi Gamboa-Rosales, Alejandra García-Hernández, Huizilopoztli Luna-García, Klinge Orlando Villalba-Condori

“…After selecting suitable features detected by the methodologies, they are included in the random forest classifier, obtaining four models. <b>Results</b>: Galgo with Random Forest achieved the best performance with only three predictors, “creatinine”, “urea”, and “lipids treatment”. …”
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Applications of Multi-Robotic Arms to Assist Agricultural Production: A Review by Xiaojian Gai, Chang Xu, Yajia Liu, Qingchun Feng, Shubo Wang

“…This paper summarizes the key technologies used in current research, including heuristic algorithms, fast search rapidly exploring random trees, reinforcement learning algorithms, etc., and focuses on reviewing the present applications of cutting-edge reinforcement learning algorithms in agricultural robotic arms. …”
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A systematic mapping to investigate the application of machine learning techniques in requirement engineering activities by Shoaib Hassan, Qianmu Li, Khursheed Aurangzeb, Affan Yasin, Javed Ali Khan, Muhammad Shahid Anwar

“…The results show that the scientific community used 57 algorithms. Among those algorithms, researchers mostly used the five following ML algorithms in RE activities: Decision Tree, Support Vector Machine, Naïve Bayes, K‐nearest neighbour Classifier, and Random Forest. …”
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Groundwater estimation and determination of its probable recharge source in the Lower Swat District, Khyber Pakhtunkhwa, Pakistan, using analytical data and multiple machine learni... by Imran Ahmad, Ibrar Ul Haq, Mansoor Ahmad, Iram Gul, Mursaleen Khan, Khushnuma Khushnuma, Ubaid Ullah, Maqsood Ur Rehman, Mohamed Metwaly

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Advancing sustainable mobility: Dynamic predictive modeling of charging cycles in electric vehicles using machine learning techniques and predictive application development by Biplov Paneru, Durga Prasad Mainali, Bishwash Paneru, Sanjog Chhetri Sapkota

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SGLT2 inhibitors and kidneys: mechanisms and main effects in diabetes mellitus patients by Vladimir V Salukhov, Yurii Sh. Khalimov, Sergey B. Shustov, Sergey I. Popov

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Effectiveness of a clinical decision support algorithm (ePOCT+) in improving quality of care for sick children in primary health facilities in Tanzania (DYNAMIC project): results f... by Dr Caroline Enos, Godfrey A. Kavishe, Alexandra V. Kulinkina, Sabine Renggli, Chacha D. Mangu, Lameck Luwanda, Peter Agrea, Humphrey Mhagama, Margaret Joram, Ibrahim Mtebene, Geofrey Isdory Ashery, Marie-Annick Le Pogam, Honorati Masanja, Nyanda E. Ntinginya, Valérie D'Acremont, Rainer Tan

“…Methods: 18 health facilities (9 intervention and 9 control, randomized 1:1) were sampled from the main cluster randomized trial. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

“…Subsequently, DDoS attack detection is performed based on random forest (RF) and decision tree (DT) algorithms. …”
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Assessing the spatiotemporal dynamics of seasonal and perennial surface water resources across Lesotho’s agroecological zones by Kunwar K. Singh, Sayedeh Sara Sayedi, Ariel BenYishay, Tšepiso A. Rantšo

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Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…In these diversified test scenarios, the improved TD3 algorithm exhibits remarkable adaptability and stability. …”
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The Controlling Factors and Prediction of Deep-Water Mass Transport Deposits in the Pliocene Qiongdongnan Basin, South China Sea by Jiawang Ge, Xiaoming Zhao, Qi Fan, Weixin Pang, Chong Yue, Yueyao Chen

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On precise path planning algorithm in wireless sensor network by Farhanda Javed, Samiullah Khan, Asfandyar Khan, Alweena Javed, Rohi Tariq, Matiullah, Faheem Khan

“…Simulation scenarios with three node densities are used in this research study such as sparse node density, medium node density, and dense node density. …”
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Modified Meerkat Clan Algorithm for Association Rules Mining by Mohamad Ab. Saleh, Ahmed T. Sadiq Sadiq

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