Evaluation of Four Methods for Predicting Carbon Stocks of Korean Pine Plantations in Heilongjiang Province, China. by Huilin Gao, Lihu Dong, Fengri Li, Lianjun Zhang

“…The first method predicted carbon stocks directly by the compatible carbon stocks models (Method 1). …”
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Evaluation and prediction of coal seam mining mode: Coefficient of Variation-TOPSIS and CNN-NGO methods by Haixiong Li, Fei Wang

“…This study explores and validates an integrated evaluation system that enhances the accuracy of predicting coal seam mining mode by comparing traditional evaluation methods with machine-learning techniques. …”
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Evaluation and comparison of semi-empirical and numerical methods in predicting wave characteristics in the South Caspian Sea by zahra hajebi, adel amouzegar, Seyed Taghi Omid Naeeni

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Evaluation of the KDS 14 Draft Design Method for Predicting the Shear Strength of Prestressed Concrete Beams by Ngoc Hieu Dinh, Si-Hyun Kim, Kyoung-Kyu Choi

“…This study evaluated the applicability of the KDS 14 draft design method, which is based on compression zone failure theory, for predicting the shear strength of slender PSC beams. …”
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Approaches, Relevant Topics, and Internal Method for Uncertainty Evaluation in Predictions of Thermal-Hydraulic System Codes by Alessandro Petruzzi, Francesco D'Auria

“…The needs come from the imperfection of computational tools, on the one side, and the interest in using such a tool to get more precise evaluation of safety margins. The paper reviews the salient features of three independent approaches for estimating uncertainties associated with predictions of complex system codes. …”
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Hotspots, evaluation methods and sustainable development of ecological carrying capacity research–based on bibliometric and knowledge mapping analysis by Li He, Gai Wang, Zhengwei He, Fang Luo, Yuxin Cen, Run Jin, Siyu Tan, Hairong Ding

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Efficiency and Reliability of Broiler Weighing Methods in Commercial Environments: A Comparative Evaluation by Isis Mariana Dombrowsky Leal Pasian, Robson Mateus Freitas Silveira, Jessica Nacarato Reple, Hilton Tadeu Zarate Couto, Iran José Oliveira da Silva

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Evaluating Prediction Performance: A Simulation Study Comparing Penalized and Classical Variable Selection Methods in Low-Dimensional Data by Edwin Kipruto, Willi Sauerbrei

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Comparative evaluation of predictable and unpredictable environments as backgrounds for selection to adaptive ability by В. М. Стариченко

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Machine Learning System for Predicting Cardiovascular Disorders in Diabetic Patients by A. Mayya, H. Solieman

“…Feature selection methods were used to derive the most significant indicators for predicting CVD risk in diabetic patients. …”
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THE METHODS OF EXTRAPOLATING A VECTOR RANDOM PROCESS BASED ON THE CANONICAL DECOMPOSITION USING THE METHOD OF INTEGRAL ASSESSMENTS FOR A CERTAIN INTERVAL WHEN DETERMINING OF RANDOM... by Rustam K. Murasov

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Editorial: Methods in predictive toxicology 2023 by Sankalp Jain, Serena Manganelli, Vitalina Gryshkova, Maria Armanda Rodrigues, Aniket Magarkar

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Evaluating the Stress State and the Load-Bearing Fraction as Predicted by an In Vivo Parameter Identification Method for the Abdominal Aorta by Jerker Karlsson, Jan-Lucas Gade, Carl-Johan Thore, Carl-Johan Carlhäll, Jan Engvall, Jonas Stålhand

“…<b>Methods:</b> Our team has evaluated an in vivo parameter identification method through in silico experiments involving finite element models and demonstrated good agreement with the parameters of a healthy abdominal aorta. …”
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A Prediction Method for Postconstruction Settlement of Pile-Soil Composite Subgrade Based on Fuzzy Comprehensive Evaluation by Hao Shan, Guanghui Jiang, Yajing Chang, Junli Cheng, Baoning Hong, Shengcheng Wang

“…This paper presents a postconstruction settlement prediction method for pile-soil composite subgrade based on the multilevel fuzzy comprehensive evaluation principle. …”
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A dissimilarity-adaptive cross-validation method for evaluating geospatial machine learning predictions with clustered samples by Yanwen Wang, Mahdi Khodadadzadeh, Raúl Zurita-Milla

“…Results showed that DA-CV provided the most accurate evaluations in 85% of scenarios. DA-CV effectively overcomes the common limitations of random and spatial CV methods, such as only considering a part of predictions in the evaluation. …”
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Enhancing diabetes risk prediction: A comparative evaluation of bagging, boosting, and ensemble classifiers with SMOTE oversampling by Rabia Asif, Darshana Upadhyay, Marzia Zaman, Srini Sampalli

“…This study explores advanced machine learning techniques, specifically bagging, boosting, and ensemble methods to improve diabetes risk prediction. Using three diverse datasets, namely, the Centers for Disease Control and Prevention (CDC) Diabetes Health Indicators dataset, the Early Stage Diabetes Risk Prediction System (ESDRP) dataset, and the PIMA Indian Diabetes dataset are utilized to evaluate the adaptability and robustness of the proposed models. …”
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Timing Method for the Isoland Signalized Intersection Considering the Traffic Uncertainty by LING Mo;WU Zhen;GUO Jianhua

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A Robustness Evaluation Method for the Robust Control of Electrical Drive Systems Based on Six-Sigma Methodology by Nabil Farah, Gang Lei, Jianguo Zhu, Youguang Guo

“…Besides the conventional predictive control of PMSM drive, three different robust predictive control methods are evaluated in terms of two different parametric uncertainty ranges and three application requirements against parametric uncertainties.…”
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Comparative Analysis of Explainable AI Methods for Manufacturing Defect Prediction: A Mathematical Perspective by Gabriel Marín Díaz

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Development of Comprehensive Predictive Models for Evaluating Böhme Abrasion Value (BAV) of Dimension Stones Using Non-Destructive Testing Methods by Ekin Köken

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