Evaluating the performances of SVR and XGBoost for short-range forecasting of heatwaves across different temperature zones of India by Srikanth Bhoopathi, Nitish Kumar, Somesh, Manali Pal

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EVALUATION OF POSSIBILITIES TO IMPROVE ACCURACY CHARACTERISTICS FOR ALGORITHMS OF REFINEMENT ANGULAR VELOCITY OF BALLISTIC AND SPACE OBJECTS IN EARLY WARNING RADARS by Sergei V. Kovbasjuk, Felix M. Andreev, Andrei V. Statkus

“…Therefore, the article deals with the methodology of comparative evaluation accuracy characteristics of algorithms of refinement angular velocity ballistic and space objects and assessing the level of their improvement through the use of different variants of construction algorithm of increasing the accuracy of range higher order derivatives, including information on the third derivative of distance. …”
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Algorithm for the formation of a system of multi-criteria metrics for evaluating the activity of energy companies taking into account ESG criteria by I.O.

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ADMET evaluation in drug discovery: 21. Application and industrial validation of machine learning algorithms for Caco-2 permeability prediction by Dong Wang, Jieyu Jin, Guqin Shi, Jingxiao Bao, Zheng Wang, Shimeng Li, Peichen Pan, Dan Li, Yu Kang, Tingjun Hou

“…In this study, we conducted an in-depth analysis of the characteristics of an augmented Caco-2 permeability dataset, and evaluated a diverse range of machine learning algorithms in combination with different molecular representations. …”
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Experience with artificial intelligence algorithms for the diagnosis of vertebral compression fractures based on computed tomography: from testing to practical evaluation by Zlata R. Artyukova, Alexey V. Petraikin, Nikita D. Kudryavtsev, Fedor A. Petryaykin, Dmitry S. Semenov, Daria E. Sharova, Zhanna E. Belaya, Anton V. Vladzimirskyy, Yuriy A. Vasilev

“…Artificial intelligence algorithm No. 1 passed the practical evaluation stage without any significant remarks, whereas algorithm No. 2 was sent for fine-tuning. …”
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Evaluating machine leaning algorithms for accuracy, stability, and among-predictors discriminability in modeling species-richness across ten datasets by Yong Cao, Tyler E. Schartel, David C. Houghton, Jared Ross, Dana M. Infante

“…While numerous machine learning (ML) algorithms for regression are available for such analyses, synthesizing outcomes across studies is challenging due to: (1) reliance on single datasets, limiting generalizability; (2) varying modeling processes; (3) inconsistent performance criteria; and (4) limited consideration of model stability and among-predictor discriminability.We addressed these issues by applying five ML algorithms—Random Forest (RF), Boosted Regression Tree (BRT), Extreme Gradient Boosting (XGB), Conditional Inference Forest (CIF), and Lasso—to ten large datasets on freshwater fish, mussels, and caddisflies. …”
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A Field Calibration Method for UHF Partial Discharge On-line Monitoring System Based on Cross-check Algorithm by Nan LI, Songyuan LI, Xuejun SHANG, Bowen GUO, Lin LI, Guoqiang ZU, Kai HOU

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Comparison of Tree Typologies Mapping Using Random Forest Classifier Algorithm of PRISMA and Sentinel-2 Products in Different Areas of Central Italy by Eros Caputi, Gabriele Delogu, Alessio Patriarca, Miriam Perretta, Giulia Mancini, Lorenzo Boccia, Fabio Recanatesi, Maria Nicolina Ripa

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Designing a Draft for a Metaheuristic Curriculum Evaluation Model (MCEM) Based on the Examination of Various Metaheuristic Artificial Intelligence Optimization Applications by Volkan Duran, Gülay Ekici

“…This paper explores the integration of metaheuristic artificial intelligence (AI) optimization algorithms into the process of curriculum evaluation, proposing a novel approach that could enhance educational outcomes. …”
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Research on manufacturing quality improvement based on product gene evaluation method and a meta-heuristic algorithm with hybrid encoding scheme by Wenxiang Xu, Chao Wang, Shimin Xu, Junyong Liang, Dezheng Liu, Baigang Du

“…In the model, the quality indicator is measured by a comprehensive evaluation approach of product gene. To address the model, an improved genetic algorithm (GA) and artificial bee colony algorithm (ABC) with hybrid encoding scheme (H-IGA-IABC) is designed by considering the different types of gene elements. …”
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Production Quality Evaluation of Electronic Control Modules Based on Deep Belief Network by Hua Gong, Wanning Xu, Congang Chen, Wenjuan Sun

“…To evaluate the production quality of electronic control modules, an algorithm based on a Deep Belief Network with Multi-mutation Differential Evolution (MDE-DBN) is designed in this study. …”
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Petrophysical evaluation of clastic formations in boreholes with incomplete well log dataset by using joint inversion technique and machine learning algorithms by Felipe Santana-Román, Ambrosio Aquino López, Manuel Romero Salcedo (+), Raúl del Valle García, Oscar Campos Enriquez

“…A succesful petrophysical evaluation of shaly-sand formations requieres: 1) the availability of high quality well log data and, 2) a petrophysical model that successfully represents the geological conditions of the rocks. …”
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System Evaluation and Management of College Students’ Physical Exercise Behavior Stages Integrating Bayesian Association Rules Data Mining Algorithm by Juan Shi

“…The experimental results show that after using MapReduce parallelization, the improved algorithm can not only process larger-scale data sets, but also save a lot of running time. …”
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Ecological and Statistical Evaluation of Genetic Algorithm (GARP), Maximum Entropy Method, and Logistic Regression in Predicting Spatial Distribution of Astragalus sp. by Amir Ghahremanian, Abbas Ahmadi, Hamid Toranjzar, Javad Varvani, Nourollah Abdi

“…This study aims to evaluate the potential habitat of Astragalus sp. using three different species distribution modeling methods: the maximum entropy (MaxEnt) model, the Genetic Algorithm for Rule-Set Production (GARP), and logistic regression. …”
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Investigating Feed-Forward Back-Propagation Neural Network with Different Hyperparameters for Inverse Kinematics of a 2-DoF Robotic Manipulator: A Comparative Study by Rania Bouzid, Jyotindra Narayan, Hassène Gritli

“…Thereafter, we train the FFBP-NN with the generated datasets using the MATLAB Neural Network Toolbox and investigate its potential by altering the hyperparameters (e.g., number of hidden neurons, number of hidden layers, and training optimizer). Three different training optimizers are considered, namely the Levenberg-Marquardt (LM) algorithm, the Bayesian Regularization (BR) algorithm, and the Scaled Conjugate Gradient (SCG) algorithm. …”
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Evaluating Sugarcane Yield Estimation in Thailand Using Multi-Temporal Sentinel-2 and Landsat Data Together with Machine-Learning Algorithms by Jaturong Som-ard, Savittri Ratanopad Suwanlee, Dusadee Pinasu, Surasak Keawsomsee, Kemin Kasa, Nattawut Seesanhao, Sarawut Ninsawat, Enrico Borgogno-Mondino, Filippo Sarvia

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Optimizing the Vegetation Health Index for Agricultural Drought Monitoring: Evaluation and Application in the Yellow River Basin by Qinghou Hang, Hao Guo, Xiangchen Meng, Wei Wang, Ying Cao, Rui Liu, Philippe De Maeyer, Yunqian Wang

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MOUD 2.0: a clinical algorithm and implementation evaluation protocol for sublingual and injectable buprenorphine treatment of opioid use disorder by Brandon L. Joa, Eric N. Fung, Michael S. Weinstein, Lara C. Weinstein, Lara C. Weinstein

“…We include a protocol for a future evaluation of the algorithm’s implementation process, “Medication for Opioid Use Disorder (MOUD) 2.0,” at a housing and integrated care clinic at a Federally Qualified Health Center.MethodsLiterature review and expert consensus informed creation of the algorithm, which underwent iterative development with feedback from clinicians, staff, and patients. …”
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Promoting or Hindering: The Impact of ESG Rating Differences on Energy Enterprises’ Green Transformation—A Causal Test from Double Machine-Learning Algorithms by Jun Wan, Yuejia Wang, Yuan Wang

“…There is a lack of comprehensive evaluation on the impact of ESG rating differences on the green transformation of energy enterprises in the transition era. …”
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Algorithm for assigning different 6-month short-term chemotherapy regimens in patients with drug-resistant tuberculosis: how to make the right choice for the clinician by Yu.I. Feshchenko, N.A. Lytvynenko, L.M. Protsyk, M.V. Pohrebna, Yu.O. Senko

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