Comparison of Machine Learning Methods (Linear Regression, Random Forest, and XGBoost) for Predicting Poverty in Central Java in 2024 by Zahwa Bunga Putri Pratama, Yani Parti Astuti

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Local Scour Around Marine Structures: A Comprehensive Review of Influencing Factors, Prediction Methods, and Future Directions by Bingchuan Duan, Duoyin Wang, Chenxi Qin, Lunliang Duan

“…Based on this, a comprehensive evaluation of the applicability of different prediction methods, including traditional empirical formulas, numerical simulations, probabilistic prediction models, and machine learning (ML) methods, was conducted. …”
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Non-Destructive Methods Based on Machine Learning for the Prediction of Sweet Potato Leaf Area: A Comparative Approach by Joao Everthon Da Silva Ribeiro, Ester Dos Santos Coelho, Antonio Gideilson Correia Da Silva, Pablo Henrique De Almeida Oliveira, Elania Freire Da Silva, Gisele Lopes Dos Santos, Anna Kezia Soares De Oliveira, John Victor Lucas Lima, Walter Esfrain Pereira, Lindomar Maria Da Silveira, Aurelio Paes Barros

“…They can be classified as destructive or non-destructive. The study evaluated the performance of five methods for predicting the leaf area of sweet potato cultivars, including simple linear regression, artificial neural networks, support vector regression, adaptive neuro-fuzzy inference system (ANFIS), and random forest (RF). …”
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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

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Predicting temporomandibular disorders in adults using interpretable machine learning methods: a model development and validation study by Yuchen Cui, Fujia Kang, Xinpeng Li, Xinning Shi, Han Zhang, Xianchun Zhu

“…Several evaluation indexes, including the area under the receiver-operating-characteristic curve (AUC), were used to compare the predictive performance. …”
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Group-Specific SVM With Bilevel Programming Methods for Parameter Optimization and Explainable AI in Urban Quality of Life Prediction by Gonzalo Rios-Vasquez, Hanns De La Fuente-Mella, Jose Ceroni-Diaz

“…This study introduces a novel machine learning-based approach incorporating bilevel programming methods to optimize predictive models for UQoL. A key contribution is the development of a Support Vector Machine (SVM) model for group-specific regression, enhanced by a bilevel programming reformulation that optimizes the hyperparameters of the model over groups of data. …”
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Identification of mitochondria-related feature genes for predicting type 2 diabetes mellitus using machine learning methods by Xiuping Xuan, Mingjin Sun, Donghui Hu, Chunli Lu

“…The prediction of candidate drugs targeting the feature genes were predicted using the DGIdb database. qRT-PCR was performed to access the mRNA expressions of the feature genes.ResultsFive mitochondria-related feature genes (SLC2A2, ENTPD3, ARG2, CHL1, and RASGRP1) were identified for type 2 diabetes mellitus prediction. …”
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Prediction of Hydrogen Production from Solid Oxide Electrolytic Cells Based on ANN and SVM Machine Learning Methods by Ke Chen, Youran Li, Jie Chen, Minyang Li, Qing Song, Yushui Huang, Xiaolong Wu, Yuanwu Xu, Xi Li

“…In recent years, the application of machine learning methods has become increasingly common in atmospheric science, particularly in modeling and predicting processes that impact air quality. …”
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Construction of a model for predicting sensory attributes of cosmetic creams using instrumental parameters based on machine learning by He Jingru, Qian Xuedan, Huang Hu, Lin Bao, Zhang Jun, Zhang Chunxiao, Chen Yuyan

“…This study aims to enhance the sensory evaluation of skin creams by using machine learning to predict sensory attributes based on instrumental parameters, addressing the limitations of conventional methods. …”
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CPT-DF: Congestion Prediction on Toll-Gates Using Deep Learning and Fuzzy Evaluation for Freeway Network in China by Tongtong Shi, Ping Wang, Xudong Qi, Jiacheng Yang, Rui He, Jingwen Yang, Yu Han

“…The congestion prediction method is designed including two modules: a deep learning (DL) prediction and a fuzzy evaluation. …”
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Application of Residual Shear Strength Predicted by Artificial Neural Network Model for Evaluating Liquefaction-Induced Lateral Spreading by Yanxin Yang, Bai Yang, Chunhui Su, Jianlin Ma

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Predicting Potential miRNA Targets for Antibody Glycosylation in CHO Cells Using a Simplified Evaluation Workflow by Patrick Schlossbauer, Florian Klingler, Friedemann Hesse

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JOINT ULTRASONOGRAPHY IN RHEUMATOID ARTHRITIS: PATHOGENETIC RATIONALE, POSSIBLE USE IN DIAGNOSIS, THERAPY EFFICIENCY EVALUATION, AND OUTCOME PREDICTION by O. G. Alekseeva

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Evaluation of ventilation and cooling strategies in cattle sheds in the middle and lower Yangtze river regions based on model prediction by Haoyuan Fang, Peishi Yan, Shengjuan Wei, Dengjin Chen

“…After verifying the model's accuracy, this study further predicted and evaluated the effects of ventilation and cooling strategies on shed thermal environments and the body heat balance of beef cattle in the region. …”
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Evaluation of conditional survival outcomes in patients with redefined anaplastic thyroid carcinoma by Yinuo Zheng, Yizhen Zhuang, Peng Zhou

“…Furthermore, after evaluation, the performance of our predictive model was found to be satisfactory.ConclusionUtilizing extensive SEER datasets, we devised and validated a CS-nomogram, enabling the prediction of the conditional probability of survival for rATC patients. …”
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The risk prediction models for cognitive frailty in the older people in China: a systematic review and meta-analysis by Minhua Ren, Hongtao Guo, Yingjie Guo, Wanjun Guo, Liangjin Zhu

“…Abstract Background Recently, many risk prediction models for Cognitive Frailty (CF) in older people in China have been developed. …”
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Extreme value prediction of the roll motion under random seas by Jie ZHU, Zailiang LIU, Yan LIN, Wei CHAI

“…The exceedance probability for the stochastic process X(t) at the critical level (e.g. the flooding angle), can be applied as an effective index to evaluate ship capsizing at seas. ConclusionExtreme value prediction of the roll motion by application of the ACER method could be an important reference to evaluate ship stability at seas.…”
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Evaluation of Spatial Interpolation Methods for Wind Speed and Direction: A Case Study in Split-Dalmatia County by M. Radić, L. Šerić, M. Bugarić

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Evaluation Methods for Stability and Analysis of Underlying Causes of Instability in Form I Atorvastatin Calcium Drug Substance by Bo Chen, Zhilong Tang, Zhenxing Zhu, Yang Xiao, Guangyao Mei, Xingchu Gong

“…Quantitative models based on PXRD, DSC, and near-infrared spectroscopy (NIRS) data were developed to predict amorphous content, and classification accuracy was evaluated. …”
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Potential for Evaluation of Interwell Connectivity under the Effect of Intraformational Bed in Reservoirs Utilizing Machine Learning Methods by Jinzi Liu

“…This paper provides a machine learning method to evaluate the connectivity between injection and production wells controlled by interlayer in reservoir. …”
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