Comparing the Estimation Power of Machine Learning Models and Statistical Models in Predicting Profit Component Changes and Selecting the Optimal Model by Maryam Izadi, Ali Ashtab, Akbar Zavari Rezaei

“…After confirming the non-normality of the average accuracy of machine learning and statistical models for profit components using the Kolmogorov-Smirnov test, the non-parametric Mann-Whitney U test was used to compare the predictive accuracy of machine learning models and statistical models in predicting the direction of changes in profit components. …”
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Prediction of chronic postsurgical pain in adults: a protocol for multivariable prediction model development by Christian Fynbo Christiansen, Lone Nikolajsen, Simon Haroutounian, Nicholas Papadomanolakis-Pakis

“…CPSP often interferes with activities of daily living and may have a negative impact on quality of life, emotional and physical well-being. Clinical prediction models can help clinicians target preventive strategies towards patients at high-risk of CPSP. …”
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Integrating personalized shape prediction, biomechanical modeling, and wearables for bone stress prediction in runners by Liangliang Xiang, Yaodong Gu, Kaili Deng, Zixiang Gao, Vickie Shim, Alan Wang, Justin Fernandez

“…The LSTM neural network with domain adaptation proved optimal for predicting bone stress in key foot bones—specifically the metatarsals, calcaneus, and talus—during the mid-stance and push-off phases (RMSE < 8.35 MPa). …”
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Model Predictive Control Using Stochastic Motion Prediction of Surrounding Vehicles in Uncontrolled Intersections by Sunyub Park, Yonghwan Jeong

“…This paper presents an autonomous driving algorithm for uncontrolled intersections based on Model Predictive Control (MPC) and Interacting Multiple Model (IMM) filters, proposing an innovative approach to addressing human driver uncertainty in mixed traffic scenarios. …”
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Ground data analysis for PM2.5 Prediction using predictive modeling techniques by Elham Nourmohammad, Yousef Rashidi

“…Conclusion: The findings highlight the importance of model selection and feature engineering in accurately predicting PM2.5 levels. …”
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MNPM: research on metabolic neural network prediction model for predicting carbon emission accuracy by Entao Luo, Li Shi, Jiyan Liu, Zheng Wu, Guoyun Duan, Lingxuan Zeng, Tangsen Huang

Subjects: “…gray model…”
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Dynamic selection of optimal tunnel convergence prediction model for a probabilistic deformation prediction by Peng ZENG, Zhiqiang ZHANG, Tianbin LI, Hao Tang, Zulong YAN, Lubo MENG

“…Traditional single prediction models struggle to adapt to the dynamic nature of tunnel convergence, limiting their predictive accuracy. …”
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Enhanced Prediction and Uncertainty Modeling of Pavement Roughness Using Machine Learning and Conformal Prediction by Sadegh Ghavami, Hamed Naseri, Farzad Safi Jahanshahi

“…Pavement performance models are considered a key element in pavement management systems since they can predict the future condition of pavements using historical data. …”
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Vehicle Trajectory Prediction Algorithm Based on Hybrid Prediction Model with Multiple Influencing Factors by Tao Wang, Yiming Fu, Xing Cheng, Lin Li, Zhenxue He, Yuchi Xiao

“…In light of this limitation, we propose a vehicle trajectory prediction algorithm predicated on a hybrid prediction model. …”
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Evaluation of predictive maintenance efficiency with the comparison of machine learning models in machining production process in brake industry by Can Aydın, Burak Evrentuğ

“…The findings highlight the importance of data preprocessing and advanced modeling techniques in predictive maintenance and emphasize how addressing data challenges can enhance the overall performance and reliability of ML models.…”
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Prediction of Solar Radiation Data for Garlic Production in Magelang Regency Using Long Short-Term Memory by Muhammad Safrul Safrudin, Imas Sukaesih Sitanggang, Hari Agung Adrianto, Syarifah Aini

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Editorial: Tropical cyclone modeling and prediction: advances in model development and its applications by Xuejin Zhang, Vijay Tallapragada, Zhan Zhang, Avichal Mehra

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Topside Electron Density Modeling Using Neural Network and Empirical Model Predictions by S. Dutta, M. B. Cohen

“…In prior work, an artificial neural network (NN) was developed and trained on two solar cycles worth of Defense Meteorological Satellite Program data (113 satellite‐years), along with global drivers and indices to predict topside electron density. In this paper, we highlight improvements made to this NN, and present a detailed comparison of the new model to E‐CHAIM and IRI as a function of location, geomagnetic condition, time of year, and solar local time. …”
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Article 700 Identification in Judicial Judgments: Comparing Transformers and Machine Learning Models by Sid Ali Mahmoudi, Charles Condevaux, Guillaume Zambrano, Stéphane Mussard

“…Predictive justice, which involves forecasting trial outcomes, presents significant challenges due to the complex structure of legal judgments. …”
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Prediction of postpartum depression in women: development and validation of multiple machine learning models by Weijing Qi, Yongjian Wang, Yipeng Wang, Sha Huang, Cong Li, Haoyu Jin, Jinfan Zuo, Xuefei Cui, Ziqi Wei, Qing Guo, Jie Hu

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Predictive performance of risk prediction models for lung cancer incidence in Western and Asian countries: a systematic review and meta-analysis by Yah Ru Juang, Lina Ang, Wei Jie Seow

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Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients by Felipe Cisternas-Caneo, María Santamera-Lastras, José Barrera-Garcia, Broderick Crawford, Ricardo Soto, Cristóbal Brante-Aguilera, Alberto Garcés-Jiménez, Diego Rodriguez-Puyol, José Manuel Gómez-Pulido

“…This study examines the application of advanced machine learning techniques, combined with metaheuristic optimization methods, to improve predictive models for intradialytic hypotension (IDH) in hemodialysis patients. …”
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Improving appendix cancer prediction with SHAP-based feature engineering for machine learning models: a prediction study by Ji Yoon Kim

“…Purpose This study aimed to leverage Shapley additive explanation (SHAP)-based feature engineering to predict appendix cancer. Traditional models often lack transparency, hindering clinical adoption. …”
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Prediction of blossoming of apple tree (Malus domestica Borkh) BY phenological models by Lučka KAJFEŽ-BOGATAJ, Klemen BERGANT

“… Paper discusses the possibilities for predicting date of blossom of apple tree (Malus domestica Borkh) cv. …”
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Determinants Factors in Predicting Life Expectancy Using Machine Learning by B. Kouame Amos, I. V. Smirnov

“…However, with the existence of various conditions and complications witnessed in society today, several factors need to be taken into consideration to predict life expectancy. Therefore, various machine learning models have been developed to predict life expectancy.   …”
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