Comparative Analysis of The Combined Model (Spatial and Temporal) and Regression Models for Predicting Murder Crime by Laith S. Ibrahim, Ghadeer Jasim Mohammed

“… This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. …”
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Predicting bankruptcy in construction business: Traditional model validation and formulation of a new model by Michal Karas, Pavla Srbová

Subjects: “…bankruptcy prediction model…”
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Adaptive opportunistic routing protocol based on forwarding-utility for delay tolerant networks by WANG Bo1, HUANG Chuan-he1, YANG Wen-zhong2

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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

“…Data from fifty participants, categorized as rearfoot and non-rearfoot strikers, were used to create personalized 3D foot models and finite element simulations. Two nine-axis inertial sensors captured three-axis acceleration data during running. …”
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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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Prediction of poor outcome in patients with acute liver failure-systematic review of prediction models. by Kama A Wlodzimirow, Saeid Eslami, Robert A F M Chamuleau, Martin Nieuwoudt, Ameen Abu-Hanna

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Comparative analysis and enhancing rainfall prediction models for monthly rainfall prediction in the Eastern Thailand by Preeyanuch Chuasuk, Tachanat Bhatrasataponkul, Aniruj Akkarapongtrakul

Subjects: “…The hybrid deep learning model in rainfall prediction…”
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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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Evaluation of the Risk Prediction Models in Predicting Kidney Outcomes in Antiglomerular Basement Membrane Disease by Huang Kuang, Yi-yang Zhao, Jin-wei Wang, Zhao Cui, Ming-hui Zhao, Xiao-yu Jia

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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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Predicting lung nodules malignancy by M. Jacob, J. Romano, D. Araújo, J.M. Pereira, I. Ramos, V. Hespanhol

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Digital generation in the context of predicting the professional future by E. F. Zeer, N. G. Tserkovnikova, V. S. Tretyakova

Subjects: “…professional future predicting model…”
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Emulsion stability prediction tool by Nor H. Halim, Sai R. Panuganti, Sanjay Misra, Jamal M.B.M. Ibrahim

“…A faster and safer alternative is by running a mathematical model. However, because of the complexity of emulsion system, an equation from first principles for predicting emulsion stability is not available even with such vast work in the literature. …”
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Predictive modeling for step II therapy response in periodontitis - model development and validation by Elias Walter, Tobias Brock, Pierre Lahoud, Nils Werner, Felix Czaja, Antonin Tichy, Caspar Bumm, Andreas Bender, Ana Castro, Wim Teughels, Falk Schwendicke, Matthias Folwaczny

“…Models accurately predicted that healthy sites stay healthy, but performed suboptimally for diseased sites. …”
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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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