Analysis of Optimal Prediction Under Stochastically Restricted Linear Model and Its Subsample Models by Nesrin Güler

“…This paper provides a study on optimal prediction problems in a linear model and its subsample models with linear stochastic restrictions, using matrix theory for precise analytical solutions. …”
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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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Engine Optimization Model for Accurate Prediction of Friction Model in Marine Dual-Fuel Engine by Mina Tadros

“…The focus is on determining the terms of the Chen–Flynn correlation—an empirical engine friction model—to improve the precision of friction and performance predictions. …”
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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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Research on Deformation Prediction Surrogate Model of Thin-walled Parts for Digital Twin Modeling by YUE Caixu, ZHANG Jiahao, XIA Wei, JIA Ruhong, GUO Yandong, LIU Xianli

Subjects: “…machining deformation prediction…”
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Prediction Model for Compaction Quality of Earth-Rock Dams Based on IFA-RF Model by Weiwei Lin, Yuling Yan, Pu Xu, Xiao Zhang, Yichuan Zhong

“…Additionally, the existing models frequently demonstrate constrained prediction accuracy and generalization capabilities. …”
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Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator by Min Huang, Huiying Zhang, Kangan Wang, Zhilei Yao, Weimin Wu

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Forecasting Referendums: A Structural Model Predicting Adoption and Support in Irish Plebiscites 1968–2024 by Stephen Quinlan, Michael S. Lewis-Beck, Matt Qvortrup

“…Election prediction flourishes among pollsters, the media, academics, and political anoraks, with four significant prognostic paradigms: opinion polls, markets, structural models, and hybrid approaches. …”
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Transitioning from Simulation to Reality: Applying Chatter Detection Models to Real-World Machining Data by Matthew Alberts, Sam St. John, Simon Odie, Anahita Khojandi, Bradley Jared, Tony Schmitz, Jaydeep Karandikar, Jamie B. Coble

“…The study applies a Random Forest classification model trained on over 140,000 simulated machining datasets, incorporating techniques like Operational Modal Analysis (OMA), Receptance Coupling Substructure Analysis (RCSA), and Transfer Learning (TL) to adapt the model for real-world operational data. …”
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Prognosis of Pediatric Dilated Cardiomyopathy: Nomogram and Risk Score Models for Predicting Death/Heart Transplantation by Bowen Xu, Yue Yuan, Lu Gao, Zhiyuan Wang, Zhenyu Lv, Wen Yu, Hongfang Jin, Zhen Zhen, Zhihui Zhao, Jia Na, Aihua Hu, Yanyan Xiao

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Modelling chelate-Induced phytoextraction: functional models predicting bioavailability of metals in soil, metal uptake and shoot biomass by Pasqualina Sacco, Fabrizio Mazzetto, Luca Marchiol

“…Contrariwise, the distribution strategy (single vs. split application) seems to produce significant differences both in plant growth and metal uptake, but not in soil metal bioavailability. The proposed models may help to understand and predict the chelate dose – effect relationship with less experimental work.…”
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What the Taylor Rule Predicts for the Case of Turkiye by Osman Cenk Kanca

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Explainable machine learning to predict the cost of capital by Niklas Bussmann, Paolo Giudici, Paolo Giudici, Alessandra Tanda, Alessandra Tanda, Ellen Pei-Yi Yu

“…Our findings pave the way for future investigations on the impact of ESG and country factors in predicting the cost of capital.…”
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Ephemeral gullies. A spatial and temporal analysis of their characteristics, importance and prediction by Jeroen Nachtergaele, Jean Poesen, Gerard Govers

“…This study, therefore, aimed at:1) describing spatial and temporal variations in ephemeral gully characteristics, in three contrasting environments;2) extending the existing studies on the importance of ephemeral gully erosion in space and time by using high-altitude stereo aerial photos (HASAP) to assess ephemeral gully volumes;3) improving ephemeral gully prediction, through the development of both empirical relationships to directly predict ephemeral gully volumes and process-oriented relationships to be built in physically-based erosion models;4) evaluating the medium to long-term evolution of an (ephemeral) gully.…”
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Spatial Variables and Land Use Change Models: A Study on Conditioning Patterns of Natural Vegetation Suppression and Persistence by Macleidi Varnier, Eliseu José Weber

Subjects: “…Predictive variables…”
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First-Order Decay Models for the Estimation of Methane Emissions in a Landfill in the Metropolitan Area of Oaxaca City, Mexico by Pérez Belmonte Nancy Merab, Sandoval Torres Sadoth, Belmonte Jiménez Salvador Isidro

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Traffic Signal Optimization in Large-Scale Urban Road Networks: An Adaptive-Predictive Controller Using Ising Models by Daisuke Inoue, Hiroshi Yamashita, Kazuyuki Aihara, Hiroaki Yoshida

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DeepPredict: a state-of-the-art web server for protein secondary structure and relative solvent accessibility prediction by Wafa Alanazi, Wafa Alanazi, Di Meng, Gianluca Pollastri

Subjects: “…protein structure prediction…”
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Predicting biking preferences in Kigali city: A comparative study of traditional statistical models and ensemble machine learning models by Jean Marie Vianney Ntamwiza, Hannibal Bwire

“…This research used a dataset of 6386 observations incorporated weather and air quality variables and applied correlation-based and iterative model-based feature selection techniques to improve predictive accuracy. …”
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Development and validation of hybrid machine learning approach for predicting survival in patients with cervical cancer: a SEER-based population study by Anjana Eledath Kolasseri, Venkataramana B.

“…The study aims to create a hybrid survival model that integrates Cox Proportional Hazards (CoxPH) with Elastic Net regularization and Random Survival Forest (RSF) to improve prediction accuracy and interpretability.MethodsData from the SEER database (2013–2015) were pre-processed through normalization and encoding. …”
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