Evaluation of different erosion models for predicting guide vane wear in Francis turbine by Rakish Shrestha, Rakish Shrestha, Kushal Shrestha, Kushal Shrestha, Sailesh Chitrakar, Sailesh Chitrakar, Bhola Thapa, Hari Prasad Neopane, Zhongdong Qian, Zhiwei Guo

“…By dividing the CG into sections and comparing the erosion predictions by different erosion models with the actual erosion, Finnie erosion model is found to be the most suitable model for this application. …”
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Comparison of Machine Learning and Deep Learning Models Performance in predicting wind energy by Saswati Rakshit, Anal Ranjan Sengupta

“…This study leverages advanced machine learning (ML) and some other statistical and deep learning based time series forecasting models to enhance the accuracy of wind energy predictions. …”
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Predicting Sentiments in Spotify Comments: A Comparative Analysis of Machine Learning Models by Filipe Augusto Felix de Queiroz, Igor Barbosa Negreiros, Giovana de Souza, Débora Cordeiro de Sousa, Sílvio Fernando Alves Xavier Júnior

“…We compare different statistical modeling and Machine Learning techniques, identifying the ones with the greatest accuracy in predicting sentiments. …”
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Predicting in-hospital mortality in ICU patients with lymphoma using machine learning models. by Ling Xu, Guang Tu, Zhonglan Cai, Tianbi Lan

“…Machine learning (ML) models offer a more accurate alternative for predicting outcomes by analyzing large datasets. …”
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Predicting transient response using data-driven models for ball-impact simulations by Ross Pivovar, Fei Chen, Raghunath Katragadda, Vidyasagar Ananthan

“…This study investigates the application of machine learning (ML) models for predicting transient responses in ball-impact elastodynamics simulations. …”
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Machine Learning Models for Predicting Mortality in Hemodialysis Patients: A Systematic Review by Alexandru Catalin Motofelea, Adelina Mihaescu, Nicu Olariu, Luciana Marc, Lazar Chisavu, Gheorghe Nicusor Pop, Andreea Crintea, Ana Maria Cristina Jura, Viviana Mihaela Ivan, Adrian Apostol, Adalbert Schiller

“…This systematic review and meta-analysis aimed to evaluate and compare the performance of various machine learning (ML) models in predicting mortality among HD patients. …”
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Predicting Dilution in Underground Mines with Stacking Artificial Intelligence Models and Genetic Algorithms by Jorge L. V. Mariz, Tertius S. G. Ferraz, Marinésio P. Lima, Ricardo M. A. Silva, Hyongdoo Jang

“…Furthermore, four stacking models were constructed by aggregating the top-performing base learners, giving rise to ensemble metamodels applied, for the first time, to the task of dilution prediction in underground mining.…”
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Transport models for predicting spontaneous ignition of pressurized hydrogen released into a tube by Gang Luo, Wenping Zhang, Zixuan Yang, Lijing Zhang, Jinfeng Zhang

“…In this paper, OpenFOAM is employed to study three different transport models for predicting spontaneous ignition of pressurized hydrogen released into a tube. …”
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Performance of deep learning models in predicting the nugent score to diagnose bacterial vaginosis by Naoki Watanabe, Tomohisa Watari, Kenji Akamatsu, Isao Miyatsuka, Yoshihito Otsuka

“…This study aimed to evaluate the performance of deep learning models in predicting the Nugent score to improve diagnostic consistency and accuracy. …”
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LLM-Prop: predicting the properties of crystalline materials using large language models by Andre Niyongabo Rubungo, Craig Arnold, Barry P. Rand, Adji Bousso Dieng

“…Current methods for predicting crystal properties focus on modeling crystal structures using graph neural networks (GNNs). …”
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Machine learning models for predicting multimorbidity trajectories in middle-aged and elderly adults by Li Yao, Qiaoxing Li, Zihan Zhou, Jiajia Yin, Tingrui Wang, Yan Liu, Qinqin Li, Lu Xiao, Dongliang Yang

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Predicting Response to Transarterial Chemoembolization in Hepatocellular Carcinoma Using Machine Learning Models by Niharika Dutta, Pankaj Gupta

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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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A vision-language model for predicting potential distribution land of soybean double cropping by Bei Gao, Yuefeng Liu, Yanli Li, Hongmei Li, Meirong Li, Wenli He

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“Revealing the future”: an ARIMA model analysis for predicting remittance inflows by Imran Khan, Darshita Fulara Gunwant

“…Purpose – The purpose of this research is to develop a predictive model that can estimate the volume of remittances channeled toward Yemen’s economic reconstruction efforts. …”
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Predicting Excavation-Induced Tunnel Response by Process-Based Modelling by Linlong Mu, Jianhong Lin, Zhenhao Shi, Xingyu Kang

“…To illustrate such a concept, this paper presents a simple process-based model consisting of artificial neural network (ANN) module, inverse modelling module, and mechanistic module. …”
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A structure-based model for predicting serum albumin binding. by Katrina W Lexa, Elena Dolghih, Matthew P Jacobson

“…This model was successfully used to predict serum albumin binding in a large test set of therapeutics that had experimental binding data.…”
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Generalized Additive Model for Predicting ECBR of Stabilized Subgrades for Pavement by Alka Shah, Tejaskumar Thaker, Vipin Shukla

“…This study presents a Generalized Additive Model (GAM) to predict the effective CBR (ECBR) of soil subgrade stabilized with recycled plastic waste under repeated loading (RL) conditions. …”
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Clinical validation of a model predicting the risk of preterm delivery. by Yohann Dabi, Sophie Nedellec, Claire Bonneau, Blandine Trouchard, Roman Rouzier, Alexandra Benachi

“…<h4>Objectives</h4>To validate a model predicting the risk of threatened preterm delivery and to establish the optimal threshold for this risk scoring system.…”
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Integrated Cox’s model for predicting survival time of glioblastoma multiforme by Zhibing Ai, Longti Li, Rui Fu, Jing-Min Lu, Jing-Dong He, Sen Li

“…Patients were separated into two groups by using 1 year as a cutoff, and a logistic regression model was used to figure out any variables that can predict whether the patient was able to live longer than 1 year. …”
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