PREDICTION OF TBM OIL TEMPERATURE BY IMPROVED CAMEL ALGORITHM ASSISTED RANDOM FOREST MODEL (MT) by REN JianJi, ZHAO RunQiu, WANG ZhenXi, LIU YuMing, YUAN YongLiang

“…Secondly, the improved camel algorithm was used to optimize the parameters of the TBM oil temperature prediction model established by the random forest to obtain the best model. …”
Get full text

Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using biomedical images by M. Eliazer, Sibi Amaran, K. Sreekumar, A. Vikram, Gyanendra Prasad Joshi, Woong Cho

“…Nowadays, researchers have begun to implement an image-processing model for analyzing jaundice. Paediatricians can detect and classify neonatal jaundice with machine learning (ML) and deep learning (DL) techniques. …”
Get full text

Predictions of Multilevel Linguistic Features to Readability of Hong Kong Primary School Textbooks: A Machine Learning Based Exploration by Zhengye Xu, Yixun Li, Duo Liu

“…For both publisher-assigned and teacher-rated readability, the all-level-feature-RF and character-level-feature-RF models performed the best. The top 10 predictive features of the two optimal models were analyzed. …”
Get full text

Advancements and challenges of artificial intelligence in climate modeling for sustainable urban planning by Teerachai Amnuaylojaroen

“…This Mini Review examines recent advancements in machine learning (ML) and deep learning (DL) techniques that improve climate risk assessment, resource optimization, and infrastructure resilience. …”
Get full text

Machine learning-enhanced near-infrared spectroscopy for high-throughput phenotyping of sweetpotato sugars across raw and cooked states by Chaochen Tang, Xueying Mo, Zhimin Ma, Zhangying Wang

“…Leveraging representative samples, characteristic spectral variables, and advanced learning algorithms, twelve optimal models were established for the four sugar indicators under three processing states. …”
Get full text

Building a composition-microstructure-performance model for C–V–Cr–Mo wear-resistant steel via the thermodynamic calculations and machine learning synergy by Shuaiwu Tong, Shuaijun Zhang, Chong Chen, Tao Jiang, Peng Li, Shizhong Wei

“…These findings contribute to the development of a composition-microstructure-performance model for C–V–Cr–Mo wear-resistant steel, supporting the rapid design and performance optimization of multi-component alloy steels, with significant potential for industrial application.…”
Get full text

Expanding the frontiers of additive manufacturing: Higher microstructure identification through probability modeling by Muhammad Shoaib, Muhammad Idrees, Hakeem Ullah, Aasim Ullah Jan, Touqeer Ahmad, Ali Akgül, Magda Abd El-Rahman, Seham M. Al-Mekhlafi

Get full text

Supervised Machine Learning Models for Predicting Sepsis-Associated Liver Injury in Patients With Sepsis: Development and Validation Study Based on a Multicenter Cohort Study by Jingchao Lei, Jia Zhai, Yao Zhang, Jing Qi, Chuanzheng Sun

“…A stacking ensemble model, using LightGBM, XGBoost, and RF as base learners and Lasso regression as the meta-model, was optimized via 10-fold cross-validation. …”
Get full text

A Bootstrapping Convolutional Neural Network Technique for Optimizing Automated Detection of Equatorial Plasma Bubbles by Optical All‐Sky Imagers by Daniel Okoh, Claudio Cesaroni, Babatunde Rabiu, Kazuo Shiokawa, Yuichi Otsuka, Samuel Ogunjo, Aderonke Akerele, John Bosco Habarulema, Bruno Nava, Yenca Migoya‐Orué, Punyawi Jamjareegulgarn, Adeniran Seun, Ogechi Adama, George Ochieng, James Ameh, Adero Awuor, Paul Baki

Get full text

Advancing computational evaluation of adsorption via porous materials by artificial intelligence and computational fluid dynamics by Heyder Mhohamdi, Usama S. Altimari, Krunal Vaghela, V. Vivek, Sarbeswara Hota, Devendra Singh, Mahesh Manchanda, Shirin Shomurotova, Prakhar Tomar, Mohammad Mahtab Alam

“…These findings underscore the practical utility of machine learning models, especially MLP, for accurate chemical concentration in environmental monitoring and process optimization with particular application for adsorption process.…”
Get full text

Introducing a Novel Method for Determining the Future Price of the Financial Markets: A Case Study of the Hang Seng Index by Afreen Akashi, Md Sanadiule Ullash, Apurba Das

“…This study seeks to address these challenges by developing an accurate hybrid forecasting model that integrates optimization algorithms with the CatBoost machine learning model. …”
Get full text

Enhancing Indoor mmWave Communication With ML-Based Propagation Models by Gustavo Adulfo Lopez-Ramirez, Alejandro Aragon-Zavala

“…With the advancement of 5G and emerging wireless communication technologies, accurate modeling of wave propagation in indoor environments has become increasingly crucial. …”
Get full text

Towards precision agriculture: metaheuristic model compression for enhanced pest recognition by Sana Parez, Norah Saleh Alghamdi, Tahir Mahmood, Waseem Ullah, Muhammad Attique Khan, Taha Houda, Naqqash Dilshad

Get full text

Artificial intelligence aided microwave coagulation therapy: Analysis of heat transfer to tumor tissue via hybrid modeling by Zheng Yang, KeWei Dai, Wujun Zhang, Rui Zhou, QingBin Wu, Liang Liu, HuaiRong Qu

“…We employed Massively Parallel Hyperparameter Tuning (MPPT) to optimize the hyperparameters for each model, ensuring optimal performance. …”
Get full text

Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study by Ahad Amini Pishro, Shiquan Zhang, Alain L’Hostis, Yuetong Liu, Qixiao Hu, Farzad Hejazi, Maryam Shahpasand, Ali Rahman, Abdelbacet Oueslati, Zhengrui Zhang

“…This paper introduces a novel classification model integrating traditional methodologies with advanced machine learning algorithms. …”
Get full text

Precision Soil Moisture Monitoring Through Drone-Based Hyperspectral Imaging and PCA-Driven Machine Learning by Milad Vahidi, Sanaz Shafian, William Hunter Frame

“…Our results demonstrate that PCA effectively detected critical variables for soil moisture estimation, with the ANN model outperforming other machine learning algorithms, including Random Forest (RF), Support Vector Regression (SVR), and Gradient Boosting (XGBoost). …”
Get full text

Machine Learning-Based State-of-Health Estimation of Battery Management Systems Using Experimental and Simulation Data by Anas Al-Rahamneh, Irene Izco, Adrian Serrano-Hernandez, Javier Faulin

Get full text

Eco-Friendly Shield Muck-Incorporated Grouting Materials: Mix Optimization and Property Evaluation for Silty Clay Tunnel Construction by Jinghui Yang, Mingyu Li, Shuai Ma, Mingzhe Xiao, Junwei Jin

Get full text

A Comparative Study of Mathematical Methods for Determining Colding’s Constants for Milling of Steels and Experimental Validation by Sujan Khadka, Rizwan Abdul Rahman Rashid, John H. Navarro-Devia, Angelo Papageorgiou, Guy Stephens, Sören Hägglund, Suresh Palanisamy

“…Overall, the findings demonstrate that Colding’s model, when applied with the appropriate computational method, can accurately optimize cutting parameters for different materials, contributing to more efficient and cost-effective machining processes.…”
Get full text

Revolutionizing heart attack prognosis: Introducing an innovative regression model for prediction by Hanaa Albanna, Madhav Raj Theeng Tamang, Chandan Patel, Mhd Saeed Sharif

“…The results demonstrated that even well-known models like Support Vector Machine and Logistic Regression can perform very well when applied to structured health data. …”
Get full text