Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

“…Abstract This study presents a comparative analysis of hybrid Extreme Learning Machine (ELM) models optimized with metaheuristic algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO) for real-time Rate of Penetration (ROP) prediction in drilling operations. …”
Get full text

Empirical research on the diffusion effect of ICT innovation diffusion and prediction in China by Wenyu HU, Wenju WANG

Subjects: Get full text

Prediction and Monitoring Model of Concrete Dam Deformation Based on WOA-RFR by FENG Yu, WU Yunxing, GU Wenjing, PANG Qiong, GU Yanchang, CHEN Siyu

Subjects: Get full text

Predictive dynamic multi-flow routing (PD-MFR) algorithm towards sixth generation (6G) software-defined networks by Buse Pehlivan, Volkan Rodoplu, Engincan Tunçay, Dilara Eraslan

“…We develop a dynamic Quality of Service (QoS) routing algorithm based on network traffic prediction for Sixth Generation (6G) SDNs. …”
Get full text

Development and Validation of a Neonatal Hypothermia Prediction Model for In-Hospital Transport Using Machine Learning Algorithms: A Single-Center Retrospective Study by Zhang W, Gu X, Gu C, Yao L, Zhang Y, Wang K

“…Six machine learning algorithms—Decision Tree (DT), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Artificial Neural Network (ANN), and Naive Bayes (NB)—were used to develop predictive models. …”
Get full text

Optimizing Equivalent Property-Damage-Only (EPDO) Prediction Models with Genetic Algorithms: A Case Study on Roundabout Geometric Characteristics by Hossein Samadi, Omid Rahmani, Khaled Shaaban, Amir Saman Abdollahzadeh Nasiri, Mehrzad Hasanvand

Subjects: “…crash prediction model…”
Get full text

Quantum algorithms for enhanced educational technologies by Basil Hanafi, Mohammad Ali, Devyaani Singh

Subjects: Get full text

Machine learning algorithms as early diagnostic tools for prolonged operative time in patients with fluorescent laparoscopic cholecystectomy: a retrospective cohort study by Chu Wang, Chu Wang, JunYe Wen, ZiYi Su, HanXiang Yu

Get full text

Parallelizing process model integration for model predictive control through oracle design and analysis for a Grover’s algorithm-inspired optimization strategy by Kip Nieman, Helen Durand, Saahil Patel, Daniel Koch, Paul M. Alsing

Subjects: Get full text

Machine learning-based coalbed methane well production prediction and fracturing parameter optimization by HU Qiujia, LIU Chunchun, ZHANG Jianguo, CUI Xinrui, WANG Qian, WANG Qi, LI Jun, HE Shan

Subjects: “…|coalbed methane|random forest algorithm|multi-task learning|particle swarm optimization algorithm|production prediction|fracturing parameter optimization…”
Get full text

Optimizing Traffic Speed Prediction Using a Multi-Objective Genetic Algorithm-Enhanced RNN for Intelligent Transportation Systems by C. Swetha Priya, F. Sagayaraj Francis

“…Additionally, we developed a Multi-Objective Genetic Algorithm (MOGA)-enhanced RNN model to optimize hyperparameters and achieve accurate traffic speed predictions. …”
Get full text

iMLGAM: Integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis for pan‐cancer immunotherapy response prediction by Bicheng Ye, Jun Fan, Lei Xue, Yu Zhuang, Peng Luo, Aimin Jiang, Jiaheng Xie, Qifan Li, Xiaoqing Liang, Jiaxiong Tan, Songyun Zhao, Wenhang Zhou, Chuanli Ren, Haoran Lin, Pengpeng Zhang

“…Abstract To address the substantial variability in immune checkpoint blockade (ICB) therapy effectiveness, we developed an innovative R package called integrated Machine Learning and Genetic Algorithm‐driven Multiomics analysis (iMLGAM), which establishes a comprehensive scoring system for predicting treatment outcomes through advanced multi‐omics data integration. …”
Get full text

A machine learning-based prediction of diabetic retinopathy using the Korea national health and nutrition examination survey (2008–2012, 2017–2021) by Min Seok Kim, Young Wook Choi, Borghare Shubham Prakash, Youngju Lee, Soo Lim, Se Joon Woo

Subjects: Get full text

Trustworthy Load Prediction for Cantilever Roadheader Robot Without Imputation by Pengjiang Wang, Yuxin Li, Yunwang Li, Yang Shen, Weixiong Zheng, Shigen Fu

Subjects: Get full text

Prediction of Insulator ESDD Based on Meteorological Feature Mining and AdaBoost-MEA-ELM Model by Yaoping WANG, Te LI, Kaihua JIANG, Wenhui LI, Qiang WU, Yu WANG

Subjects: “…esdd prediction…”
Get full text

Optimizing knee osteoarthritis severity prediction on MRI images using deep stacking ensemble technique by Punita Panwar, Sandeep Chaurasia, Jayesh Gangrade, Ashwani Bilandi, Dayananda Pruthviraja

“…In the present investigation, four pre-trained models, specifically CNN, AlexNet, ResNet34 and ResNet-50, were utilized to predict the severity of KOA. Further, a Deep stack ensemble technique was employed to achieve optimal performance resulting to the accuracy of 99.71%.…”
Get full text

Identifying the Latitude and Longitude of ATMs in ATM Networks by Niloofar Haghjoo, Mohammad rahmati, Ali Zare Mirakabad

Subjects: “…atm location prediction algorithm…”
Get full text

Design and Analysis of an MPC-PID-Based Double-Loop Trajectory Tracking Algorithm for Intelligent Sweeping Vehicles by Zhijun Guo, Mingtian Pang, Shiwen Ye, Yangyang Geng

“…To enhance the precision and real-time performance of trajectory tracking control in differential-steering intelligent sweeping robots and to improve the adaptability of the control algorithm to errors caused by sensor noise, tire slip, and skid, an MPC-PID (Model Predictive Control–Proportional-Integral-Derivative) dual closed-loop control strategy was proposed. …”
Get full text

Research on Slope Stability Prediction Based on MC-BKA-MLP Mixed Model by Yan Lu, Hongze Zhao

“…Subsequently, a novel Black Kite Algorithm (BKA) was developed to enhance the prediction model of a multilevel perceptron neural network. …”
Get full text

Robust Parameter Inversion and Subsidence Prediction for Probabilistic Integral Methods in Mining Areas by Xinjian Fang, Rui Yang, Mingfei Zhu, Jinling Duan, Shenshen Chi

“…A critical challenge in subsidence prediction lies in the sensitivity of existing probabilistic integral parameter inversion methods to gross errors, leading to unstable predictions and compromised reliability. …”
Get full text