AI-Driven Predictive Maintenance in Mining: A Systematic Literature Review on Fault Detection, Digital Twins, and Intelligent Asset Management by Luis Rojas, Álvaro Peña, José Garcia

Subjects: “…predictive maintenance…”
Get full text

Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. …”
Get full text

Pathways to chronic disease detection and prediction: Mapping the potential of machine learning to the pathophysiological processes while navigating ethical challenges by Ebenezer Afrifa‐Yamoah, Eric Adua, Emmanuel Peprah‐Yamoah, Enoch O. Anto, Victor Opoku‐Yamoah, Emmanuel Acheampong, Michael J. Macartney, Rashid Hashmi

Subjects: Get full text

Feature Selection Using a Genetic Algorithms and Fuzzy logic in Anti-Human Immunodeficiency Virus Prediction for Drug Discovery by Houda Labjar, Mohammad Al-Sarem, Mohamed Kissi

“…This paper presents an approach that uses both genetic algorithm (GA) and fuzzy inference system (FIS), for feature selection for descriptor in a quantitative structure activity relationships (QSAR) classification and prediction problem. …”
Get full text

Unleashing quantum algorithms with Qinterpreter: bridging the gap between theory and practice across leading quantum computing platforms by Wilmer Contreras-Sepúlveda, Braulio Misael Villegas-Martínez, Sandra Gesing, José Javier Sánchez-Mondragón, Juan Carlos Sánchez-Pérez, Claudia Andrea Vidales-Basurto, J. Jesús Escobedo-Alatorre, Angel David Torres-Palencia, Omar Palillero-Sandoval, Jacob Licea-Rodriguez, Néstor Lozano-Crisóstomo, Julio César García-Melgarejo, Eddie Nelson Palacios-Perez

“…Due to the inherent complexity and divergence from classical computing, several major quantum computing libraries have been developed to implement quantum algorithms, namely IBM Qiskit, Amazon Braket, Cirq, PyQuil, and PennyLane. …”
Get full text

Algorithm for selecting predictors and prognosis of atrial fibrillation in patients with coronary artery disease after coronary artery bypass grafting by B. I. Geltser, K. I. Shakhgeldyan, V. Yu. Rublev, B. O. Shcheglov, E. A. Kokarev

“…These values in best model based on multivariate LR were lower (0,75; 0,7; 0,68 and 0,7, respectively).Conclusion. The developed algorithm for selecting predictors made it possible to verify significant predictive ranges and weight coefficients characterizing their influence on PAF development. …”
Get full text

Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems by Lihui Zheng, Xu Fan, Zongshan Kang, Xinjun Jin, Wenchao Zheng, Xiaofen Fang

“…Specifically, the VToMe algorithm achieves stable detection of medium to long term system faults, while the BiGRU network achieves rapid fault prediction in the short term. …”
Get full text

Charging pile fault prediction method combining whale optimization algorithm and long short-term memory network by Yansheng Huang, Atthapol Ngaopitakkul, Suntiti Yoomak

“…., the model optimization process stays in the non-optimal regional minimum) in complex parameter space, the study innovatively proposes a hybrid prediction model that combines the whale optimization algorithm with the gated recurrent unit-long short-term memory neural network. …”
Get full text

An Ultra-Short-Term Wind Power Prediction Method Based on the Fusion of Multiple Technical Indicators and the XGBoost Algorithm by Xuehui Wang, Yongsheng Wang, Yongsheng Qi, Jiajing Gao, Fan Yang, Jiaxuan Lu

“…However, its inherent volatility and unpredictability pose challenges for accurate short-term prediction. This study proposes an ultra-short-term wind power prediction framework that integrates multiple technical indicators with the extreme gradient boosting (XGBoost) algorithm. …”
Get full text

Prediction of Coiled Tubing Erosion Rate Based on Sparrow Search Algorithm Back-Propagation Neural Network Model by Yinping Cao, Fengying Fang, Guowei Wang, Wenyu Zhu, Yijie Hu

Subjects: Get full text

Parking Demand Prediction Method of Urban Commercial-Office Complex Buildings Based on the MRA-BAS-BP Algorithm by Xiang Tang, Jianxiao Ma, Shun Zhou, Tianci Shan

“…Hence, in this paper, a combined algorithm based on the MRA model, beetle antennae search (BAS) algorithm, and BP neural network is proposed for demand prediction. …”
Get full text

Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm by Xuehui Fan, Ruixue Ye, Yan Gao, Kaiwen Xue, Zeyu Zhang, Jing Xu, Jingpu Zhao, Jun Feng, Yulong Wang

Get full text

An integrated stacked convolutional neural network and the levy flight-based grasshopper optimization algorithm for predicting heart disease by Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Majad Mansoor, Filippo Sanfilippo

“…Accurate and early prediction of heart disease remains a significant challenge due to the complexity of symptoms and the variability of contributing factors. …”
Get full text

Prediction of Anthocyanin Content in Purple-Leaf Lettuce Based on Spectral Features and Optimized Extreme Learning Machine Algorithm by Chunhui Liu, Haiye Yu, Yucheng Liu, Lei Zhang, Dawei Li, Junhe Zhang, Xiaokai Li, Yuanyuan Sui

“…The results indicated the following: (1) For the feature band selection methods, the UVE-CARS-SNV-DBO-ELM model achieved an R_m² of 0.8623, an RMSE_m of 0.0098, an R_v² of 0.8617, and an RMSE_v of 0.0095, resulting in an RPD of 2.7192, further demonstrating that UVE-CARS enhances feature band extraction based on UVE and indicating a strong model performance. (2) For the vegetation index, VI3 showed a better predictive accuracy than VI2. The VI3-WOA-ELM model achieved an R_m² of 0.8348, an RMSE_m of 0.0109 mg/g, an R_v² of 0.812, an RMSE_v of 0.011 mg/g, and an RPD of 2.3323, demonstrating good performance. (3) For the optimization algorithms, the DBO, SABO, and WOA all performed well in optimizing the ELM model. …”
Get full text

RUL Prediction of Rolling Bearings Based on Fruit Fly Optimization Algorithm Optimized CNN-LSTM Neural Network by Jiaping Shen, Haiting Zhou, Muda Jin, Zhongping Jin, Qiang Wang, Yanchun Mu, Zhiming Hong

“…To address this challenge, this paper proposes a data-driven artificial neural network method, namely the CNN-LSTM bearing remaining life prediction model based on the fruit fly optimization algorithm (FOA). …”
Get full text

A Multi-Algorithm Machine Learning Model for Predicting the Risk of Preterm Birth in Patients with Early-Onset Preeclampsia by Xu Y, Zu Y, Zhang Y, Liang Z, Xu X, Yan J

“…Yanhong Xu,1,* Yizheng Zu,2,* Ying Zhang,1,* Zewei Liang,1 Xia Xu,1,3– 5 Jianying Yan1,3– 5 1College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, Fuzhou, Fujian, People’s Republic of China; 2The Affiliated Changzhou Second People’s Hospital of Nanjing Medical University, Changzhou, Jiangsu, People’s Republic of China; 3Fujian Clinical Research Center for Maternal-Fetal Medicine, Fuzhou, Fujian, People’s Republic of China; 4Laboratory of Maternal-Fetal Medicine, Fujian Maternity and Child Health Hospital, Fuzhou, Fujian, People’s Republic of China; 5National Key Obstetric Clinical Specialty Construction Institution of China, Fuzhou, Fujian, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xia Xu, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, No. 18 Daoshan Road, Gulou District, Fuzhou, Fujian, People’s Republic of China, Email xuxia0623@fjmu.edu.cn Jianying Yan, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University Fujian Maternity and Child Health Hospital, No. 18 Daoshan Road, Gulou District, Fuzhou, Fujian, People’s Republic of China, Email yanjy2019@fjmu.edu.cnPurpose: To analyze the risk factors for preterm birth in patients with early-onset preeclampsia (EOPE) based on multi-algorithm machine learning and to construct a predictive model to explore the predictive value of the model.Methods: A retrospective analysis was conducted on 442 EOPE patients from a single tertiary center, divided into preterm birth (< 37 weeks, n=358) and term-born (≥ 37 weeks, n=84) groups. …”
Get full text

From Crisis to Algorithm: Credit Delinquency Prediction in Peru Under Critical External Factors Using Machine Learning by Jomark Noriega, Luis Rivera, Jorge Castañeda, José Herrera

Get full text

Fatigue and stamina prediction of athletic person on track using thermal facial biomarkers and optimized machine learning algorithm by P. K. Santhosh, B. Kaarthick

Get full text

A Hybrid Internet of Behavior Algorithm for Predicting IoT Data of Plant Growing using LSTM and NB Models by Khansaa Yaseen Ahmad, Omar Muayad Abdullah

“…The researches that compare the accuracy between classical statistical prediction procedures and deep learning algorithms represent an important and modern field. …”
Get full text

A Short-Term Solar Photovoltaic Power Optimized Prediction Interval Model Based on FOS-ELM Algorithm by G. Ramkumar, Satyajeet Sahoo, T. M. Amirthalakshmi, S. Ramesh, R. Thandaiah Prabu, Kasipandian Kasirajan, Antony V. Samrot, A. Ranjith

“…The variance of model uncertainty is computed in the first stage by using a learning algorithm to provide predictable PV power estimations. …”
Get full text