Predicting Landing Position Deviation in Low-Visibility and Windy Environment Using Pilots’ Eye Movement Features by Xiuyi Li, Yue Zhou, Weiwei Zhao, Chuanyun Fu, Zhuocheng Huang, Nianqian Li, Haibo Xu

Get full text

Fault detection of key parts of wind turbine based on BP neural network combination prediction model by Jingjing Zhang, Liming Liu, Lei Wang, Wei Xi

Subjects: Get full text

Machine-Learning Assisted Prediction of Spectral Power Distribution for Full-Spectrum White Light-Emitting Diode by Jiajie Fan, Yutong Li, Irena Fryc, Cheng Qian, Xuejun Fan, Guoqi Zhang

“…Then, the Back Propagation (BP) and Genetic Algorithm-Back Propagation (GA-BP) NNs are proposed to predict the spectral characteristic parameters of LEDs operated under any usage conditions. …”
Get full text

A Novel Strategy Coupling Optimised Sampling with Heterogeneous Ensemble Machine-Learning to Predict Landslide Susceptibility by Yongxing Lu, Honggen Xu, Can Wang, Guanxi Yan, Zhitao Huo, Zuwu Peng, Bo Liu, Chong Xu

Subjects: “…landslide susceptibility prediction…”
Get full text

Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…Machine learning (ML) has demonstrated potential in predicting SSIs; however, the challenge of addressing imbalanced class ratios remains. …”
Get full text

Enhancing Heart Attack Prediction: Feature Identification from Multiparametric Cardiac Data Using Explainable AI by Muhammad Waqar, Muhammad Bilal Shahnawaz, Sajid Saleem, Hassan Dawood, Usman Muhammad, Hussain Dawood

Subjects: Get full text

Student dropout prediction through machine learning optimization: insights from moodle log data by Markson Rebelo Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, Rafael Targino, Vinicius Ramos, Emanuel Marques Queiroga, Roberto Munoz, Cristian Cechinel

“…In particular, we employed the CatBoost algorithm, trained on student activity logs from the Moodle platform. …”
Get full text

Predicting student performance academic using Automated Machine Learning (AutoML): in medical academic institutions by Rania A. Abougalala, Nouf Alharbi, Mohamed A. Amasha, Marwa F. Areed, Salem Alkhalaf, Dalia Khairy

“…Abstract Educational institutions seek to increase distinguished educational programs, and these programs increase costs and expenses of these institutions consuming a lot of their budget. …”
Get full text

Siamese Graph Convolutional Split-Attention Network with NLP based Social Sentimental Data for enhanced stock price predictions by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…Finally, a Graph Convolutional Split-Attention Network (SGCSAN) for promisingly predicting whether the stock prices are going to hit the ground and fly high again or is going to nosedive with Humboldt Squid Optimization Algorithm (HSOA) is introduced to further improve accuracy with lesser error generation. …”
Get full text

Multi-Condition Magnetic Core Loss Prediction and Magnetic Component Performance Optimization Based on Improved Deep Forest by Haotian Shi, Zipeng Jin

“…This paper proposes a core loss prediction model based on an improved deep forest algorithm and information entropy-enhanced genetic algorithm. …”
Get full text

Accurate Prediction of 327 Rice Variety Growth Period Based on Unmanned Aerial Vehicle Multispectral Remote Sensing by Zixuan Qiu, Hao Liu, Lu Wang, Shuaibo Shao, Can Chen, Zijia Liu, Song Liang, Cai Wang, Bing Cao

“…In this study, multispectral images of rice at various growth stages were captured using an unmanned aerial vehicle, and single-plant rice silhouettes were identified for 327 rice varieties by establishing a deep-learning algorithm. A growth stage prediction method was established for the 327 rice varieties based on the normalized vegetation index combined with cubic polynomial regression equations to simulate their growth changes, and it was first proposed that the growth stages of different rice varieties were inferred by analyzing the normalized difference vegetation index growth rate. …”
Get full text

Research on prediction of bottom hole flowing pressure for vertical coalbed methane wells based on improved SSA-BPNN by YU Yang, DONG Yintao, LI Yunbo, BAO Yu, ZHANG Lixia, SUN Hao

Subjects: “…|coalbed methane|sparrow search algorithm|neural network|bottom hole flowing pressure|prediction model…”
Get full text

An Adaptive Maximum Power Output Sustaining System for a Photovoltaic Power Plant Based on a Robust Predictive Control Approach by I. Elzein, Yu. N. Petrenko

“…This paper makes an emphasis on model predictive controller as a control method for controlling the maximum power point tracking through the utilization of the well-known algorithm namely the Perturb and Observe technique. …”
Get full text

Application of log-based specific surface area prediction for permeability modeling in a highly heterogeneous carbonate reservoir in the middle east by Mojtaba Homaie, Ida Lykke Fabricius, Morten Leth Hjuler, Asadollah Mahboubi, Ali Kadkhodaie, Reza Moussavi Harami

“…This study evaluates two log-based methodologies for specific surface modeling and their role in predicting permeability. The first method utilizes density and gamma-ray logs, as previously validated in North Sea chalks, while the second method innovatively integrates deep resistivity and porosity data using a K-nearest neighbor machine learning algorithm. …”
Get full text

Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

Subjects: Get full text

Cutting-edge approaches to specific energy prediction in TBM disc cutters: Integrating COSSA-RF model with three interpretative techniques by Jian Zhou, Zijian Liu, Chuanqi Li, Kun Du, Haiqing Yang

“…Therefore, in this paper, the sparrow search algorithm (SSA), combined with six chaotic mapping strategies, is utilized to optimize the random forest (RF) model for predicting SE, referred to as the COSSA-RF prediction models. …”
Get full text

Comparison of Univariate and Multivariate Applications of GBLUP and Artificial Neural Network for Genomic Prediction of Growth and Carcass Traits in the Brangus Heifer Population by Sunday O. Peters, Kadir Kızılkaya, Mahmut Sinecen, Milt G. Thomas

Subjects: “…genomic prediction…”
Get full text

Improved Pacific Decadal Oscillation Prediction by an Optimizing Model Combined Bidirectional Long Short-Term Memory and Multiple Modal Decomposition by Hang Yu, Junbo Lei, Pengfei Lin, Tao Zhang, Hailong Liu, Huilin Lai, Lindong Lai, Bowen Zhao, Bo Wu

Subjects: Get full text

Development of a Self-Updating System for the Prediction of Steel Mechanical Properties in a Steel Company by Machine Learning Procedures by Valerio Zippo, Elisa Robotti, Daniele Maestri, Pietro Fossati, David Valenza, Stefano Maggi, Gennaro Papallo, Masho Hilawie Belay, Simone Cerruti, Giorgio Porcu, Emilio Marengo

“…The proposed approach has a comprehensive connotation, starting from data pre-treatment and cleaning, to model building and prediction. Different machine learning algorithms are compared (Polynomial Regression, LASSO, Random Forests and Gradient Boosting, ANN, SVM, and k-NN), to provide the best predictive ability, also exploiting human reinforcement. …”
Get full text

Leveraging explainable artificial intelligence with ensemble of deep learning model for dementia prediction to enhance clinical decision support systems by Mohamed Medani, Ghada Moh. Samir Elhessewi, Mohammed Alqahtani, Somia A. Asklany, Sulaiman Alamro, Da’ad Albalawneh, Menwa Alshammeri, Mohammed Assiri

Subjects: Get full text