Surface Roughness Prediction of Bearing Ring Precision Grinding Based on Feature Extraction by Chaoyu Shi, Bohao Chen, Yao Shi, Jun Zha

“…In order to improve the surface roughness of bearing ring grinding under multiple working conditions, a prediction model of bearing ring surface roughness based on feature extraction was proposed. …”
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Integration of SimWeight and Markov Chain to Predict Land Use of Lavasanat Basin by M S. Mirakhorlo, M. Rahimzadegan

“…Production and prediction of land-use/land cover changes (LULCC) map are among the significant issues regarding input of many environmental and hydrological models. …”
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Predicting patient deterioration with physiological data using AI: systematic review protocol by Chris Plummer, Edward Meinert, Victoria Riccalton, Lynsey Threlfall, Cen Cong

“…This systematic review aims to establish which AI or machine learning algorithm is best suited to analysing physiological data sets to predict patient deterioration in a hospital setting.Methods and analysis A systematic review will be conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) and the PICOS (Population, Intervention, Comparator, Outcome and Study) frameworks. …”
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Data efficient prediction of excited-state properties using quantum neural networks by Manuel Hagelueken, Marco F Huber, Marco Roth

“…We present a quantum machine learning model that predicts excited-state properties from the molecular ground state for different geometric configurations. …”
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Deep learning-based time series prediction for precision field crop protection by Tao He, Meijin Li, Dong Jin

“…We introduce the Resource-Aware Adaptive Decision Algorithm (RAADA), which leverages reinforcement learning to translate SADF-Net’s predictions into optimized strategies for resource allocation, such as irrigation scheduling and pest control. …”
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A nomogram for predicting small bowel mucosal healing in pediatric Crohn’s disease by Bingxia Chen, Huiwen Li, Hongli Wang, Lu Ren, Liya Xiong, Yang Cheng, Rui Li, Meiwan Cao, Zihuan Zeng, Sitang Gong, Peiyu Chen, Lanlan Geng

“…The least absolute shrinkage and selection operator (LASSO) logistic regression algorithm was applied to identify predictive factors for small bowel MH. …”
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Prediction of rock burst risk in underground openings based on intuitionistic fuzzy set by Xin Wang, Kebin Shi, Quan Shi, Heng Zhang, Liqiang Bai

“…In this paper, a model for risk prediction of rock burst is proposed based on intuitionistic fuzzy set theory. …”
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Neural network for prediction solar radiation in Relizane region (Algeria) - Analysis study by Dahmani Abdennasser, Yamina Ammi, Salah Hanini

“…The global solar radiation prediction is the most necessary part of the project and performance of solar energy applications. …”
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Recurrence Multilinear Regression Technique for Improving Accuracy of Energy Prediction in Power Systems by Quota Alief Sias, Rahma Gantassi, Yonghoon Choi, Jeong Hwan Bae

“…This paper also creates a pre-clustering using the K-Means algorithm before the energy prediction to improve accuracy. …”
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Application of phase analysis to predict long-term dynamics of atmospheric air temperature by L.  T. Sozaeva

“…Further prediction of the values of the time series in the retrospective section is carried out by the least square method. …”
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Deep spatio-temporal dependent convolutional LSTM network for traffic flow prediction by Jie Tang, Rong Zhu, Fengyun Wu, Xuansen He, Jing Huang, Xianlai Zhou, Yishuai Sun

“…Secondly, for time features, most scholars use time series prediction models, such as recurrent neural networks and their variants. …”
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Rockburst Prediction Based on the KPCA-APSO-SVM Model and Its Engineering Application by Yuefeng Li, Chao Wang, Jiankun Xu, Zonghong Zhou, Jianhui Xu, Jianwei Cheng

“…The comparative results show that the KPCA-APSO-SVM model has a higher prediction accuracy; as such, it provides a new reliable method for rockburst prediction.…”
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Hybridized Deep Learning Model for Perfobond Rib Shear Strength Connector Prediction by Jamal Abdulrazzaq Khalaf, Abeer A. Majeed, Mohammed Suleman Aldlemy, Zainab Hasan Ali, Ahmed W. Al Zand, S. Adarsh, Aissa Bouaissi, Mohammed Majeed Hameed, Zaher Mundher Yaseen

“…Accurate and reliable prediction of Perfobond Rib Shear Strength Connector (PRSC) is considered as a major issue in the structural engineering sector. …”
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Fatigue life prediction and stresses applicability of TBCs by the virtual S-N curve method by Changcheng Xie, Chao Ma, Changhao Wang, Yudong Yao, Pinbo Huang

“…Finally, the errors of different stresses for TBCs life prediction are analyzed in conjunction with the particle swarm algorithm, and the stress with the best applicability is identified and verified experimentally. …”
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Electric Vehicle Charging Station Planning Method Based on System Dynamics Prediction by YANG Nan, LIANG Pengcheng, HUANG Yuehua, ZHANG Lei, GE Zhichao, LI Huangqiang, XIN Peizhe, SHEN Ran

“…In addition， by incorporating the increase in EV ownership predicted through SD prediction as opposed to relying on a fixed ownership model， the proposed planning method leads to higher costs and total income. …”
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Prediction of environmental suitability for Haematoxylum campechianum: A proposal to promote reforestation in Mexico by Anay Serrano-Rodríguez, Annery Serrano Rodríguez, Yarelys Ferrer-Sánchez, Fernando Abasolo-Pacheco, Mariela Alexi Díaz Ponce, Norma María Guerrero Chuez, Pedro Harrys Lozano Mendoza, Alexis Herminio Plasencia-Vázquez

“…Models of potential distribution and ecological niche allow to estimate priority areas for the management of species of interest, as well as to identify variables related to environmental suitability and predict the behavior of species in the face of anthropogenic disturbances. …”
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Method of investigating thermal fluctuation processes in problems of diagnostics and prediction of insulating materials by Marina N. Dubyago, Nikolay K. Poluyanovich, Vyacheslav Kh. Pshikhopov

“…That makes it possible to combine two control techniques - prediction of the growing insulation defect and nondestructive testing of the thermal fluctuation processes of a power cable - in one measuring tool. …”
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A metaheuristic optimization-based approach for accurate prediction and classification of knee osteoarthritis by Amal G. Diab, El-Sayed M. El-Kenawy, Nihal F. F. Areed, Hanan M. Amer, Mervat El-Seddek

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Research on shale TOC prediction method based on improved BP neural network by Chaorong Wu, Kaixing Huang, Zhengtao Sun, Yizhen Li, Yong Li, Yuexiang Hao, Zhengxing Sun, Ziqi Wang

“…This paper studies a method for predicting shale TOC content using a BP neural network optimized by an improved cuckoo search algorithm. …”
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Access control relationship prediction method based on GNN dual source learning by Dibin SHAN, Xuehui DU, Wenjuan WANG, Aodi LIU, Na WANG

“…With the rapid development and wide application of big data technology, users’ unauthorized access to resources becomes one of the main problems that restrict the secure sharing and controlled access to big data resources.The ReBAC (Relationship-Based Access Control) model uses the relationship between entities to formulate access control rules, which enhances the logical expression of policies and realizes dynamic access control.However, It still faces the problems of missing entity relationship data and complex relationship paths of rules.To overcome these problems, a link prediction model LPMDLG based on GNN dual-source learning was proposed to transform the big data entity-relationship prediction problem into a link prediction problem with directed multiple graphs.A topology learning method based on directed enclosing subgraphs was designed in this modeled.And a directed dual-radius node labeling algorithm was proposed to learn the topological structure features of nodes and subgraphs from entity relationship graphs through three segments, including directed enclosing subgraph extraction, subgraph node labeling calculation and topological structure feature learning.A node embedding feature learning method based on directed neighbor subgraph was proposed, which incorporated elements such as attention coefficients and relationship types, and learned its node embedding features through the sessions of directed neighbor subgraph extraction and node embedding feature learning.A two-source fusion scoring network was designed to jointly calculate the edge scores by topology and node embedding to obtain the link prediction results of entity-relationship graphs.The experiment results of link prediction show that the proposed model obtains better prediction results under the evaluation metrics of AUC-PR, MRR and Hits@N compared with the baseline models such as R-GCN, SEAL, GraIL and TACT.The ablation experiment results illustrate that the model’s dual-source learning scheme outperforms the link prediction effect of a single scheme.The rule matching experiment results verify that the model achieves automatic authorization of some entities and compression of the relational path of rules.The model effectively improves the effect of link prediction and it can meet the demand of big data access control relationship prediction.…”
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