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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Multi-Step Prediction of TBM Tunneling Speed Based on Advanced Hybrid Model by Defu Liu, Yaohong Yang, Shuwen Yang, Zhixiao Zhang, Xiaohu Sun

“…Finally, several subsequences were fed into a Long Short-Term Memory (LSTM) network optimized by the Sparrow Search Algorithm (SSA) for multi-step training and prediction, and the predicted results of each subsequence were added up to obtain the final result. …”
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The relationship between the annual catch of bigeye tuna and climate factors and its prediction by Peng Ding, Hui Xu, Xiaorong Zou, Xiaorong Zou, Xiaorong Zou, Shuyi Ding, Siqi Bai

“…The SSA-XGBoost model have the highest prediction accuracy, followed by XGBoost, BP, LSTM, and RF. …”
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Regression models for predicting the effect of trash rack on flow properties at power intakes by Shuguang Li, Sultan Noman Qasem, Hojat Karami, Ely Salwana, Alireza Rezaei, Danyal Shahmirzadi, Shahab S. Band

“…Vortex flow characteristics in a reservoir and horizontal water intake have been predicted by using regression models in this numerical research. …”
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Output Power Prediction of a Photovoltaic Module Through Artificial Neural Network by Muhammad Aseer Khan, Muhammad Arqum Khan, Husan Ali, Bilal Ashraf, Shahbaz Khan, Dur-E-Zehra Baig, Abdul Wadood, Tahir Khurshaid

“…In this paper, an experimental measurement dataset of 28296 samples with all the environmental parameters mentioned above are taken as the inputs and power as its output, of a Poly-Silicon (Poly-Si) PV module, is trained through Artificial Neural Network (ANN), to predict the output power accurately. The proposed ANN contains a layer size of 15 and training algorithm used is Levenberg-Marquardt. …”
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Integrated Wavelet-Grey-Neural Network Model for Heritage Structure Settlement Prediction by Yonghong He, Pengwei Jin, Xin Wang, Shaoluo Shen, Jun Ma

“…Finally, a wavelet reconstruction fusion algorithm is developed to achieve the collaborative optimization of dual-channel prediction results. …”
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