The Field Attributes May not Accurately Predict the Need for Early Tracheostomy Tube Insertion in Severe TBI Patients: A New Insight With the Help of AI Algorithms by Adrina Habibzadeh, Sepehr Khademolhosseini, Reza Taheri, Amin Niakan, Saeed Tayebi Khorami, Hadis Ghasemi, HosseinAli Khalili

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Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms by Vijaykumar S. Jatti, A. Saiyathibrahim, Arvind Yadav, Murali Krishnan R., B. Jayaprakash, Sumit Kaushal, Vinaykumar S. Jatti, Ashwini V. Jatti, Savita V. Jatti, Abhinav Kumar, Soumaya Gouadria, Ebenezer Bonyah

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A Salvage Target Tracking Algorithm for Unmanned Surface Vehicles Combining Improved Line-of-Sight and Key Point Guidance by Jiahe Liu, Chao Liu, Mingmei Wen, Yang Wang, Jinzhe Wang, Rencheng Zheng

Subjects: “…line-of-sight guidance algorithm…”
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Research on Thickness Error Optimization Method of Rolling System Based on Improved Sparrow Search Algorithm–Bidirectional Long Short-Term Memory Network–Attention by Qingyun Wu, Xinchen Li, Jiafei Ji, Bowen Xing

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Reduction to master integrals and transverse integration identities by Vsevolod Chestnov, Gaia Fontana, Tiziano Peraro

“…We describe a proof-of-concept implementation of the application of transverse integration identities in the context of integral reduction. We include some applications to cutting-edge integral families, showing significant improvements over traditional algorithms.…”
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A Modified Kalman Filter Based on Radial Basis Function Neural Networks for the Improvement of Numerical Weather Prediction Models by Athanasios Donas, George Galanis, Ioannis Pytharoulis, Ioannis Th. Famelis

“…This study introduces a novel enhancement to the Kalman filter algorithm by integrating it with Radial Basis Function neural networks to improve numerical weather prediction models. …”
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Optimizing Solar Radiation Prediction Based on The Internet of Things Platform in Photovoltaic Power Plant by Neda Ashrafi Khozani, Maryam Mahmoudi, Shabnam Nasr Esfahani

“…Managers and designers encounter economic and managerial challenges due to the uncertainty and difficulty in predicting solar radiation levels. This research introduces a highly accurate prediction method utilizing tree-based methods, enhanced by meta-heuristic algorithms to boost performance. …”
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Predictive Ecological Cooperative Control of Electric Vehicles Platoon on Hilly Roads by Bingbing Li, Weichao Zhuang, Boli Chen, Hao Zhang, Sheng Yu, Jianrun Zhang, Guodong Yin

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GAN data reconstruction based prediction method of telecom subscriber loss by Kehong A, Xiaodong HU

“…Users are the core of operators’ interests.With the introduction of the policy of transferring network with a number, the competition between operators becomes more and more fierce.In order to accurately predict subscriber loss tendency in advance, a prediction method of subscriber loss based on generative adversarial network data reconstruction was proposed.Firstly, the dirty data in the telecom subscriber loss data was used by effective data preprocessing method.Secondly, the GAN was used to reconstruct the telecom subscriber loss data to solve the problem of the imbalance of the telecom subscriber loss data.Finally, extreme gradient boosting algorithm was used to train the telecom subscriber loss prediction model based on GAN reconstruction and the SMOTE sampling model based on synthetic minority oversampling technique sampling method respectively, and compare the prediction accuracy of the two models.The experimental results show that the prediction accuracy of the GAN reconstructed telecom subscriber loss prediction model is increased by 6.75%, the accuracy rate is increased by 25.91%, the recall rate is increased by 30.91%, and the F1-score is increased by 28.73% compared with the unreconstructed prediction model.This method can effectively improve the accuracy of telecom subscriber loss prediction.…”
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An Ensemble Model for Predicting Cardiovascular Disease utilizing Nature Inspired Optimization by Annwesha Banerjee Majumder, Somsubhra Gupta, Sourav Majumder, Dharmpal Singh

“… This paper represents an efficient model for heart disease prediction model utilizing an ensemble mechanism optimized through BAT algorithm. …”
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Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

Subjects: “…dissolved oxygen prediction…”
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Efficient Ensemble Learning-Based Models for Plastic Hinge Length Prediction of Reinforced Concrete Shear Walls by Naser Safaeian Hamzehkolaei, Mohammad Sadegh Barkhordari

“…This study aims to develop practical machine-learning (ML) models for PHL prediction of RCSWs. For this purpose, 721 data of nonplanar and rectangular RCSWs were utilized. …”
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Methodology of optimal distribution of single-phase electric consumers in power supply systems by the criterion of reduction of additional losses caused by load asymmetry and non-s... by A. A. Pesterev, S. S. Kostinskiy, N. D. Narakidze

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A Study of Deep Learning Neural Network Algorithms and Genetic Algorithms for FJSP by Xiaofeng Shang

“…CNN-LSTM-GA is superior to the other two algorithms in terms of prediction accuracy and overall performance of FJSP. …”
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Multi-step Prediction of Monthly Sediment Concentration Based on WPT-ARO-DBN/WPT-EPO-DBN Model by GAO Xuemei, CUI Dongwen

Subjects: “…prediction of monthly sediment concentration…”
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Novel concept for the healthy population influencing factors by Yuhao Shen, Jichao Wang, Lihua Ma, Huizhe Yan

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Pore size classification and prediction based on distribution of reservoir fluid volumes utilizing well logs and deep learning algorithm in a complex lithology by Hassan Bagheri, Reza Mohebian, Ali Moradzadeh, Behnia Azizzadeh Mehmandost Olya

“…Subsequently, the CUDA Deep Neural Network Long Short-Term Memory algorithm(CUDNNLSTM), belonging to the category of DL algorithms and harnessing the computational power of GPUs, is employed for the prediction of CBW, BVI, and FFV logs. …”
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Predicting higher risk factors for COVID-19 short-term reinfection in patients with rheumatic diseases: a modeling study based on XGBoost algorithm by Yao Liang, Siwei Xie, Xuqi Zheng, Xinyu Wu, Sijin Du, Yutong Jiang

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Derivation and validation of an algorithm to predict transitions from community to residential long-term care among persons with dementia-A retrospective cohort study. by Wenshan Li, Luke Turcotte, Amy T Hsu, Robert Talarico, Danial Qureshi, Colleen Webber, Steven Hawken, Peter Tanuseputro, Douglas G Manuel, Greg Huyer

“…<h4>Conclusions and implications</h4>We developed an algorithm to predict time to LTC entry among individuals living with dementia. …”
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Comparison of Support Vector Machine (SVM) and Random Forest (RF) Algorithm Performance with Random Undersampling Technique to Predict Gestational Diabetes Mellitus Risk by Annisa Damayanti, Anna Baita

“…From both models, it shows that the SVM and RF algorithms have very good prediction performance in predicting DMG, but the SVM algorithm can predict DMG better than RF because the number of prediction errors is lower.…”
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