A SHAP algorithm-based prediction of the interlaminar shear strength degradation of G/BFRP bars embedded in concrete exposed to marine environment by Xuan Zhao, Pei-Fu Zhang, Qi Zhao, Daxu Zhang, Yiliyaer Tuerxunmaimaiti, Heng Cao

“…To address this issue, a dataset collected from published literature was compiled and SHAP algorithm-based method was employed to predict the ILSS retention (ILSSR). …”
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Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa by Tirualem Zeleke Yehuala, Sara Beyene Mengesha, Nebebe Demis Baykemagn

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Training and inference Time Efficiency Assessment Framework for machine learning algorithms: A case study for hyperspectral image classification by Xiaorou Zheng, Jianxin Jia, Shoubin Dong, Yawei Wang, Runuo Lu, Yuwei Chen, Yueming Wang

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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

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Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…[Objective] Factors such as road networks， temperature， and electric vehicle （EV） type affect the spatial and temporal distribution of EV charging loads. To improve prediction accuracy， a spatiotemporal EV charging load prediction model is developed by integrating multiparty information. …”
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Passenger Flow Prediction for Rail Transit Stations Based on an Improved SSA-LSTM Model by Xing Zhao, Chenxi Li, Xueting Zou, Xiwang Du, Ahmed Ismail

Subjects: “…passenger flow prediction…”
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Prediction of hydrogen production in proton exchange membrane water electrolysis via neural networks by Muhammad Tawalbeh, Ibrahim Shomope, Amani Al-Othman, Hussam Alshraideh

“…Hence, this work employs the artificial neural network (ANN) to develop a model that accurately predicts HPR in PEMWE setups. A novel approach is introduced by employing the Levenberg–Marquardt backpropagation (LMBP) algorithm for training the ANN. …”
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NOx Emission Prediction of Waste Gas Based on the Grey Self-memory Bernoulli Model by GUO Xiaojun; ZHANG Rui; SHEN Houxue; YOU Dan

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Combinatorial machine learning approaches for high-rise building cost prediction and their interpretability analysis by Zenghui Liu, Jing Lin

“…It compares individual cost prediction models (Decision Tree, BP Neural Network, and Support Vector Machine) with combined prediction models (BP-DT and BP-SVM) for high-rise building cost prediction. …”
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Research on Oil Well Production Prediction Based on GRU-KAN Model Optimized by PSO by Bo Qiu, Jian Zhang, Yun Yang, Guangyuan Qin, Zhongyi Zhou, Cunrui Ying

Subjects: “…oil well production prediction…”
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A machine learning based prediction model for short term efficacy of nasopharyngeal carcinoma by Qiulu Zhong, Xiangde Li, Qinghua Du, Qianfu Liang, Danjing Luo, Jiaying Wen, Haiying Yue, Wenqi Liu, Xiaodong Zhu, Jian Li

“…Three machine learning algorithms were used to construct predictive models for the short-term efficacy of LANPC. …”
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Highway subgrade stability prediction model based on depth separation convolutional fusion network by Yubian Wang

“…The experimental results indicate that the proposed data structure and algorithm can better distinguish the defect features of highway roadbeds. …”
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Urban intersection traffic flow prediction: A physics-guided stepwise framework utilizing spatio-temporal graph neural network algorithms by Yuyan Annie Pan, Fuliang Li, Anran Li, Zhiqiang Niu, Zhen Liu

“…This manuscript introduces a novel framework, the Physics-Guided Spatio-Temporal Graph Neural Network (PG-STGNN), specifically designed for traffic flow prediction. By integrating the principles of traffic flow physics with advanced spatio-temporal graph neural network algorithms, the framework captures complex spatio-temporal dependencies in traffic networks. …”
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Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials by Simin Nazari, Amira Abdelrasoul

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Prediction of maximum forming depth in single point incremental forming of 6061 aluminum alloy based on Adaboost regression by LIANG Zhikai, ZHANG Zhichao, HU Lan, PANG Qiu

“…Based on the experimental results， a regression model using the Adaboost algorithm is developed to predict the forming depth of 6061 aluminum alloy thin sheets at the forming diameter of 100 mm. …”
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Predicting Optimum Moisture Content by the individual and hybrid approach of machine learning by Yinghui Yang, Yahui Dai, Qunting Yang

“…Machine learning offers a promising alternative by enabling the creation of advanced predictive models and algorithms that can improve the accuracy and efficiency of OMC predictions compared to traditional empirical methods. …”
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Machine Learning Approaches for Predicting Employee Turnover: A Systematic Review by Hojat Talebi, Amid Khatibi Bardsiri, Vahid Khatibi Bardsiri

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Cooperative Sleep and Energy-Sharing Strategy for a Heterogeneous 5G Base Station Microgrid System Integrated with Deep Learning and an Improved MOEA/D Algorithm by Ming Yan, Tuanfa Qin, Wenhao Guo, Yongle Hu

“…Numerical results indicate that our approach achieves significant energy savings while ensuring accurate predictions of BSMG energy demands through a multi-objective evolutionary algorithm based on decomposition.…”
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The application of machine learning algorithms for predicting length of stay before and during the COVID-19 pandemic: evidence from Wuhan-area hospitals by Yang Liu, Yang Liu, Renzhao Liang, Chengzhi Zhang

“…We employed six machine learning algorithms to predict the probability of LOS.ResultsAfter implementing variable selection, we identified 35 variables affecting the LOS for COVID-19 patients to establish the model. …”
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Predicting the chemical equilibrium point of reacting components in gaseous mixtures through a novel Hierarchical Manta-Ray Foraging Optimization Algorithm by Oguz Emrah Turgut, Hadi Genceli, Mustafa Asker, Mustafa Turhan Çoban, Mohammad Akrami

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