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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Design and Implementation of Mobile Experiment Algorithm Designer Interface for Network Control System Laboratory by Jahan Zaib Bhatti, Guo-Ping Liu, Shafqat Ali, Nasim Ullah, Ivo Pergl, Lukas Prokop, Vojtech Blazek

Subjects: “…Control engineering education…”
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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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Kerf geometry prediction and optimization in laser cutting of basalt fiber reinforced polymer composites using decision tree and coati optimization algorithm by Ammar H. Elsheikh, Ninshu Ma, Fadl A. Essa, Mahmoud Khedr, Ahmed Mohamed Mahmoud Ibrahim

“…This study introduces a Coati Optimization Algorithm (COA) integrated with a Decision Tree (DT) algorithm to predict and optimize kerf geometry in Basalt Fiber Reinforced Polymer (BFRP) composites during laser cutting. …”
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Development and validation of a spontaneous preterm birth risk prediction algorithm based on maternal bioinformatics: A single-center retrospective study by Yu Chen, Xinyan Shi, Zhiyi Wang, Lin Zhang

“…In terms of predicting the risk of preterm birth, the XGBoost algorithm demonstrated the most outstanding performance, with an AUCROC of 0.89 (95% CI: 0.88–0.90). …”
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Predicting Surface Roughness and Grinding Forces in UNS S34700 Steel Grinding: A Machine Learning and Genetic Algorithm Approach to Coolant Effects by Mohsen Dehghanpour Abyaneh, Parviz Narimani, Mohammad Sadegh Javadi, Marzieh Golabchi, Samareh Attarsharghi, Mohammadjafar Hadad

“…A relational equation with 25 coefficients is developed, using optimized algorithms to predict surface roughness with an 85 percent accuracy and grinding forces with a 90 percent accuracy rate. …”
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A novel wheeled mobile robots control based on robust hybrid controller: Mixed H2/H∞ and predictive algorithm approach by Sibang Liu, Kuili Liu, Zhen Zhong, Jinghan Yi, Hamdulah Aliev

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Predictive method for poultry carcass visceral dimensions using 3D point cloud and Genetic Algorithm-based wavelet neural network by Zhengwei Zhu, Yan Chen, Lu Cai, Jinzhou Yang, Ke Wen, Jingjing Bao, Zhigang Hu, Dandan Fu

“…Then, a prediction model of poultry visceral size (GA-WNN) was built by K-fold cross validation method, Genetic Algorithm and Wavelet Neural Network (WNN). …”
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Battle Royale Optimization for Optimal Band Selection in Predicting Soil Nutrients Using Visible and Near-Infrared Reflectance Spectroscopy and PLSR Algorithm by Jagadeeswaran Ramasamy, Anand Raju, Kavitha Krishnasamy Ranganathan, Muthumanickam Dhanaraju, Backiyathu Saliha, Kumaraperumal Ramalingam, Sathishkumar Samiappan

“…Further partial least square regression (PLSR) was used to find the latent variable and to evaluate various algorithms for their performance in predicting soil properties. …”
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Integrative electricity need prediction utilizing enhanced squeeze net and flexible Coyote optimization algorithm A combination of RCPs SSPs and socioeconomic by Bin Yang, Bin Song, Yadegar Abdi

“…Squeeze Net carefully learns complex data patterns to produce reliable predictions, while FCOA focuses on improving the prediction framework. …”
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Forward Predicting Chromatic-Optical Parameters of the Mixed Light of White-Red Light-Emitting Diode Configurations Based on Deep Learning Algorithms by Songsheng Lin, Huanting Chen, Yin Zheng, Quanji Xie, Xuehua Shen, Huichuan Lin, Shuo Lin, Yan Li

“…Four deep learning algorithms were evaluated. Each model was trained to reconstruct the SPD curves and predict the corresponding optical and chromatic parameters. …”
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Prediction of the Residual Compressive Strength of Rice Husk Ash Concrete after Exposure to Elevated Temperatures Using XGBoost Machine Learning Algorithm by Elvis Ang'ang'o, Silvester Abuodha, Siphila Mumenya

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