Prediction of chloride concentration in concrete under multi-salt environment: Optimization of integrated algorithm based on MSCPO and interpretability analysis by Daming Luo, Kanglei Du, Ditao Niu

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NGBoost algorithm-based prediction of mechanical properties of a hot-rolled strip and its interpretability research with ANOVA values by Hongyi Wu, Jinwen Jin, Zhiwei Li

“…The study focused on predicting tensile strength, yield strength, and elongation of hot-rolled strip steel and compared the predictive results with those obtained from the gradient boosting algorithm, Lasso regression, and decision tree algorithms. …”
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Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm by Qiyuan Cui, Jianhong Pu, Wei Li, Yun Zheng, Jiaxi Lin, Lu Liu, Peng Xue, Jinzhou Zhu, Mingqing He

“…ObjectiveThe aim of this study was to develop and validate a machine learning-based model to predict the development of impaired fasting glucose (IFG) in middle-aged and older elderly people over a 5-year period using data from a cohort study.MethodsThis study was a retrospective cohort study. …”
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Predicting the Cetane Number of Biodiesel using two AI-Models: the Gradient-based ANN and ANN Optimized by Genetic Algorithm by Hadis Tanha, Fatemeh Bashipour

“…They were the gradient-based artificial neural network (GB-ANN) and the multi-layer-perceptron ANN optimized by the genetic algorithm (GA-ANN) for the first time. The three input variablesof the model for predicting the target variable of the biodiesel CN are the average number of carbon atoms, average number of double bonds, and average molecular weight of the fatty acid methyl esters. …”
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Novel machine learning algorithm in risk prediction model for pan-cancer risk: application in a large prospective cohort by Chi-Pang Wen, Xifeng Wu, Qingfeng Hu, Huakang Tu, Shan Pou Tsai, David Ta-Wei Chu

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Application of Decision Tree (M5Tree) Algorithm for Multicrop Yield Prediction of the Semi-Arid Region of Maharashtra, India by Kalpesh Borse, Prasit Agnihotri

“…Modern artificial intelligence algorithms have shown to be highly useful tools for accurately predicting agricultural production. …”
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Ensemble design for seasonal climate predictions: studying extreme Arctic sea ice lows with a rare event algorithm by J. Sauer, F. Massonnet, G. Zappa, F. Ragone

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Enhanced CO₂ Emissions Prediction Using Temporal Fusion Transformer Optimized by Football Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally

Subjects: “…carbon dioxide emissions prediction…”
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Efficient Channel Prediction Technique Using AMC and Deep Learning Algorithm for 5G (NR) mMTC Devices by Vipin Sharma, Rajeev Kumar Arya, Sandeep Kumar

“…In this paper, we have proposed a channel prediction scheme based on a deep learning (DL) algorithm possessed by parametric analysis. …”
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WCN24-657 ARTIFICIAL INTELLIGENCE IN PREDICTING PROGRESSION IN ADVANCED CKD: FROM ALGORITHM DEVELOPMENT TO REAL-WORLD DEPLOYMENT by Ricardo Aguilar Grajeda, Priyanka Arya, Chin-Chi Kuo, Mandar Gori, Suresha Venkataraya, Joel Fernandes, Sanjay Singh, Yu-Ting Lin, Hsiu-Yin Chiang, Yi-Chun Chan, Min-Yen Wu, Zi-Han Lin, Arsh Kumar Jain

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A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI. by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md Mehedi Hassan

“…Moreover, among all the hyperparameter-optimized algorithms, adaboost algorithm outperformed all the other hyperparameter-optimized algorithms. …”
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Efficient Recovery of Linear Predicted Coefficients Based on Adaptive Steepest Descent Algorithm in Signal Compression for End-to-End Communications by Abel Kamagara, Abbas Kagudde, Baris Atakan

“…Herein, the steepest descent algorithm is applied at the receiver to decode the affected linear predicted coefficients. …”
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Prediction of the Punching Load Strength of SCS Slabs with Stud-Bolt Shear Connectors Using Numerical Modeling and GEP Algorithm by Mehdi Yousefi, Mohammad Golmohammadi, Seyed Hashem Khatibi, Majid Yaghoobi

“…Finally, using the experimental setup and gene expression programming (GEP) algorithm, several numerical models were planned to predict the maximum strength of the slabs and a simple relation was proposed. …”
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An ideally designed deep trust network model for heart disease prediction based on seagull optimization and Ruzzo Tompa algorithm by Yuan Jin, Yunliang Lai, Azadeh Noori Hoshyar, Nisreen Innab, Meshal Shutaywi, Wejdan Deebani, A. Swathi

“…Although recent studies propose comprehensive automated diagnostic systems, these systems tend to focus on one aspect, such as feature selection, prioritization, or predictive accuracy. A more complete approach that considers all of these factors can improve the efficiency of a cardiac prediction system. …”
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Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle by Gusti Ayu Putu Febriyanti, Anna Baita

“…This study evaluates the performance of two machine learning algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT), in predicting heart disease risk by applying undersampling techniques to handle data imbalance. …”
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A Prediction of the Shooting Trajectory for a Tuna Purse Seine Using the Double Deep Q-Network (DDQN) Algorithm by Daeyeon Cho, Jihoon Lee

“…This study proposes a method for predicting shooting trajectories using the Double Deep Q-Network (DDQN) algorithm. …”
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TCN-LSTM-MHSA model optimized by improved slime mould algorithm for stress prediction of roadway anchor bolts (cables) by QI Junyan, CHE Yuhao, WANG Lei, YUAN Ruifu

Subjects: “…anchor bolt (cable) stress prediction…”
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Deep learning algorithms enable MRI-based scapular morphology analysis with values comparable to CT-based assessments by Hanspeter Hess, Alexandra Oswald, J. Tomás Rojas, Alexandre Lädermann, Matthias A. Zumstein, Kate Gerber

“…A deep learning-based segmentation network was trained with paired CT derived scapula segmentations. An algorithm to fuse multi-plane segmentations was developed to generated high-resolution 3D models of the scapula on which morphological landmark- and axes were predicted using a second deep learning network for morphological analysis. …”
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Reference frame list optimization algorithm in video coding by quality enhancement of the nearest picture by Junyan HUO, Ruipeng QIU, Yanzhuo MA, Fuzheng YANG

“…Interframe prediction is a key module in video coding, which uses the samples in the reference frames to predict those in the current picture, thus helps to represent the complex video by transmitting a small amount of the prediction residual.In lossy video coding, the qualities of reference frames are affected by the quantization distortion, which lead to poor prediction accuracy and performance degradation.Targeted at the low latency video services, a reference frame list optimization algorithm was proposed, which enhanced the quality of the nearest reference frame by a deep learning-based convolutional neural network, and integrated the enhanced reference frame into the reference frame list to improve the accuracy of interframe prediction.Compared with H.265/HEVC reference software HM16.22, the proposed algorithm provides BD-rate savings of 9.06%, 14.92% and 13.19% for Y, Cb and Cr components, respectively.…”
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Research on Predicting Joint Rotation Angles Through Mechanomyography Signals and the Broad Learning System by Yu Bai, Xiaorong Guan, Huibin Li, Shi Cheng, Rui Zhang, Long He

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