Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study by Chuang Li, Youbei Lin, Xuyang Xiao, Xinru Guo, Jinrui Fei, Yanyan Lu, Junling Zhao, Lan Zhang

“…This study demonstrates that machine learning models—particularly the RF algorithm—hold substantial promise for predicting kinesiophobia in postoperative lung cancer patients. …”
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Product perceptual design optimization model based on BP neural network by Lei Yong

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An adaptive transition probability matrix with quality seeds for cellular automata models by Youcheng Song, Xu Hongtao, Haijun Wang, Ziyang Zhu, Xinyi Kang, Xiaoxu Cao, Zhang Bin, Haoran Zeng

“…Addressing this gap, our research introduces the adaptive transition probability matrix with quality seeds (ATPMS) model, which incorporates both the Markov model and the genetic algorithm (GA) into the traditional CA framework. …”
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Predictive Models for Educational Purposes: A Systematic Review by Ahlam Almalawi, Ben Soh, Alice Li, Halima Samra

“…The review compares the effectiveness of machine learning (ML) algorithms such as Support Vector Machines (SVMs), Artificial Neural Networks (ANNs), and Decision Trees with traditional statistical models, assessing their ability to manage complex educational data and improve decision-making. …”
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Predicting CO₂ Emissions with Advanced Deep Learning Models and a Hybrid Greylag Goose Optimization Algorithm by Amel Ali Alhussan, Marwa Metwally, S. K. Towfek

“…In this paper, we propose a general framework that combines advanced deep learning models (such as GRU, Bidirectional GRU (BIGRU), Stacked GRU, and Attention-based BIGRU) with a novel hybridized optimization algorithm, GGBERO, which is a combination of Greylag Goose Optimization (GGO) and Al-Biruni Earth Radius (BER). …”
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Sentiment Analysis Algorithm Based on Deep Transfer Learning for Multi-Source Data Fusion by Long Qin

“…The experiment outcomes indicate that the artificial bee colony-improved particle swarm optimization algorithm designed in the study has the minimum convergence value under single-peak and multi-peak test functions, with a standard deviation of less than 0.25 and a success rate of 100% in optimization. …”
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A Novel Hyper-Heuristic Algorithm with Soft and Hard Constraints for Causal Discovery Using a Linear Structural Equation Model by Yinglong Dang, Xiaoguang Gao, Zidong Wang

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Modelling the evolutionary dynamics of drug resistance in tuberculosis using hypercube and Baum-Welch algorithm inference: A case study of Tanzania by Leonce Leandry, Egbert Mujuni, Morten Brun, Eunice W. Mureithi, Mbazi Senkoro, Saidi Mfaume

“…To address some of these issues, the study investigated the evolutionary dynamics of drug resistance using a 6-hypercubic model, Hidden Markov Model (HMM) and the Baum-Welch algorithm for inference. …”
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Advanced internet of things enhanced activity recognition for disability people using deep learning model with nature-inspired optimization algorithms by Mohammed Maray

“…The EARDP-DLMNOA model mainly relies on improving the activity recognition model using advanced optimization algorithms. …”
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Multi-Agent Communication for Dynamic Job-Shop Scheduling: A Robust Single-Machine Scheduling Model With Genetic Algorithm Optimization by Hong-Phuc Nguyen, Quang-Hieu Ngo, van-Can Nguyen

“…The experimental results show that the proposed method outperforms the stand-alone single-machine scheduling model, achieving up to a 34% reduction in total tardiness cost and improving lead times and scheduling stability under uncertainties. …”
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A cross-chain model for warehouse receipts in port supply chain based on notary mechanism and ShangMi cryptographic algorithms by Yangbo Chen, Wei Ou, Mengxue Pang, Jianqiang Ma, Qiuling Yue, Wenbao Han

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Extreme gradient boosting algorithm based urban daily traffic index prediction model: a case study of Beijing, China by Jiancheng Weng, Kai Feng, Yu Fu, Jingjing Wang, Lizeng Mao

“…The daily dimensional prediction model proposed in this paper has an important application value for predicting traffic status and improving the operation quality of urban road networks.…”
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Parameter extraction of PV models under varying meteorological conditions using a modified electric eel foraging optimization algorithm by Hadeer Khalifa, Mohamed Ebeed, Gaber Magdy, Sherif A. Khaleel, Mohamed I. Shehata, Moataz M. Salah, Francisco Jurado, Hossam Hassan Ali

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Construction of a risk prediction model for postoperative deep vein thrombosis in colorectal cancer patients based on machine learning algorithms by Xin Liu, Xingming Shu, Yejiang Zhou, Yifan Jiang

“…The XGBoost model demonstrated strong potential for improving early detection and treatment in clinical settings.…”
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An application of Arctic puffin optimization algorithm of a production model for selling price and green level dependent demand with interval uncertainty by Hachen Ali, Md. Al-Amin Khan, Ali Akbar Shaikh, Adel Fahad Alrasheedi, Seyedali Mirjalili

“…To assess the accuracy and reliability of the proposed model, the Arctic Puffin Optimization (APO) algorithm is employed to analyze and solve a specific numerical illustration. …”
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Intelligent algorithm-based model for predicting mass transfer performance in CO2 absorption within a rotating packed bed by Wei Zhang, Hao Chen, Ke Huang, Xing Shu, Cheng Fu, Bin Huang

“…To address these challenges, this study introduces three advanced intelligent models aimed at improving the prediction of the mass transfer coefficient. …”
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A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion by Rebecca E. Abbott, Alain Nishimwe, Hadi Wiputra, Ryan E. Breighner, Arin M. Ellingson

“…Results demonstrate that OrthoFusion significantly reduced segmentation time, while improving structural similarity of bone images and relative accuracy of derived bone model geometries. …”
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The Impact of Different Parallel Strategies on the Performance of Kriging-Based Efficient Global Optimization Algorithms by Hang Fu, Qingyu Wang, Takuji Nakashima, Rahul Bale, Makoto Tsubokura

“…A parallel efficient global optimization (EGO) algorithm with a pseudo expected improvement (PEI) multi-point sampling criterion, proposed in recent years, is developed to adapt the capabilities of modern parallel computing power. …”
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Fusion of motion smoothing algorithm and motion segmentation algorithm for human animation generation. by Shinan Ding

“…In the field of human animation generation, the existing technology is often limited by the dependence on large-scale data sets, and it is difficult to capture subtle dynamic changes when processing motion transitions, resulting in insufficient animation fluency and realism. In order to improve the naturalness and diversity of human animation generation, a method combining motion smoothing algorithm and motion segmentation algorithm is proposed. …”
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Optimization and Verification of One-dimensional Three-field Model for Transient Analysis of Pressurized Water Reactor by YUAN Leqi1, LI Zanwang1, 2, FAN Jie1, 3, GOU Junli1, SHAN Jianqiang1

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