Integrated Systemic Modeling of Production Scheduling, Maintenance, and Quality Control in Closed-Loop Supply Chains by Javad Rahim, Ali Morovati Sharifabadi, Davood Andalib Ardakani

“…The Strategic Choice Approach (SCA) was employed to structure complex decision-making processes, leveraging the expertise of industry professionals to identify key uncertainties and variables. A Genetic Algorithm (GA) was utilized to optimize decision variables, including sample size, sampling intervals, control limits, and maintenance schedules, ensuring robust solutions under real-world constraints. …”
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Pure data correction enhancing remote sensing image classification with a lightweight ensemble model by Huaxiang Song, Hanglu Xie, Yingying Duan, Xinyi Xie, Fang Gan, Wei Wang, Jinling Liu

“…Specifically, our models achieve an overall accuracy of up to 96.8%, representing a 1.1% improvement on the challenging NWPU45 dataset. …”
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Prediction of China’s Sulfur Dioxide Emissions by Discrete Grey Model with Fractional Order Generation Operators by Wei Meng, Daoli Yang, Hui Huang

“…Based on fractional order operators, a discrete grey model with fractional operators is developed, which also makes use of genetic algorithms to optimize the modeling parameter r. …”
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Reducing Safety Risks in Construction Tower Crane Operations: A Dynamic Path Planning Model by Binqing Cai, Zhukai Ye, Shiwei Chen, Xun Liang

“…The proposed model consists of three modules: first, a path information collection module preprocessing the video data to capture relevant operational path information; second, a path safety risk evaluation module employing You Only Look Once version 8 (YOLOv8) instance segmentation to identify potential risk factors along the operational path, e.g., potential drop zones and the positions of nearby workers; and finally, a path planning module utilizing an improved Dynamic Window Approach for tower cranes (TC-DWA) to avoid risky areas and optimize the operational path for enhanced safety. …”
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Quantum chimp-enanced SqueezeNet for precise diabetic retinopathy classification by Anas Bilal, Muhammad Shafiq, Waeal J. Obidallah, Yousef A. Alduraywish, Alishba Tahir, Haixia Long

“…This paper presents an advanced hybrid approach that utilizes the Quantum Chimp Optimization Algorithm (QCOA) integrated with SqueezeNet to enhance the accuracy and efficiency of DR classification significantly. …”
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Modeling and Regulation of Dynamic Temperature for Layer Houses Under Combined Positive- and Negative-Pressure Ventilation by Lihua Li, Min Li, Yao Yu, Yuchen Jia, Zhengkai Qian, Zongkui Xie

“…Based on a new combined positive- and negative-pressure ventilation (CPNPV) mode, a dynamic temperature model is constructed. Additionally, a temperature control method for a layer house is designed using a variable universe fuzzy PID control algorithm (VFPID). …”
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Creating cell-specific computational models of stem cell-derived cardiomyocytes using optical experiments. by Janice Yang, Neil J Daily, Taylor K Pullinger, Tetsuro Wakatsuki, Eric A Sobie

“…We used the genetic algorithm (GA), a heuristic parameter calibration method, to tune ion channel parameters in a mathematical model of iPSC-CM physiology. …”
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Dark Side of the Web: Dark Web Classification Based on TextCNN and Topic Modeling Weight by Gun-Yoon Shin, Younghoan Jang, Dong-Wook Kim, Sungjin Park, A-Ran Park, Younghwan Kim, Myung-Mook Han

“…For validation, we employed two datasets and compared the performance of the model with other text classification algorithms, where the proposed model demonstrated superior effectiveness in Dark Web classification.…”
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Ship-DETR: A Transformer-Based Model for EfficientShip Detection in Complex Maritime Environments by Yi Wang, Xiang Li

“…First, we introduce the high-low frequency (HiLo) attention into the intra-scale feature interaction module to enhance the extraction of both high- and low-frequency features, reduce computational complexity, and improve detection performance. To strengthen the model&#x2019;s multi-scale fusion capability for ship features of different scales, we incorporate the bidirectional feature pyramid network (BiFPN) to optimize cross-scale feature fusion and add the <inline-formula> <tex-math notation="LaTeX">$S_{2}$ </tex-math></inline-formula> features to further enhance the representation of small-scale ship features. …”
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Research on monthly runoff prediction model considering secondary decomposition of multiple fitness functions and deep learning by Zhongfeng Zhao, Xueni Wang, Hua Jin, Jie Zheng

“…The issue of high-frequency noise in the decomposed components of runoff sequences and the difficulty in ensuring the rationality of algorithm parameters, this study proposes a monthly runoff prediction model for that considers multiple fitness function optimization. …”
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Integrated energy microgrid bi-level game scheduling optimization taking into account electricity-heat-hydrogen enriched compressed natural gas coupling and shared energy storage by Changgang Wang, Xiaoning Sun

“…Finally, the proposed model is solved using the Black-winged Kite algorithm in conjunction with the CPLEX solver.Case studies demonstrate the effectiveness of the proposed method, showing revenue increases of 9.15% for integrated energy microgrid operators and 8.29% for load aggregators, alongside a reduction in carbon emissions by 8.76%.…”
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Deep learning-based edge detection for random natural images by Kanija Muntarina, Rafid Mostafiz, Sumaita Binte Shorif, Mohammad Shorif Uddin

“…Deep learning approaches offer significant advantages in capturing high-level representations, thereby improving the accuracy and robustness of edge detection algorithms. …”
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Connected Transit Bus Dynamic Priority Weight Modeling and Conflicting Request Resolution Control at the Signalized Intersection by Shuxian He, Haihang Han, Huan Zhang, Shanzhi Sun, Tony Z. Qiu

“…Moreover, for the transit signal priority system, how to establish a model to measure traffic demand for conflicting priority request resolution and improve system response time has been widely researched for the last few decades. …”
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School-level prediction and management of myopia in children and adolescents by Shengsong Xu, Linling Li, Yingting Zhu, Zhenbang Ruan, Yiwen Qu, Zhuandi Zhou, Yin Hu, Zhidong Li, Fei Hou, Xiaohua Zhuo, Yunxia Leng, Xuelin Huang, Yamei Lu, Zhirong Wang, Shuifeng Deng, Yehong Zhuo, Guoming Zhang, Min Fu, Xiao Yang

“…The interactions between age and other variables were revealed by the algorithms, and hence the final prediction models were established based on age segmentation. …”
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Enhancing Agricultural Futures Return Prediction: Insights from Rolling VMD, Economic Factors, and Mixed Ensembles by Yiling Ye, Xiaowen Zhuang, Cai Yi, Dinggao Liu, Zhenpeng Tang

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Perceptual-Preference-Based Touring Routes in Xishu Gardens Using Panoramic Digital-Twin Modeling by Xueqian Gong, Zhanyuan Zhu, Li Guo, Yong Zhong, Deshun Zhang, Jing Li, Manqin Yao, Wei Yong, Mengjia Li, Yujie Huang

“…Accordingly, the proposed model synchronizes Type II peak-hour throughput with Type I off-peak experiential depth using dynamic path allocation algorithms. …”
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Evaluation of Machine Learning Models for Estimating Grassland Pasture Yield Using Landsat-8 Imagery by Linming Huang, Fen Zhao, Guozheng Hu, Hasbagan Ganjurjav, Rihan Wu, Qingzhu Gao

“…The findings also highlighted the importance of predictor selection in optimizing model performance, except for the reflectance and vegetation indices characterizing vegetation canopy information, the inclusion of soil moisture information could appropriately improve the accuracy of model predictions, especially for grasslands with relatively low vegetation cover.…”
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Development and validation of a risk prediction model for acute kidney injury in coronary artery disease by Ming Ye, Chang Liu, Duo Yang, Hai Gao

“…This study focuses on developing accurate predictive models to improve the early detection and prognosis of AKI in CAD patients. …”
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Predicting the subclinical carotid atherosclerosis in overweight and obese patients using a machine learning model by D. V. Gavrilov, T. Yu. Kuznetsova, M. A. Druzhilov, I. N. Korsakov, A. V. Gusev

“…To improve the model performance, the fill missing function was used. …”
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Development and application of an early prediction model for risk of bloodstream infection based on real-world study by Xiefei Hu, Shenshen Zhi, Yang Li, Yuming Cheng, Haiping Fan, Haorong Li, Zihao Meng, Jiaxin Xie, Shu Tang, Wei Li

“…Based on the optimal combination, six machine learning algorithms were used to construct an early BSI risk prediction model. …”
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