New Hybrid Method for Buffer Positioning and Production Control Using DDMRP Logic in Smart Manufacturing by Sahar Habbadi, Ismail El Mouayni, Brahim Herrou, Souhail Sekkat

“…To identify the optimal buffer locations, a Genetic Algorithm (GA) is employed. …”
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探討強化學習演算法之素材推薦機制與AI學習履歷之學習者感知 Learner Perceptions of AI-Powered Learning Portfolios and Personalized Material Recommendation Mechanisms in Reinforcement Learning Algorithms... by 曾建維 Jian-Wei Tzeng, 黃天麒 Tien-Chi Huang, 薛承祐 Cheng-Yu Hsueh, 廖英淞 Ying-Song Liao

“…Enhancing usage incentive, continuously refining the accuracy of the recommendation system’s algorithms, and conducting comparative analyses with existing systems are essential to improve the recommendation system’s perceived utility. …”
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Exploiting full-duplex opportunities in WLANs via a reinforcement learning-based medium access control protocol by Song Liu, Peng Wei

“…Thus, we develop a Window-Constraint Bayesian (WCB) algorithm to generate optimized scheduling policies online. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…Oversampling techniques, model optimization, and reduced communication rounds were used to mitigate the issues. …”
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BERT-OntoSent: combining BERT language model with sentiment ontology for enhanced sentiment analysis on social media by Abdelweheb Gueddes, Mohamed Ali Mahjoub

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Adaptive data driven multi period power supply recovery method for distribution networks by Xi Ye, Meng Yang, Zhihong Yang, Qing Xiang, Yazhuo Li

“…Finally, simulations on the improved IEEE-33 bus system and actual example systems verify that the adaptive data driven power supply recovery model for distribution networks can reduce conservatism and improve the robustness of the optimization results. …”
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Stochastic robot failure management in an assembly line under industry 4.0 environment by Kuldip Singh Sangwan, Anirudh Tusnial, Suveg V Iyer

“…A particle swarm optimization (PSO) algorithm is developed to solve the proposed integrated model. …”
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An interpretable machine learning model for predicting mortality risk in adult ICU patients with acute respiratory distress syndrome by Wanyi Li, Hangyu Zhou, Yingxue Zou

“…This study used eight machine learning algorithms to construct predictive models. Recursive feature elimination with cross-validation is used to screen features, and cross-validation-based Bayesian optimization is used to filter the features used to find the optimal combination of hyperparameters for the model. …”
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Evaluating Machine Learning and Deep Learning models for predicting Wind Turbine power output from environmental factors. by Montaser Abdelsattar, Mohamed A Ismeil, Karim Menoufi, Ahmed AbdelMoety, Ahmed Emad-Eldeen

“…Preprocessing techniques, including feature scaling and parameter tuning, improved model performance by enhancing data consistency and optimizing hyperparameters. …”
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Environmental Risk Mitigation via Deep Learning Modeling of Compressive Strength in Green Concrete Incorporating Incinerator Ash by Amin Amraee, Seyed Azim Hosseini, Farshid Farokhizadeh, Mohammad Hassan Haeri

“…A database for deep learning modeling was created using Convolutional Neural Networks (CNNs) and the Multi-Verse Optimizer (MVO) algorithm. …”
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DMM-YOLO: A high efficiency soil fauna detection model based on an adaptive dynamic shuffle mechanism by Jiehui Ke, Renbo Luo, Guoliang Xu, Yuna Tan, Zhifeng Wu, Liufeng Xiao

“…Therefore, this paper proposes an improved algorithm based on You Only Look Once (YOLO) v9, which enhances feature capture capability while reducing parameters by 33.6%. …”
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Machine Learning-Based Prediction of Resilience in Green Agricultural Supply Chains: Influencing Factors Analysis and Model Construction by Daqing Wu, Tianhao Li, Hangqi Cai, Shousong Cai

“…Secondly, by integrating configurational analysis with machine learning, it innovatively constructs a resilience level prediction model based on fsQCA-XGBoost. The research findings are as follows: (1) fsQCA identifies a total of four high-resilience pathways, verifying the core proposition of “multiple conjunctural causality” in complex adaptive system theory; (2) compared with single algorithms such as Random Forest, Decision Tree, AdaBoost, ExtraTrees, and XGBoost, the fsQCA-XGBoost prediction method proposed in this paper achieves an optimization of 66% and over 150% in recall rate and positive sample identification, respectively. …”
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Intelligent Methods of Operational Response to Accidents in Urban Water Supply Systems Based on LSTM Neural Network Models by Aliaksey A. Kapanski, Nadezeya V. Hruntovich, Roman V. Klyuev, Aleksandr E. Boltrushevich, Svetlana N. Sorokova, Egor A. Efremenkov, Anton Y. Demin, Nikita V. Martyushev

“…The results showed that the optimally tuned LSTM model can achieve high accuracy and outperform traditional methods such as the Holt–Winters model. …”
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Robust model predictive control for polytopic uncertain systems via a high-rate network with the FlexRay protocol by Jianhua Wang, Fuqiang Fan, Yanye Yu, Shuxin Du, Xiaorui Guo

“…Subsequently, taking both high-rate networks and FRP into account, sufficient conditions are obtained by solving a time-varying terminal constraint set of an auxiliary optimization problem. In addition, an algorithm including both off-line and on-line parts is provided to find a sub-optimal solution. …”
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A novel mechanism-guided residual network for accurate modelling of scroll expander under noisy and sparse data conditions by Xiaoshuang Lv, Xin Ma, Wei Peng, Ke Li, Chengdong Li

“…This framework is based on the architecture of residual network, where the mechanistic laws are embedded as constraints in the training of the network through an improved loss function. Then, a hybrid optimization algorithm is detailed, which can achieve efficient and accurate updating of the parameters of the network and mechanistic equations. …”
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Control Strategy of In-Port U-Turn for Ships Based on Arctangent Function Nonlinear Feedback by Shihang Gao, Xianku Zhang

“…The strategy integrates a closed-loop gain-shaping algorithm with nonlinear feedback control, applied to a nonlinear motion mathematical model specifically designed for low-speed operations in shallow waters. …”
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Integrated export instream coefficient model for accurate nonpoint source pollution estimation and management in the Yellow River Basin by Xueting Wang, Lei Wu, Yongkun Luo, Yimu Liu, Ruowen Wang

“…Empirical EC values were derived using genetic algorithm (GA) and Latin hypercube sampling, then improved EC and corrected EC were employed to estimate pollutant discharge and water inflow across land uses. …”
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A Study on Canopy Volume Measurement Model for Fruit Tree Application Based on LiDAR Point Cloud by Na Guo, Ning Xu, Jianming Kang, Guohai Zhang, Qingshan Meng, Mengmeng Niu, Wenxuan Wu, Xingguo Zhang

“…In the domain of point cloud feature extraction, an improved Alpha Shape algorithm is proposed for extracting point cloud contours. …”
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MRI-based brain tumor ensemble classification using two stage score level fusion and CNN models by Oussama Bouguerra, Bilal Attallah, Youcef Brik

“…Nine deep learning models are then trained and tested on the enhanced dataset, experimenting with five optimizers. …”
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FCB-YOLOv8s-Seg: A Malignant Weed Instance Segmentation Model for Targeted Spraying in Soybean Fields by Zishang Yang, Lele Wang, Chenxu Li, He Li

“…To address these challenges, this study proposes an improved weed instance segmentation model based on YOLOv8s-Seg, named FCB-YOLOv8s-Seg, for targeted spraying operations in soybean fields. …”
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