An Optimized Method for Solving the Green Permutation Flow Shop Scheduling Problem Using a Combination of Deep Reinforcement Learning and Improved Genetic Algorithm by Yongxin Lu, Yiping Yuan, Jiarula Yasenjiang, Adilanmu Sitahong, Yongsheng Chao, Yunxuan Wang

“…It introduces a novel hybrid approach that combines end-to-end deep reinforcement learning with an improved genetic algorithm. Firstly, the PFSP is modeled using an end-to-end deep reinforcement learning (DRL) approach, named PFSP_NET, which is designed based on the characteristics of the PFSP, with the actor–critic algorithm employed to train the model. …”
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Training State-of-the-Art Deep Learning Algorithms with Visible and Extended Near-Infrared Multispectral Images of Skin Lesions for the Improvement of Skin Cancer Diagnosis by Laura Rey-Barroso, Meritxell Vilaseca, Santiago Royo, Fernando Díaz-Doutón, Ilze Lihacova, Andrey Bondarenko, Francisco J. Burgos-Fernández

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Kans-Unet Model and Its Application in Image Patch-Shaped Detection by Xingsu Li, Zhong Li, Jianping Huang, Ying Han, Kexin Zhu, Bo Hao, Junjie Song, Yumeng Huo

“…The module applies a learnable activation function at the edge of the network, which not only reduces the number of model parameters but also significantly improves the generalization performance of the network. …”
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Research on the Prediction Model of Wheel Set Failure Rate for Urban Rail Trains Based on IPSO-BP Algorithm by HE Deqiang, SUN Yi, MENG Jiwei, LIU Jianren

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Improved Dab-Deformable Model for Runway Foreign Object Debris Detection in Airport Optical Images by Yang Cao, Yuming Wang, Yilin Zhu, Rui Yang

“…First, this paper introduces a Lightweight Deep-Shallow Feature Fusion algorithm (LDSFF), which integrates a hotspot sensing network and a spatial mapping enhancer aimed at focusing the model on significant regions. …”
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Dynamical analysis of fractional hepatitis B model with Gaussian uncertainties using extended residual power series algorithm by Qursam Fatima, Mubashir Qayyum, Murad Khan Hassani, Ali Akgül

“…This manuscript extends existing mathematical models for HBV by introducing a treatment compartment to improve understanding, diagnosis, and treatment strategies. …”
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Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm by Qichun Bing, Dayi Qu, Xiufeng Chen, Fuquan Pan, Jinli Wei

“…Because of the uncertainty and nonlinearity, short-term traffic flow forecasting remains a challenging task. In order to improve the accuracy of short-term traffic flow forecasting, a short-term traffic flow forecasting method based on LSSVM model optimized by GA-PSO hybrid algorithm is put forward. …”
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A Hybrid Internet of Behavior Algorithm for Predicting IoT Data of Plant Growing using LSTM and NB Models by Khansaa Yaseen Ahmad, Omar Muayad Abdullah

“…To improve the prediction accuracy, the outputs of the LSTM system were used as inputs to the Naïve Bayes algorithm. …”
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LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

“…This allowed for a comprehensive comparison across diverse algorithmic configurations and enabled the identification of the most efficient model for disease prediction. …”
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Research on Lightweight Model of Multi-person Pose Estimation Based on Improved YOLOv8s-Pose by FU Yu, GAO Shuhui

“…To address the issues of high computational load and slow detection speed in existing human pose estimation models, this paper proposes a lightweight improved algorithm based on the YOLOv8s-Pose model. …”
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A Study of Corrosion-Grade Recognition on Metal Surfaces Based on Improved YOLOv8 Model by Hao Chen, Ying Cao, Shengxian Cao, Heng Piao

“…Finally, based on ablation experiments and comparison experiments, performance analyses of multiple algorithmic models are conducted for horizontal and vertical comparisons in order to verify the effectiveness of the improved method and the superiority of the models in this paper. …”
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Optimizing Personalized Recommender Systems for Teachers’ Digital Learning Models Using Deep Learning Algorithms by Jun Zhong, Wenjuan Zhang

“…To address this issue, this paper proposes a personalized recommendation algorithm based on Graph Neural Networks (PRAGNN) for teachers’ digital learning models. …”
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Taylor-Spotted Cat Optimization (Taylor-SCO): An Energy-Efficient Cluster Head Selection Algorithm with Improved Trust Factor for Data Routing in WSN by Shivaraj Kalburgi, M. Manimozhi

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A recurrent neural network and parallel hidden Markov model algorithm to segment and detect heart murmurs in phonocardiograms. by Andrew McDonald, Mark J F Gales, Anurag Agarwal

“…We propose a novel recurrent neural network and hidden semi-Markov model (HSMM) algorithm that can both segment the signal and detect a heart murmur, removing the need for a two-stage algorithm. …”
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Forecasting Models and Genetic Algorithms for Researching and Designing Photovoltaic Systems to Deliver Autonomous Power Supply for Residential Consumers by Ekaterina Gospodinova, Dimitar Nenov

“…It is suggested that two minimized criteria be used to create a model for forecasting FOU. This model can be used with a genetic algorithm to make a prediction that fits a specific case, such as a time series representation based on discrete fuzzy sets of the second type. …”
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Estimation and Modeling of Fluctuating Wind Amplitude and Phase Spectrum Using APES Algorithm Based on Field Monitored Data by Dan-hui Dan, Xiang-jie Wang, Xing-fei Yan, Wei Cheng

“…Compared with the measured FWAS, the stochastic Davenport eFWAS model proposed in this paper can accurately describe the statistical properties of the local wind field and improve the modeling accuracy of the FWAS, which is important in antiwind structural design and safety assessment.…”
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An Optimization Model for Shell Plate Seam Landing Using Minimum Manufacturing Cost and a Solution by Genetic Algorithm by Ho Rim Pae, Min Hyok Jon, Chol Jun Pak

“…In this paper, a new optimization model and its solution method for the landing of seams and butts (for convenience, seam and butt are simply called seam) on the ship hull surface are proposed in order to improve the shipbuilding efficiency. …”
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A non-intrusive load monitoring algorithm based on real-time feature extraction and deep learning model by Behrooz Taheri, Mostafa Sedighizadeh, Mohammad Reza Nasiri, Alireza Sheikhi Fini

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Prediction of Coiled Tubing Erosion Rate Based on Sparrow Search Algorithm Back-Propagation Neural Network Model by Yinping Cao, Fengying Fang, Guowei Wang, Wenyu Zhu, Yijie Hu

“…To accurately predict the erosion rate of coiled tubing, this study studied the influence law of erosion rate through experiments, screened the main influencing factors of erosion rate by grey relational analysis (GRA), and established a back-propagation neural network (BPNN) model optimized by the sparrow search algorithm (SSA) to predict the erosion rate. …”
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Short-Term Wind Power Forecast Based on CNN&LSTM-GRU Model Integrated with CEEMD-SE Algorithm by Guohua YANG, Xin QI, Rui JIA, Yifeng LIU, Fei MENG, Xin MA, Xiaowen XING

“…In order to further improve the accuracy of short-term wind power forecast, a CNN & LSTM-GRU based short-term wind power prediction model using CEEMD-SE algorithm is proposed. …”
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