The Fine Feature Extraction and Attention Re-Embedding Model Based on the Swin Transformer for Pavement Damage Classification by Shizheng Zhang, Kunpeng Wang, Zhihao Liu, Min Huang, Sheng Huang

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Leveraging ultrasonic-derived phenotypes and estimated breeding value to improve abdominal fat weight prediction in chickens throughout the egg laying period by Penghao Li, Zhengda Li, Fan Ying, Dan Zhu, Dawei Liu, Xianyi Song, Jie Wen, Guiping Zhao, Bingxing An

“…The stepwise backwards variables selection was conducted to rule out the possible bias of multicollinearity between independent variables and AFW. While, AFT measured by ultrasound improved the predictive ability of all the models (R² of KNN showed highest increase of 12.35 %). …”
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Bilevel Optimization Framework for Multiregional Integrated Energy Systems Considering 6G Network Slicing and Battery Energy Storage Capacity Sharing by Kun Cui, Ming Chi, Yong Zhao, Zhi-Wei Liu

“…The proposed line search-based global Levenberg–Marquardt algorithm addresses the limitations of existing algorithms with necessary and innovative improvements to tackle the challenge of global convergence in nonsmooth optimization problems. …”
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Deep reinforcement learning for multi-objective location optimization of onshore wind power stations: a case study of Guangdong Province, China by Yanna Gao, Hong Dong, Liujun Hu, Fanhong Zeng, Yuqun Gao, Zhuonan Huang, Shaohua Wang, Shaohua Wang

“…To solve this model at large scale, a deep reinforcement learning (DRL) algorithm is designed and implemented. The DRL approach is benchmarked against a traditional optimization implementation using the Gurobi solver. …”
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Impact of integrating type-1 distributed generation on distribution network using modified genetic algorithm and voltage stability index: a technical and cost–benefit analysis appr... by Olakunle Elijah Olabode, Daniel Oluwaseun Akinyele, Titus Oluwasuji Ajewole, Samuel Okeolu Omogoye, Akeem Abimbola Raji

“…The backward-forward sweep formed the backbone of the load flow, while the voltage stability index was used to select the suitable buses where type-1 DG was integrated for optimal performance. …”
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Enhancing Consumer Agent Modeling Through Openness-Based Consumer Traits and Inverse Clustering by Brahim Benaissa, Masakazu Kobayashi, Hiroshi Takenouchi

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Inter-Object Navigation of Unmanned Aerial Vehicles to Increase the Efficiency and Accuracy of Inspection of Power Lines by Tymochko O., Fustii V., Kolesnyk G., Olizarenko S., Kalashnyk G., Kulish R., Tymoschuk O., Galinskji D.

“…Solving the problem of multi-criteria optimization of the drone team flight route planning made it possible to reduce the cost of monitoring critical infrastructure facilities while improving its efficiency and accuracy. …”
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Enhancing Intelligent Control Strategies for UAVs: A Comparative Analysis of Fuzzy Logic, Fuzzy PID, and GA-Optimized Fuzzy PID Controllers by Nigatu Wanore Madebo

“…The GAFPID controller employs evolutionary computation through a genetic algorithm to optimize parameter tuning, offering superior control performance. …”
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A Hybrid GRA-TOPSIS-RFR Optimization Approach for Minimizing Burrs in Micro-Milling of Ti-6Al-4V Alloys by Rongkai Tan, Abhilash Puthanveettil Madathil, Qi Liu, Jian Cheng, Fengtao Lin

“…The validation experimental results agree well with the GRA-TOPSIS-RFR-optimized outcomes. This research provides valuable insights into optimizing the micro-milling process of titanium components, ultimately contributing to improved quality, performance, and service life across various aerospace applications.…”
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Application of a grey wolf optimization-enhanced convolutional neural network and bidirectional gated recurrent unit model for credit scoring prediction. by Yetong Fang

“…The GWO algorithm is introduced to further improve the overall performance of the model by optimizing key parameters. …”
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Artificial intelligence model for predicting early biochemical recurrence of prostate cancer after robotic-assisted radical prostatectomy by Miguel Angel Bergero, Pablo Martínez, Patricio Modina, Ricardo Hosman, Wenceslao Villamil, Romina Gudiño, Carlos David, Lucas Costa

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Nonlinear Compensation of the Linear Variable Differential Transducer Using an Advanced Snake Optimization Integrated with Tangential Functional Link Artificial Neural Network by Qiuxia Fan, Xinqi Zhang, Zhuang Wen, Lei Xu, Qianqian Zhang

“…First, the Latin hypercube sampling method and the Levy flight method are introduced into the snake optimization (SO) algorithm, which enhances the global search ability and diversity preservation ability of the SO algorithm and effectively solves the common overfitting and local optimal problems in the training process of the gradient descent method. …”
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Multi-criteria decision model for multicircular flight control of unmanned aerial vehicles through a hybrid approach by Noorulden Basil, Hamzah M. Marhoon, Bayan Mahdi Sabbar, Abdullah Fadhil Mohammed, Osamah Albahri, Ahmed Albahri, Abdullah Alamoodi, Iman Mohamad Sharaf, Amare Merfo Amsal, Mahrous Ahmed, Enas Ali, Sherif S. M. Ghoneim

“…This study provides a robust solution for UAV control based on the potential of hybrid optimization algorithms to improve UAV precision and reliability in autonomous flight.…”
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Study on the Method of Vineyard Information Extraction Based on Spectral and Texture Features of GF-6 Satellite Imagery by Xuemei Han, Huichun Ye, Yue Zhang, Chaojia Nie, Fu Wen

“…Accurately identifying the distribution of vineyard cultivation is of great significance for the development of the grape industry and the optimization of planting structures. Traditional remote sensing techniques for vineyard identification primarily depend on machine learning algorithms based on spectral features. …”
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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…Our approach indicated significant improvements in classification accuracy compared to previous studies. …”
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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…In order to quickly and accurately predict the production capacity of infilling wells, this study classifies the “three-stage” declining trend observed in the production pressure curves of existing wells into: (1) A drastic decline period, regarded as the initial water production stage; (2) a rapid decline period; and (3) a slow decline period, both considered part of the later gas production stage. The Grey Wolf Optimizer(GWO) algorithm, a fast optimization algorithm with adaptive capabilities and an information feedback mechanism, is applied for hyperparameter optimization of the Long Short-term Memory (LSTM) neural network. …”
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Simultaneous OPEX and carbon footprint reduction with hydrogen enhancement in autothermal reforming: a machine learning–based surrogate modeling and optimization framework by Sahar Shahriari, Davood Iranshahi

“…The resulting solutions demonstrate notable improvements across all targeted criteria. The proposed framework helped reduce the simulation cost and also achieved 65.69 % higher hypervolume and 66.26 % lower IGD than the genetic algorithm. …”
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Adaptive sliding mode control based on maximum power point tracking for boost converter of photovoltaic system under reference voltage optimizer by Borhen Torchani, Ahmad Taher Azar, Ahmad Taher Azar, Ahmad Taher Azar, Anis Sellami, Saim Ahmed, Saim Ahmed, Ibrahim A. Hameed, Ibraheem Kasim Ibraheem, Moamin Ibrahim Jameel Al-Obaidi

“…The primary objective of this approach is to maximize the converter’s output power while ensuring optimal operation in the face of varying environmental conditions such as solar irradiance and temperature, while dynamically adapting to variations in system parameters, as demonstrated by the obtained results. …”
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Intelligent End-Edge Computation Offloading Based on Lyapunov-Guided Deep Reinforcement Learning by Xue Feng, Chi Xu, Xi Jin, Changqing Xia, Jing Jiang

“…To address the end-edge computation offloading challenge in the multi-terminal and multi-server environment, this paper proposes an intelligent computation offloading algorithm based on Lyapunov optimization and deep reinforcement learning. …”
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Artificial neural networks-based multi-objective optimization of immersion cooling battery thermal management system using Hammersley sampling method by Muhammed Donmez, Mehmet Ihsan Karamangil

“…Using the Hammersley method, various module designs are generated. Multi-objective optimization, using ANN-based multi objective genetic algorithms, is conducted on a 16S1P configuration at 4C discharge and 0.008 kg/s. …”
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