A novel hybrid fruit fly and simulated annealing optimized faster R-CNN for detection and classification of tomato plant leaf diseases by E. Gangadevi, Ben Othman Soufiane, Balamurugan Balusamy, Firoz Khan, Masresha Getahun

“…By hybridizing the fruit fly optimization algorithm and simulated annealing, the Faster R-CNN’s hyper-parameter issues are addressed, and the convergence rate is improved. …”
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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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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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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 Fairness in Autonomous Vehicles: Proof of Confidence With Blockchain Technology by Jimin Ryu, Yong Ik Yoon

“…Unlike existing mechanisms, such as Proof of Work and Proof of Stake, PoC is designed to improve transaction efficiency while maintaining strong data integrity and supporting fair decision-making processes in dynamic driving environments. …”
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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

“…Experiments show that the LyA3C algorithm can converge stably and effectively improve the long-term network computation rate by 2.8% and 5.7% in comparison to the A2C-based and TD3-based algorithms.…”
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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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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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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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Occupant-Centric Visual Comfort Assessment and Optimization of Passive Solar Façade Shading Systems through View-Based Analysis of Daylight Glare Probability, View Content, and Spa... by Martin Ivanov, Jun Sato

“…Two experimental studies validate the approach: the first systematically evaluates multiple predefined shading patterns to identify optimal characteristics, while the second demonstrates that algorithmic optimization of highly irregular shading configurations can simultaneously improve multiple visual comfort metrics, significantly outperforming regular shading patterns in terms of glare reduction, view preservation, and spatial frequency performance.…”
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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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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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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 main contributions of this article include an improvement in system robustness against irradiance variations, thanks to the integration of an adaptive algorithm and a PI controller within the SMC. …”
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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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Optimized Two-Stage Anomaly Detection and Recovery in Smart Grid Data Using Enhanced DeBERTa-v3 Verification System by Xiao Liao, Wei Cui, Min Zhang, Aiwu Zhang, Pan Hu

“…The first stage employs an optimized increment-based detection algorithm achieving 95.0% for recall and 54.8% for precision through multidimensional analysis. …”
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Nondestructive detection and classification of impurities-containing seed cotton based on hyperspectral imaging and one-dimensional convolutional neural network by Yeqi Fei, Zhenye Li, Tingting Zhu, Zengtao Chen, Chao Ni

“…With a processing time of 11.764 μs per pixel from experimental data, it shows a much improved speed requirement while maintaining the accuracy of real production lines. …”
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Optimizing Security of Radio Frequency Identification Systems in Assistive Devices: A Novel Unidirectional Systolic Design for Dickson-Based Field Multiplier by Atef Ibrahim, Fayez Gebali

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Research on Impact of Planned Path Length and Yaw Cost on Collaborative Search of Unmanned Aerial Vehicle Swarms by Heng Zhang, Wenyue Meng, Yanan Liu, Guanyu Liu, Jian Zhang

“…To address the unclear impacts of a planned path length and yaw cost on search performance in large-scale Unmanned Aerial Vehicle (UAV) swarm collaborative search scenarios under complex and dynamic environments, a path grid determination algorithm is proposed, transforming the path-planning problem into an optimal waypoint selection problem, enabling UAVs to make rapid decisions using the Particle Swarm Optimization (PSO) algorithm. …”
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Multi-Objective Optimization Research Based on NSGA-II and Experimental Study of Triplex-Tube Phase Change Thermal Energy Storage System by Yi Zhang, Haoran Yu, Yingzhen Hou, Neng Zhu

“…On this basis, the influence of the optimization variables was analyzed. The optimized configuration (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>r</mi><mn>1</mn></msub><mo>=</mo><mn>0.014</mn></mrow></semantics></math></inline-formula> m, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>r</mi><mn>2</mn></msub><mo>=</mo><mn>0.041</mn></mrow></semantics></math></inline-formula> m, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>r</mi><mn>3</mn></msub><mo>=</mo><mn>0.052</mn></mrow></semantics></math></inline-formula> m) was integrated into a modular design, achieving a 2.12% improvement in heat transfer efficiency and a 73.23% increase in heat storage rate. …”
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