YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

“…To overcome these limitations, this paper introduces YOLOv11-GSF, a real-time strawberry ripeness detection algorithm based on YOLOv11, which incorporates several innovative features: a Ghost Convolution (GhostConv) convolution method for generating rich feature maps through lightweight linear transformations, thereby reducing computational overhead and enhancing resource utilization; a C3K2-SG module that combines self-moving point convolution (SMPConv) and convolutional gated linear units (CGLU) to better capture the local features of strawberry ripeness; and a F-PIoUv2 loss function inspired by Focaler IoU and PIoUv2, utilizing adaptive penalty factors and interval mapping to expedite model convergence and optimize ripeness classification. …”
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BWO–ICEEMDAN–iTransformer: A Short-Term Load Forecasting Model for Power Systems with Parameter Optimization by Danqi Zheng, Jiyun Qin, Zhen Liu, Qinglei Zhang, Jianguo Duan, Ying Zhou

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Virtual power plant to ensure reliable power supply and accident-free operation of process equipment of a mining enterprise by Telmanova E.D., Abdrakhmanov I.D.

“…The paper presents a schematic diagram and stages of building a mathematical model of BAS. Structural optimization of this algorithm, which improves the topology of the system, has been performed. …”
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Modeling and optimization of culture media for recombinant Helicobacter pylori vaccine antigen HpaA by Runqing Tan, Song Zhou, Min Sun, Yu Liu, Xiumei Ni, Jin He, Gang Guo, Kaiyun Liu

“…The artificial neural network linked genetic algorithm (ANN-GA) model exhibited superior predictive accuracy, achieving a rHpaA yield of 0.61 g/L, which represents a 93.2% increase compared to the initial medium. …”
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Integrative electricity need prediction utilizing enhanced squeeze net and flexible Coyote optimization algorithm A combination of RCPs SSPs and socioeconomic by Bin Yang, Bin Song, Yadegar Abdi

“…The effectiveness of the compact network is increased by using the Flexible Coyote Optimization Algorithm (FCOA), which plays a vital role in optimizing parameters and accelerating convergence. …”
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Estimation of Lithium-Ion Battery SOC Based on IFFRLS-IMMUKF by Xianguang Zhao, Tao Wang, Li Li, Yanqing Cheng

“…To tackle the challenge of precise SOC estimation in complex environments, this study introduces an improved forgetting factor recursive least squares (IFFRLS) method, which integrates the Golden Jackal optimization (GJO) algorithm with the traditional FFRLS method. …”
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UAVRM-A*: A Complex Network and 3D Radio Map-Based Algorithm for Optimizing Cellular-Connected UAV Path Planning by Yanming Chai, Yapeng Wang, Xu Yang, Sio-Kei Im, Qibin He

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Optimizing Outdoor Micro-Space Design for Prolonged Activity Duration: A Study Integrating Rough Set Theory and the PSO-SVR Algorithm by Jingwen Tian, Zimo Chen, Lingling Yuan, Hongtao Zhou

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An optimal design method of the resonant-free C-type filter by XU Fangwei, JIA Junwei, GUO Kai, XU Lin, CHEN Jiale, LU Yuguo

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Research on Operation Curve Planning Technology Adaptive to Undulating Tracks for Heavy-Haul Trains by JIANG Jie, ZHANG Zhengfang, LUO Yuan, ZHOU Huangbiao, XIONG Jiayuan

“…Finally, the ant colony algorithm was used to solve this model, resulting in the generation of the optimal control curve for heavy-haul trains running on undulating track sections. …”
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A distributional reinforcement learning model for optimal glucose control after cardiac surgery by Jacob M. Desman, Zhang-Wei Hong, Moein Sabounchi, Ashwin S. Sawant, Jaskirat Gill, Ana C. Costa, Gagan Kumar, Rajeev Sharma, Arpeta Gupta, Paul McCarthy, Veena Nandwani, Doug Powell, Alexandra Carideo, Donnie Goodwin, Sanam Ahmed, Umesh Gidwani, Matthew A. Levin, Robin Varghese, Farzan Filsoufi, Robert Freeman, Avniel Shetreat-Klein, Alexander W. Charney, Ira Hofer, Lili Chan, David Reich, Patricia Kovatch, Roopa Kohli-Seth, Monica Kraft, Pulkit Agrawal, John A. Kellum, Girish N. Nadkarni, Ankit Sakhuja

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Leveraging Game Theory to Design Incentive-Compatible Time-Varying electricity pricing with Demand-Side management by Magda I. El-Afifi, Bishoy E. Sedhom, Abdelfattah A. Eladl, Padmanaban Sanjeevikumar, Samaa Fawzy

“…This study investigates a novel approach to improve energy efficiency through a Demand Response (DR) program with a Game Theory (GT)-based Time-of-Use (ToU) pricing model. …”
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Optimization Design of Node Placement Manipulators Based on Working Area and Response Speed by Huang Zhiqiang, Duan Yuxing, Song Xiaowei, Wang Jie, Fu Mingwei, Sun Haoxiang, Li Gang

“…Based on the multi-objective particle swarm algorithm and the variable density method, the size optimization and lightweight design of the node-distributed manipulator arm are carried out. …”
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Fusion of Visible and Infrared Images Using a Reinforcement Learning System Based on Fuzzy Logic and Convolution Optimized with Wild Horse Algorithm by Mahvash Zarimeidani, Amir Amirabadi, Nasrin Amiri, Iman Ahanian, Siavash Es’haghi

“…This hybrid reinforcement learning system was optimized using algorithms including wild horse optimization (WHO), genetic algorithm (GA), and particle swarm optimization (PSO) to improve specific fusion metrics such as image correlation, similarity coefficient, image entropy, and signal-to-noise ratio. …”
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Energy efficient adaptive clustering with QoS-aware CBRP and grey wolf optimization clustering algorithm for mobile ad-hoc network (MANET) by Minal Patil, Manish Chawhan, Roshan Umate, Abhishek Madankar, Bhumika Neole

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Development of a Mathematical Model and Structural Optimization of the Specific Resistance of a Broken Line Subsoiler by Da Qiao, Qian Shi, Pinyan Lv, Yingjie Guo, Daping Fu, Min Liu, Limin Jiang, Yang Wang, Jingli Wang, Weizhi Feng

“…Aiming at the problems of shallow subsoiling depth, large subsoiling specific resistance and small soil bulkiness in subsoiling operation in saline-alkali soil, this paper establishes a mathematical model of the specific resistance of a broken line subsoiler and uses genetic algorithm and the discrete element method to optimize the structure design of the subsoiler. …”
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Efficient cooling capability in microchannel heat sink reinforced with Y-shaped fins: Based on artificial neural network, genetic algorithm, Pareto front, and numerical simulation by Xiang Ma, Ali Basem, Pradeep Kumar Singh, Rebwar Nasir Dara, Ahmad Almadhor, Amira K. Hajri, Raymond Ghandour, Barno Abdullaeva, H. Elhosiny Ali, Samah G. Babiker

“…The applied cost functions demonstrated the high accuracy of the models in predicting system performance. A genetic algorithm was employed for single-objective optimization targeting three criteria: maximizing total efficiency, minimizing pressure drop, and maximizing the Nusselt number. …”
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Advanced Vehicle Routing for Electric Fleets Using DPCGA: Addressing Charging and Traffic Constraints by Yuehan Zheng, Hao Chang, Peng Yu, Taofeng Ye, Ying Wang

“…With the rapid proliferation of electric vehicles (EVs), urban logistics faces increasing challenges in optimizing vehicle routing. This paper presents a new modeling framework for the Electric Vehicle Routing Problem (EVRP), where multiple electric trucks serve a set of customers within their capacity limits. …”
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A new Hybrid Metaheuristic Model for Image Edge Detection by Adil Khalil, Adel Abed Al Wahaab, Ahmed Abbas

“…These techniques may have the potential to provide advanced capabilities to improve the image edge detection process. A metaheuristic model such as the Bat algorithm may offer appropriate parameters for the edge detection algorithm. …”
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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization by Sivakumar Palanıswamy, Vijayakumar Vaıthyam Rengarajan, Sandhya Devi Ramıah Subburaj

“…It is presumed that the implementation of deep learning algorithms demands a large amount of data to learn complex features automatically and this can pose a challenge for applications with lesser data to achieve generalization. …”
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