Résultats de la recherche - optimization algorithm

In complex environments where satellite signals may be interfered with, it is difficult to achieve precise positioning of high-speed aerial vehicles solely through the inertial navigation system. To overcome this challenge, this paper proposes an NGO-ELM geomagnetic matching-assisted navigation algo...

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In this paper we consider a reachability problem for a nonlinear affine-control system  with  integral constraints, which assumed to be quadratic in the control variables.  Under  controllability assumptions it was  proved [8] that any admissible control, that steers the control system to the bounda...

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An efficient adaptive modeling criterion for the polymer electrolyte membrane fuel cell (PEMFC) is proposed in this paper, which can facilitate its precise simulation, design, analysis and control. In this work, a number of state-of-the-art algorithms have been adapted to optimize the complex electr...

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Electric vehicles are at the forefront of the transition towards more sustainable transportation, and battery management systems are tasked with ensuring optimal operation and balancing of the individual cells within a battery pack for increased performance, longevity, and safety of EV batteries. Th...

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A highly loaded axial flow compressor often leads to significant flow separation, resulting in increased pressure loss and deterioration of the pressure increase ability. Improving flow separation within a compressor is crucial for enhancing aeroengine performance. This study proposes adding a fin s...

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Accurate prediction of Air Quality Index (AQI) concentrations remains a critical challenge in environmental monitoring and public health management due to the complex nonlinear relationships among multiple atmospheric factors. To address this challenge, we propose a novel prediction model that integ...

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Straw row grouping is vital in conservation tillage for precision seeding, and accurate centerline extraction of the seedling bands enhances agricultural spraying efficiency. However, the traditional single-threshold Otsu segmentation struggles with adaptability and accuracy under complex field cond...

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Magnetic positioning technology is a novel and direct method to measure the attitude and position information of discrete particles in dense granular flow. However, owing to the need to manually set the initial value and other boundary conditions in the process of algorithm solution, the deviation b...

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Land desertification represents a significant and sensitive global ecological issue. In the Inner Mongolia region of China, soil desertification and salinization are widespread, resulting from the combined effects of extreme drought conditions and human activities. Using Gaofen 5B AHSI imagery as ou...

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Supply chain management plays a critical role in the process of converting raw materials into final products and services. Although, conventional supply chains may fall short of the modern expectations of efficiency, cost-efficiency and sustainability. Green Agri-Food Supply Chain Networks (GASCN) a...

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Reinforcement learning plays a crucial role in the field of robotic arm grasping, providing a promising approach for the development of intelligent and adaptive grasping strategies. Due to distribution shift and local optimum in action, traditional online reinforcement learning is difficult to use e...

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This paper presents a multi-source data-driven hybrid path planning framework that integrates global A* search with local Deep Q-Network (DQN) optimization to address complex terrestrial routing challenges. By fusing ASTER GDEM terrain data with OpenStreetMap (OSM) road networks, we construct a stan...

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Food delivery has emerged as a crucial aspect of the dining experience, driven by the proliferation of the Internet and the expansion of the catering industry. Delivery times have become a significant factor affecting customer satisfaction. However, the inherent unpredictability of the delivery proc...

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Urban transportation systems evolve toward greater diversification, scalability, and complexity. To address the escalating issue of urban traffic congestion, leveraging modern information technologies to enhance the integration of multiple transportation modes and maximize overall efficiency has eme...

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With the growing prevalence of cybercrime, botnets have emerged as a significant threat, infiltrating an increasing number of legitimate computers annually. Challenges arising for organizations, educational institutions, and individuals as a result of botnet attacks include distributed denial of ser...

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This paper presents a digital twin-driven multi-objective optimization approach for enhancing the performance and productivity of a multi-product manufacturing system under complex operational challenges. More specifically, the concept of digital twin is applied to virtually replicate a physical sys...

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This study investigates a variant of the shortest path problem (SPP) tailored for plug-in hybrid electric vehicles (PHEVs), incorporating two practical features: hybrid energy mode switching and partial charging. A novel modeling framework is proposed that enables PHEVs to dynamically switch between...

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The study optimizes the flight trajectory and power of multiple unmanned aerial vehicles with the deep deterministic policy gradient algorithm and constructs a multi-unmanned aerial vehicle semantic communication optimization model based on singular value decomposition and multi-agent deep reinforce...

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The scheduling of carrier-based aircraft departure operations is subject to stringent temporal, spatial, and resource constraints. Conventional approaches struggle to yield exact solutions or provide a comprehensive mathematical description of this complex, dynamic process. This study proposes a sim...

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Mobile Edge Computing (MEC) alleviates latency and bandwidth strain on centralized cloud infrastructures by enabling the offloading of tasks to proximal edge servers, yet resource optimization in dense dynamic networks remains an open problem. This paper proposes a genetic algorithm (GA)-based appro...

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