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An Optimized Strategy Coverage Control Algorithm for WSN
Published 2014-07-01“…Thirdly, OSCC picks out the optimal routing solution while conducting combinatorial optimization of routing path using ant colony optimization (ACO) algorithm, thus reducing the energy spending of whole network. …”
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Overview of Deep Learning Algorithms and Optimizers for Brain Tumor Segmentation
Published 2025-04-01Get full text
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Mathematical Models and Algorithms of Optimal Load Management of Electricity Consumers
Published 2019-11-01“…Based on the calculated-and-experimental studies, it was determined that the proposed mathematical model of the problem is adequate, while the developed algorithms for optimal planning of short-term power system modes with optimization of load profile of regulated electricity consumers and taking into account various types of limitations are of high computational qualities.…”
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Optimized Negative Selection Algorithm for Image Classification in Multimodal Biometric System
Published 2023-04-01“…Hence, this work developed an Optimized Negative Selection Algorithm (ONSA) for image classification in biometric systems. …”
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Optimization of Complex Cancer Morphology Detection Using the SIVQ Pattern Recognition Algorithm
Published 2012-01-01“…In a number of cases in surgical pathology, morphometric quantitation is already performed manually or semi-quantitatively, with this effort contributing to diagnostic workup. Digital whole slide imaging, coupled with emerging image analysis algorithms, offers great promise as an adjunctive tool for the surgical pathologist in areas of screening, quality assurance, consistency, and quantitation. …”
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Application of an improved ant colony algorithm based on unevenly distributed pheromone and multi-objective optimization in path planning for unmanned surface vehicles
Published 2025-02-01“…ObjectiveTo address the challenges of path planning for unmanned surface vehicles in complex waters, this paper proposes an improved ant colony optimization(ACO)algorithm based on uneven distributed pheromone and multi-objective optimization.MethodsFirst, a probabilistic roadmap method (PRM) is used to generate an initial path. …”
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Synchronous Optimization for Demand-Driven Train Operation Plan in Rail Transit Network Using Nondominated Sorting Coevolutionary Memetic Algorithm
Published 2022-01-01“…Considering the entire network as a whole, researchers have realized that synchronous optimization is of great significance. …”
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DIDADTIC TOOLS FOR THE STUDENTS’ ALGORITHMIC THINKING DEVELOPMENT
Published 2017-12-01“…Modern engineers must possess high potential of cognitive abilities, in particular, the algorithmic thinking (AT). In this regard, the training of future experts (university graduates) of technical specialities has to provide the knowledge of principles and ways of designing of various algorithms, abilities to analyze them, and to choose the most optimal variants for engineering activity implementation. …”
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Optimal Assembly Position and Multi-objective Trajectory Optimization for Dual Robotic Arms Collaboration
Published 2024-01-01“…Finally, based on the optimal position of flexibility, the multi-objective particle swarm algorithm is used to optimize the trajectory with the objectives of time, energy consumption and impact; by performing simulation analysis in the Matlab robot simulation platform, the results show that, by applying the flexibility index to the trajectory planning, it can improve the operation efficiency of the robotic arm, while reducing energy consumption and impact loss, and maintain a high degree of operability during the whole motion process, effectively avoiding the randomness of the traditional manual teaching method, thus realizing the optimal flexible trajectory planning for collaborative assembly of dual robotic arms.…”
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Advancing Pile-Bearing Capacity Prediction with Meta-Heuristic Enhanced Specific ANFIS strategys
Published 2025-05-01Get full text
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Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm
Published 2022-01-01“…After 114 iterations of the heuristic search algorithm, the optimal value is 6.83353635e-001, while the average optimal value is 6.83551939e-001. …”
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Comprehensive Research on Energy Saving Synergy Optimization and Optimal Real-time Control of Hybrid Electric Mining Trucks
Published 2024-07-01“…This study takes the hybrid electric mining truck as a research object, establishes the mathematical model of the whole vehicle, takes reducing fuel consumption as the goal, establishes a collaborative optimization model that comprehensively considers the interaction between transmission system parameters and energy management strategies, and combines particle swarm optimization (PSO) algorithm and dynamic programming (DP) algorithm to build a two-layer interactive optimization algorithm to eliminate the interaction between transmission system parameters and energy management strategies. …”
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Image Similarity Quantum Algorithm and Its Application in Image Retrieval Systems
Published 2025-01-01“…It is found that the AE-QIP algorithm achieves comparable precision to the ST-QIP algorithm while exhibiting significant reductions in qubit consumption and average processing time. …”
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UWB Base Station Deployment Optimization Method Considering NLOS Effects Based on Levy Flight-Improved Particle Swarm Optimizer
Published 2025-03-01“…In this paper, we propose a new UWB BS deployment optimization method that takes into account the influence of NLOS occlusion, determines the BS deployment range and occlusion by indoor map information, uses the locatable points coverage rate in the whole indoor positioning area as the fitness function, and proposes an improved particle swarm optimization algorithm based on the Levy flight strategy (LPSO) to solve the optimization problem. …”
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Supply chain management and optimization in transportation logistics
Published 2022-12-01“…These two classes can scan all problem sizes while generating optima and near optimal solution. …”
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LEO multi-service routing algorithm based on multi-objective decision making
Published 2016-10-01“…In low earth orbit(LEO) satellite networks,in view of the unbalanced link resource,it's difficult to meet differentiated quality of service(QoS) requirements and easily lead to reduce the efficiency of the whole network.A routing algorithm based on multi-objective decision making was proposed which defined LEO satellite network transmission service as the delay sensitive,sensitive bandwidth and reliability sensitive three categories.It used the eigenvector method to calculate service weights,and used the consistency ratio to determine whether it can be accepted.Based on the multi-objective decision making theory,it combined with the actual state of satellite network nodes and links and the specific requirements of the business,calculating the path that meets the QoS requirements of the service,so as to realize the LEO satellite network multi objective dynamic routing optimization.Established simulation platform based on the iridium network system simulated network delay,the uncertain characteristics like the residual bandwidth and packet error rate,route planning for the randomly generated three classes of business.The simulation results show that,the algorithm not only satisfies the QoS constrain while balancing the traffic load of the satellite link effectively,but also improves the performance on the throughput.…”
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Automatic Vehicles’ Trajectories Optimization on Highway Exclusive Lanes
Published 2022-01-01“…The rapid development of V2X communication has made it possible to optimize and control the trajectories of vehicles from the whole traffic flow’s perspective and improve traffic performance. …”
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Chinese National Condition Based Power Dispatching Optimization in Microgrids
Published 2018-01-01“…This paper proposed a study on the power dispatching optimization in the microgrid aiming at Chinese national condition based on PSO algorithm. …”
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Optimization of Transformation Coefficients Using Direct Search and Swarm Intelligence
Published 2017-04-01“…Now, methods based on heuristic rules and fuzzy logic, or methods that optimize parts of the whole system separately, are applied to this problem. …”
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