Search Results - (( evolution optimization sensor algorithm ) OR ( mobile optimization method algorithm ))
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1
A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…In a previous research, a relocating algorithm for mobile sensor network had been introduced and the goal was to save energy and prolong the lifetime of the sensor networks using Particle Swarm Optimization (PSO) where both of sensing radius and travelled distance had been optimized in order to save energy in long-term and shortterm. …”
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2
Evolution, design, and future trajectories on bipedal wheel-legged robot: A comprehensive review
Published 2023“…The analysis encompasses optimization techniques, sensor integration, machine learning, and adaptive control methods, evaluating their impact on robot capabilities. …”
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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Design, optimization and fabrication of a climbing six articulated-wheeled robot using artificial evolution and 3D printing
Published 2015“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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An improved gbln-pso algorithm for indoor localization problem in wireless sensor network
Published 2022“…Then, we compared the result with Particle Swarm Optimization (PSO), Differential Evolution Particle Swarm Optimization (DEPSO), Health Particle Swarm Optimization (HPSO) and Global best Local Neigborhood Particle Swarm Optimization (GbLN-PSO) algorithm. …”
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6
Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Subjects:Conference Paper -
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Mobile robot path planning using hybrid genetic algorithm and traversability vectors method
Published 2004“…Recent advances in robotics and machine intelligence have led to the application of modern optimization method such as the genetic algorithm (GA), to solve the path-planning problem. …”
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Optimization of mobile robot path planning in semi-dynamic environment using genetic algorithm
Published 2023“…The environment design for mobile robots' path planning based on industry environment shows excellent combinations with the GA method that generate the optimal path for the mobile robot with a semi-dynamic obstacle.…”
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9
Adaptive route optimization for mobile robot navigation using evolutionary algorithm
Published 2021“…For example, Ant Colony Optimization (ACO) is an optimization algorithm based on swarm intelligence which is widely used to solve path planning problem. …”
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Proceedings -
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Teletraffic performance of mobile cellular channel assignment using genetic algorithm
Published 2023Subjects:Conference paper -
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Overview of Evolutionary Algorithms and Neural Networks for Modern Mobile Communication
Published 2024journal::journal article -
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Optimization of ANPR algorithm on android mobile phone
Published 2013“…In this paper, the optimization of ANPR algorithm on limited hardware of Android mobile phone is presented. …”
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Proceeding Paper -
13
Enhancing performance of global path planning for mobile robot through Alpha–Beta Guided Particle Swarm Optimization (ABGPSO) algorithm
Published 2025“…The results reveal that our proposed method reduces the mobile robot's travel time by up to 69%, 67%, 72%, and 79% compared to these algorithms, while consistently achieving optimal path lengths. …”
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Optimized performance data transmission in Mobile IP networks
Published 2014“…Our new method determines an optimal domain for each mobile node and does not allow nodes to exit from that optimal domain. …”
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Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building
Published 2023“…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network
Published 2019“…In the proposed work, the focused problem is how to reduce the communication energy consumption and to avoid the routing hole problem by optimized routing algorithms. First, a routing hole detection algorithm is proposed prior to designing the routing protocol which decreases about 30 percent energy consumption rate, detection time and detection overhead. …”
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Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
Published 2018“…Furthermore, Optimized Parametric Topology Control Routing algorithm performs significantly better than Triangular Routing Method and Change Foreign Agent Algorithm. …”
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18
A review on autonomous mobile robot path planning algorithms
Published 2020“…The emerging trend of modern industry automation requires intelligence to be embedded into mobile robot for ensuring optimal or near-optimal solutions to execute certain task. …”
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A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization
Published 2016“…In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm.…”
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Improvement and application of particle swarm optimization algorithm
Published 2025“…Finally, real-world tests are performed to verify the proposed Algorithm's efficacy compared to existing optimization methods. …”
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