Search Results - (( global optimization method algorithm ) OR ( simulation optimization sensor algorithm ))
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…In addition, it is expected that it can be applied in real-time application. In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. …”
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2
Modelling of multi-robot system for search and rescue
Published 2023“…In this project, this sensor-based algorithm is known as the Obstacle Avoidance Algorithm. …”
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Optimizing Invasive ECT sensor dimensions for conducting pipe: A simulation study
Published 2025“…This simulation study aims to optimize the dimensions of an invasive Electrical Capacitance Tomography (ECT) sensor for conducting pipe applications. …”
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4
Observer-based fault detection approach using fuzzy adaptive poles placement system with real-time implementation
Published 2021“…Therefore, this paper proposes a fuzzy-based observer tuning method to optimize and adapt the selection of poles locations to determine the optimal gains of the observer, and it is experimentally applied to a composite sensor fault detection. …”
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Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter
Published 2013“…As a simulation study, we applied the algorithms in a network to track the position and speed of a projectile and compared the results with real world circumstances, using the concept of transient mean square deviations of network as a cost function. …”
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6
Vector evaluated particle swarm optimization approach to solve assembly sequence planning problem
Published 2022“…Production scheduling is a complex combined optimization problem and the optimization method of which is not perfect [1]. …”
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7
Design and modelling of an autonomous robotic airship with soft computing control
Published 2012“…Along with the prototype airship, a path planner was also proposed for the UAV for the purpose of obstacle avoidance and path optimization using genetic algorithm to minimize on the distance travelled and to generate the shortest path to cover the specified waypoints. …”
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8
Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems
Published 2023“…To exhibit superior performance of GAOB-EACP method, an extensive range of simulations can be implemented. …”
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Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. …”
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10
IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks
Published 2024“…Additionally, simulation results confirm that the proposed algorithm IWDSA exhibits outstanding performance compared to other algorithms utilizing optimization techniques, including genetic algorithms, bat algorithms, ant colony optimization, and swarm optimization. …”
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Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space
Published 2015“…The simulated robot is equipped with a sonar sensor and several infrared sensors on its chassis. …”
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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
Published 2020“…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
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13
Deterministic static sensor node placement in wireless sensor network based on territorial predator scent marking behavior
Published 2023“…This paper proposes a sensor node placement algorithm that utilizes a new biologically inspired optimization algorithm that imitates the behaviour of territorial predators in marking their territories with their odours known as Territorial Predator Scent Marking Algorithm (TPSMA). …”
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Provisioning an energy efficient with maximum coverage WSN through biological inspired sensor node placement
Published 2023Conference Paper -
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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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Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network
Published 2014“…This study proposed Extended Virtual Force and Cuckoo Search (EVFCS) algorithm with a combination of EVFA and CS algorithm to find an optimal node placement. …”
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17
Multi-objective biological mimicry optimization algorithm for WSN sensor node placement
Published 2023Conference Paper -
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Chaotic Mapping Lion Optimization Algorithm-Based Node Localization Approach for Wireless Sensor Networks
Published 2023“…Keywords: anchor nodes; metaheuristic optimization algorithm; node localization; tent chaotic mapping; wireless sensor networks…”
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Wireless sensor network deployment performance based on FOA, PSO and TPSMA / Nurhidayah Kamal Akbar, Husna Zainol Abidin, and Ahmad Ihsan Mohd Yassin
Published 2019“…This paper compares the random deployment with other two algorithms known as Fruit Fly Optimization (FOA) and Particles Swarm Optimization (PSO) Territorial Predator Scent Marking Algorithm (TPSMA) to solve the coverage hole problem. …”
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An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks
Published 2015“…We first model the network energy consumption and then determine the optimal number of clusters for the network. The problem of selecting an optimal cluster is formulated as a Markov Decision Process (MDP) in the algorithm and the obtained simulation results show convergence, learning and adaptability of the algorithm to dynamic environment towards achieving an optimal solution. …”
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