Search Results - (( simulation optimization sensor algorithm ) OR ( problem implementation bee algorithm ))
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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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2
Application of Bee Colony Optimization (BCO) in NP-Hard Problems
Published 2011“…P-Median problem will be used as the main case study in implementing one of the Bee-Inspired algorithms to prove, illustrate example and show the characteristics of the selected concept…”
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3
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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4
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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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem
Published 2023“…The Artificial Bee Colony (ABC) algorithm has gained widespread attention and has been applied in various fields due to its ability to achieve excellent global optimization results and ease of implementation. …”
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Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin
Published 2022“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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Research Reports -
7
Bees algorithm enhanced with Nelder and Mead method for numerical function optimisation
Published 2019“…The Bees Algorithm is a population-based optimisation algorithm inspired by the food foraging behaviour of honey bees. …”
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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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An improved bees algorithm local search mechanism for numerical dataset
Published 2015“…Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental search techniques is based on the food foraging activities of bees. …”
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Thesis -
10
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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11
A true annealing approach to the marriage in honey-bees optimization algorithm
Published 2003“…The modified algorithm is tested using a group of randomly generated hard 3-SAT problems to compare its behavior and efficiency against previous implementations. …”
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Minimizing the total cost of inventory by using artificial bee colony algorithm / Nurul Syakira Mohd Zin
Published 2021“…The algorithm characterised a swarm-based meta-heuristic algorithm comprised of three divisions of bee troops in the ABC model, namely employed, onlooker, and scout bees. …”
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Student Project -
13
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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15
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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Thesis -
16
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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18
Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…Recently, an attractive bio-inspired method—namely the Artificial Bee Colony (ABC)—has shown outstanding performance with some typical computational algorithms in different complex problems. …”
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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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