Search Results - (( simulation optimization sensor algorithm ) OR ( using optimization strategy algorithm ))

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  1. 1

    Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm by Arezoumand, Reza

    Published 2015
    “…Employing a multi-robot system and path planning with spanning tree algorithm is a strategy for speeding up sensor node deployment. …”
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    Node placement strategy in wireless sensor network by Ahmad, Puteri Azwa, Mahmuddin, Massudi, Omar, Mohd Hasbullah

    Published 2013
    “…Simulation results proofed that a uniform deployment achieved using VFA approach with an optimal sensing range to cover the region of interest.…”
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  4. 4

    Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

    Published 2014
    “…There are two prevailing strategies used to collect data in sensor networks. …”
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    Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter by Solouk, Vahid, Taghizadeh, Hamid, Moghanjoughi, Ayyoub Akbari, Razm, S. K.

    Published 2013
    “…The proposed algorithms provide precise state estimates in a moment as global state estimates using various updates at each step. …”
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  7. 7

    Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan by Khan, Muhammad Zafar Iqbal

    Published 2022
    “…Using the simulation software, it was observed that the alive nodes are higher in numbers i.e. 189 nodes after 500 rounds for the proposed routing algorithm compared to the previous methods which had only 150 alive nodes. …”
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  8. 8

    PID-PSO DC motor position controller design for ankle rehabilitation system by Azizi, Muhammad Azizul Raziq

    Published 2023
    “…The control algorithms also aim to be analyzed using an incremental rotary encoder sensor device as closed-loop feedback for dorsiflexion and plantarflexion movement. …”
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    Artificial neural controller synthesis for TORCS by Shi, Jun Long

    Published 2015
    “…The results showed: (1) DE hybrid FFNN could generate optimal controllers, (2) the proposed fitness function had successfully generated the required car's racing controllers, (3) the proposed minimization algorithm had been successfully minimize the number of RF sensors used, (4) the PDE algorithm could be implemented to generate optimal solutions for car racing controllers, and (5) the combination of components for average car speed and distance between the car and track axis is very important compared to other components. …”
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    Non-weighted aggregate evaluation function of multi-objective optimization for knock engine modeling by Witwit, Azher Razzaq Hadi

    Published 2017
    “…It also aims to optimize the nonlinear nature of the factors by using Genetic Algorithm (GA) as well as investigate the behavior of such function. …”
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  12. 12

    Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Kamarulzaman, Ab Aziz, Nor Hidayati, Abdul Aziz

    Published 2019
    “…Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. …”
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    Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid by Gaeid, Khalaf Salloum

    Published 2012
    “…In this work however, the fault protection is an additional feature of the control system, where the wavelet based fault tolerant system has been tested and simulated using a 1kW IM, which has a short stator winding and sensor faults, while the primary faults are open stator winding. …”
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    IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

    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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  15. 15

    Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space by Zahari, Ammar, Ismail , Amelia Ritahani, Desia, Recky

    Published 2015
    “…The simulated robot is equipped with a sonar sensor and several infrared sensors on its chassis. …”
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  16. 16

    Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

    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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    Deterministic static sensor node placement in wireless sensor network based on territorial predator scent marking behavior by Abidin H.Z., Din N.M., Radzi N.A.M.

    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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    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    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 by Puteri Azwa, Ahmad

    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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