Search Results - (( wave optimization _ algorithm ) OR ( using optimization sensor algorithm ))

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  1. 1

    Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors by Binajjaj, Saeed Ali Saeed

    Published 2010
    “…Computation of the sensitivity function required two successive steps: (i) the forward (direct) propagation of the UWB wave-field, and (ii) the reverse (adjoint) propagation of the residual waves. …”
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    Thesis
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    A miniature stub-loaded antenna optimized at VHF band for FSR sensor application / Hasrul Hisyam Harun by Harun, Hasrul Hisyam

    Published 2014
    “…Antenna design in this paper simulated using Computer Simulation Technique (CST) and introduced Parameter Sweep and Genetic Algorithm (GA) technique to determine the optimal lengths of antenna and stubs. …”
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    Thesis
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    Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

    Published 2023
    “…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”
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    Feasibility study on utilization of stub loaded miniature monopole antenna for forwards scattering micro-radar (FSR) network project: article / Hamid Salim by Salim, Hamid

    Published 2013
    “…The performance parameter which would be evaluate consists of the operating frequency, the wavelength, return loss (S11), antenna gain, beamwidth, line impedance and Voltage Standing Wave Ratio (VSWR). The result obtained from both execution of Genetic Algorithm (GA) optimization and Parameter Sweep analysisis presented and conclude by future work recommendations for the continuity of this research.…”
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    Article
  6. 6

    Feasibility study on utilization of stub loaded miniature monopole antenna for forwards scattering micro-radar (FSR) network project / Hamid Salim by Salim, Hamid

    Published 2013
    “…The performance parameter which would be evaluate consists of the operating frequency, the wavelength, return loss (S1 1), antenna gain, beamwidth, line impedance and Voltage Standing Wave Ratio (VSWR). The result obtained from both execution of Genetic Algorithm (GA) optimization and Parameter Sweep analysisis presented and conclude by future work recommendations for the continuity of this research.…”
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    Thesis
  7. 7

    Bayesian Network Classifiers for Damage Detection in Engineering Material by Mohamed Addin, Addin Osman

    Published 2007
    “…To validate the classi¯ers and the proposed algorithm, two data sets were used, the ¯rst set represents voltage amplitudes of Lamb-waves produced and col- lected by sensors and actuators mounted on the surface of laminates contain di®erent arti¯cial damages. …”
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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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    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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  12. 12

    Inversion Of Surface Wave Phase Velocity Using New Genetic Algorithm Technique For Geotechnical Site Investigation by Hamimu, La

    Published 2011
    “…Therefore the use of genetic algorithm (GA) optimization technique which is one of nonlinear optimization methods is an appropriate choice to solve surface wave inversion problem having high nonlinearity and multimodality. …”
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    Global optimization method for continuous - Time sensor scheduling by Woon, Siew Fang, Rehbock, Volker, Loxton, Ryan C.

    Published 2010
    “…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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    Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

    Published 2017
    “…The main contribution of the paper is to introduce a dynamic programming algorithm, which defines an optimal policy for solving the visual sensor coverage problem. …”
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    A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network by Gumaida, Bassam, Abubakar, Adamu

    Published 2024
    “…Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other op- timization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). …”
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    A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization by ., Nurul Mu’azzah Abdul Latiff NikNoordini, NikAbdMalik Abdul Halim

    Published 2016
    “…One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm.…”
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