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  1. 1
    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm

    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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  2. 2
    Provisioning an energy efficient with maximum coverage WSN through biological inspired sensor node placement

    Provisioning an energy efficient with maximum coverage WSN through biological inspired sensor node placement by Abidin H.Z., Din N.M.

    Published 2023
    Conference Paper
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  3. 3
    Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network

    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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  4. 4
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks / Salmah Fattah by Salmah , Fattah

    Published 2022
    “…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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  5. 5
    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks

    A hybrid multi-objective optimisation for energy efficiency and better coverage in underwater wireless sensor networks by Salmah Fattah

    Published 2022
    “…Next, it establishes the research problems by implementing various existing algorithms using comparative analysis. Based on that analysis, this research suggests a hybrid algorithm: the Multi-Objective Optimisa­tion Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy). …”
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  6. 6
    The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications

    The Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP) Method for Solving Wireless Sensor Networks Optimization Problems in Smart Grid Applications by Shehadeh, Hisham A., Idris, Mohd Yamani Idna, Ahmedy, Ismail, Ramli, Roziana, Noor, Noorzaily Mohamed

    Published 2018
    “…To do this, a smart grid application case study together with a WSN QoS model is used to find the optimal value of the packet payload size. Our proposed method, named Multi-Objective Optimization Algorithm Based on Sperm Fertilization Procedure (MOSFP), along with other three state-of-The-Art multi-objective optimization algorithms known as OMOPSO, NSGA-II and SPEA2, are utilized in this study. …”
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  7. 7
    Adaptive Algorithm for Optimal Route Configuration in Multi-Hop Wireless Sensor Network

    Adaptive Algorithm for Optimal Route Configuration in Multi-Hop Wireless Sensor Network by Shabani, Hikma, Ahmed Mohamed, Ahmed Haidar, Norhuzaimin, Julai, Musse, Mohamud Ahmed, Hoole, P.R.P., Marai, Majdi

    Published 2017
    “…This paper proposes an optimal route configuration technique based on an adaptive genetic algorithm in which the architecture of multi-hop wireless sensor network is considered as a distributed computing infrastructure. …”
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  8. 8
    Wireless sensor network deployment performance based on FOA, PSO and TPSMA / Nurhidayah Kamal Akbar, Husna Zainol Abidin, and Ahmad Ihsan Mohd Yassin

    Wireless sensor network deployment performance based on FOA, PSO and TPSMA / Nurhidayah Kamal Akbar, Husna Zainol Abidin, and Ahmad Ihsan Mohd Yassin by Kamal Akbar, Nurhidayah, Zainol Abidin, Husna, Mohd Yassin, Ahmad Ihsan

    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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  9. 9
    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system

    Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2018
    “…That is why, image template matching problem is now considered as an optimization problem. By implementing optimization algorithm in image template matching, it is expected that the computation time can be reduced. …”
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  10. 10
    WSN sensor node placement approach based on multi-objective optimization

    WSN sensor node placement approach based on multi-objective optimization by Abidin H.Z., Din N.M., Radzi N.A.M.

    Published 2023
    Conference Paper
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  11. 11
    Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building

    Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    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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  12. 12
    Transmission path optimization Based on Efficiency Communication System

    Transmission path optimization Based on Efficiency Communication System by Jin Fan, Kit, Guan Lim, Sin, Helen Ee Chuo, Min, Keng Tan, Ali Farzamnia, Tze, Kenneth Kin Teo

    Published 2022
    “…This paper points out the research focus of the wireless sensor network transmission path and discusses the optimization problem of the transmission based on grid model. …”
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  13. 13
    Optimization of ANPR algorithm on android mobile phone

    Optimization of ANPR algorithm on android mobile phone by Mutholib, Abdul, Gunawan, Teddy Surya, Chebil, Jalel, Kartiwi, Mira

    Published 2013
    “…Our proposed algorithm was based on Tesseract library. For comparison purpose, the template matching based OCR will be compared to Artificial Neural Network (ANN) based OCR. …”
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  14. 14
    Whale optimization algorithm strategies for higher interaction strength t-way testing

    Whale optimization algorithm strategies for higher interaction strength t-way testing by Ali Abdullah, Hassan, Salwani, Abdullah, Kamal Z., Zamli, Rozilawati, Razali

    Published 2022
    “…To ensure that WOA conquers premature convergence and avoids local optima for large search spaces (owing to high-order interaction), three variants of WOA have been developed, namely Structurally Modified Whale Optimization Algorithm (SWOA), Tolerance Whale Optimization Algorithm (TWOA), and Tolerance Structurally Modified Whale Optimization Algorithm (TSWOA). …”
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  15. 15
    Optimization in active vibration control: virtual experimentation using COMSOL multiphysics - MATLAB integration

    Optimization in active vibration control: virtual experimentation using COMSOL multiphysics - MATLAB integration by Md Nor, Khairul Affendy, Abdul Muthalif, Asan Gani, Wahid, Azni N.

    Published 2014
    “…Ant colony optimization algorithm is employed for this purpose. …”
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  16. 16
    Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming

    Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Sebastian, P., Hamid, N.H.B., Ahmed, E.F.

    Published 2022
    “…Thus, related surveillance planning methods optimize the placement of visual sensors based on equally significance grids by not limiting to demand of coverage. …”
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  17. 17
    Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh

    Single-objective and multi-objective optimization algorithms based on sperm fertilization procedure / Hisham Ahmad Theeb Shehadeh by Hisham Ahmad, Theeb Shehadeh

    Published 2018
    “…In this work, Single Objective Optimization Algorithm (SOOA) is proposed. The SOOA version is extended to Multi Objective Optimization Algorithm (MOOA). …”
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  18. 18
    IOT-based fertigation system / Mohamad Amir Furqan Darus

    IOT-based fertigation system / Mohamad Amir Furqan Darus by Darus, Mohamad Amir Furqan

    Published 2024
    “…It integrates the MDD3A Cytron motor driver for water pump control and the Ph sensor to monitor soil acidity or alkalinity. Using advanced algorithms and machine learning techniques, the system nalyses the collected data to determine optimal irrigation and fertilization requirements. …”
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  19. 19
    A green clustering protocol for mobile sensor network using particle swarm optimization

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. …”
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  20. 20
    A green clustering protocol for mobile sensor network using particle swarm optimization

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. We define a new fitness function that can optimize the energy consumption of the whole network and minimize the relative distance between cluster heads and their respective member nodes. …”
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