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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
    A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles

    A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles by Abdulhasan Al-Jarah, Ali Husam

    Published 2017
    “…In a previous research, a relocating algorithm for mobile sensor network had been introduced and the goal was to save energy and prolong the lifetime of the sensor networks using Particle Swarm Optimization (PSO) where both of sensing radius and travelled distance had been optimized in order to save energy in long-term and shortterm. …”
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  3. 3
    Design, optimization and fabrication of a climbing six articulated-wheeled robot using artificial evolution and 3D printing

    Design, optimization and fabrication of a climbing six articulated-wheeled robot using artificial evolution and 3D printing by Lim, Shun Hoe, Teo, Jason Tze Wi

    Published 2015
    “…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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  4. 4
    An improved gbln-pso algorithm for indoor localization problem in wireless sensor network

    An improved gbln-pso algorithm for indoor localization problem in wireless sensor network by Muhammad Shahkhir, Mozamir

    Published 2022
    “…Then, we compared the result with Particle Swarm Optimization (PSO), Differential Evolution Particle Swarm Optimization (DEPSO), Health Particle Swarm Optimization (HPSO) and Global best Local Neigborhood Particle Swarm Optimization (GbLN-PSO) algorithm. …”
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  5. 5
    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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  6. 6
    Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network

    Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network by Sama, Najm Us

    Published 2019
    “…In the proposed work, the focused problem is how to reduce the communication energy consumption and to avoid the routing hole problem by optimized routing algorithms. First, a routing hole detection algorithm is proposed prior to designing the routing protocol which decreases about 30 percent energy consumption rate, detection time and detection overhead. …”
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  7. 7
    Curve fitting by rational cubic Bézier with C1 and G1 continuity using metaheuristics methods

    Curve fitting by rational cubic Bézier with C1 and G1 continuity using metaheuristics methods by Najihah, Mohamed, Ahmad Lutfi, Amri Ramli, Ahmad, Abd Majid, Abd Rahni, Mt Piah

    Published 2019
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  8. 8
    Data fitting by G1 rational cubic Be´zier curves using harmony search

    Data fitting by G1 rational cubic Be´zier curves using harmony search by Mohamed, Najihah, Majid, Ahmad Abd, Piah, Abd Rahni Mt

    Published 2015
    “…A metaheuristic algorithm, called Harmony Search (HS) is implemented for data fitting by rational cubic Be´ zier curves. …”
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  9. 9
    A secure trust aware ACO-Based WSN routing protocol for IoT

    A secure trust aware ACO-Based WSN routing protocol for IoT by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A., Hassan Abdalla Hashim, Aisha

    Published 2022
    “…The performance of the proposed routing algorithm is demonstrated through MATLAB. Based on the proposed system, to find the secure and optimal path while aiming at providing trust in IoT environment, the average energy consumption is minimized by nearly 50% even as the number of nodes has increased, as compared with the conventional ACO algorithm, a current ant-based routing algorithm for IoT-communication, and a present routing protocol RPL for IoT.…”
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  10. 10
    Comparison between Cubic Bezier curve, Rational Cubic Bezier curve and Rational Cubic Timmer curve with the application of Arabic Calligraphy design / Nurhusnina Md Radhi

    Comparison between Cubic Bezier curve, Rational Cubic Bezier curve and Rational Cubic Timmer curve with the application of Arabic Calligraphy design / Nurhusnina Md Radhi by Md Radhi, Nurhusnina

    Published 2018
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  11. 11
    Artificial neural controller synthesis for TORCS

    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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  12. 12
    Data Fitting by G1 Rational Cubic Bézier Curves Using Harmony Search

    Data Fitting by G1 Rational Cubic Bézier Curves Using Harmony Search by Najihah, Mohamed, Ahmad, Abd Majid, Abd Rahni, Mat Piah

    Published 2015
    “…A metaheuristic algorithm, called Harmony Search (HS) is implemented for data fitting by rational cubic Bézier curves. …”
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  13. 13
    Rational Bi-Quartic Spline with Six Parameters for Surface Interpolation with Application in Image Enlargement

    Rational Bi-Quartic Spline with Six Parameters for Surface Interpolation with Application in Image Enlargement by Karim, S.A.A.

    Published 2020
    “…This rational bi-quartic spline has six free parameters that can be used to refine the final interpolating surface. …”
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  14. 14
    Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms

    Automatic design, optimization and In-Situ Fabrication of Heterogeneous Swarm Robot bodies using 3-D printing and multi-objective evolutionary algorithms by Teo, Jason Tze Wi, Johnny Koh, Chin, Kim On, Chua, Bih Lii, Willey Liew, Noor Ajian Mohd. Lair, Lim, Shun Hoe

    Published 2012
    “…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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  15. 15
    An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines

    An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines by Bala, A., Ismail, I., Ibrahim, R., Sait, S.M., Oliva, D.

    Published 2020
    “…This problem is often formulated as a typical optimization problem. Metaheuristic algorithms are known to be excellent tools for solving optimization problems. …”
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  16. 16
    Smart agriculture: precision farming through sensor-based crop monitoring and control system

    Smart agriculture: precision farming through sensor-based crop monitoring and control system by Mohamad Hakhrani, Asyful Azhim, Abdul Hamid, Syamsul Bahrin

    Published 2024
    “…Subsequently, four distinct algorithms are trained with the collected dataset to ascertain the most optimal algorithm for predicting crop growth and harvesting time, resulting in the selection of the Random Forest Regression model, which attains the highest model score of 86%. …”
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  17. 17
    Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization

    Representation Of Rational Bézier Quadratics Using Genetic Algorithm, Differential Evolution And Particle Swarm Optimization by Yahya, Zainor Ridzuan

    Published 2013
    “…These techniques have been used to optimize control points and weights in the description of spline functions used. …”
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  18. 18
    Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function

    Curve Reconstruction By Metaheuristics Algorithms On Cubic Rational Bézier Function by Mohamed, Najihah

    Published 2019
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  19. 19
    Applications and comparison of quadratic and cubic rational Bezier curve on batik design / Muhammad Izhar Ishak

    Applications and comparison of quadratic and cubic rational Bezier curve on batik design / Muhammad Izhar Ishak by Ishak, Muhammad Izhar

    Published 2017
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  20. 20
    Designing of skull defect implants using C1 rational cubic Bezier and offset curves

    Designing of skull defect implants using C1 rational cubic Bezier and offset curves by Najihah, Mohamed, Ahmad, Abd Majid, Abd Rahni, Mt Piah, Zainul, Ahmad Rajion

    Published 2015
    “…In this study, data approximation by a rational cubic Bézier function uses HS to optimize position of middle points and value of the weights. …”
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