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  1. 1

    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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    Article
  2. 2

    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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    Thesis
  3. 3

    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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    Article
  4. 4

    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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    Thesis
  5. 5

    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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    Article
  6. 6

    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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    Thesis
  7. 7

    Adaptive beamforming algorithm based on Simulated Kalman Filter by Kelvin Lazarus, Lazarus

    Published 2017
    “…Some of the metaheuristic algorithms have been modified from the original algorithms to improve the algorithms performance in adaptive beamforming application. …”
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    Thesis
  8. 8

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Testing on real data sets showed consistency results as the simulated ones. Generally, the proposed modified k-means algorithm is able to determine the optimum number of clusters for huge data.…”
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    Thesis
  9. 9

    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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    Article
  10. 10

    Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm by Zeni, Saltihie

    Published 2012
    “…This document is a study about LEACH algorithm where the implementation was done using OMNeT++ network simulator to study the performance of this algorithm in term of network lifetime. …”
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    Thesis
  11. 11

    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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    Thesis
  12. 12

    A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and Swap Operator by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2021
    “…The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. …”
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    Conference or Workshop Item
  13. 13

    1D Multigrid Solver For Finite Element Method by Azhar, Mohamad Amiruddin

    Published 2022
    “…The new algorithm also has been tested using time simulation. …”
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    Monograph
  14. 14

    Comparison of path planning in simulated robot by Ch’ng, Chee Yu’ng

    Published 2020
    “…There are 4 path planning algorithms will be compared, which are Dijkstra’s algorithm, A* algorithm, RapidExploring Random Tree (RRT) algorithm, and the last one is an algorithm modified from A*. …”
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    Final Year Project / Dissertation / Thesis
  15. 15

    Estimation of the denitrification in the lower Mississippi Valley by Saleh, Abdul Razak

    Published 2001
    “…The CREAMS denitrification algorithm was modified to account for the high soil moisture conditions by incorporating a water function.The average annual denitrification value simulated by using modified algorithm was higher than the one predicted by CREAMS algorithm.This result is expected because the modified algorithm uses a water function to reflect the degree of soil saturation.…”
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    Conference or Workshop Item
  16. 16

    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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    Research Report
  17. 17

    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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    Article
  18. 18

    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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    Article
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