Search Results - (( based application drops algorithm ) OR ( using optimization based algorithm ))

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  1. 1

    Modified And Ensemble Intelligent Water Drop Algorithms And Their Applications by O. F. Alijla, Basem

    Published 2015
    “…The Intelligent Water Drop (IWD) algorithm is a swarm-based model that is useful for undertaking optimization problems. …”
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    Thesis
  2. 2

    Hybrid Improved Bacterial Swarm Optimization Algorithm for Hand-Based Multimodal Biometric Authentication System by Shanmugasundaram, Karthikeyan, Mohmed, Ahmad Sufril Azlan, Ruhaiyem, Nur Intan Raihana

    Published 2019
    “…Concurrently, the local optima trap (i.e., premature convergence) of PSO algorithm was averted by using mutation operator. The HIBS algorithm was tested using benchmark functions and compared against classical BFO, PSO and other hybrid algorithms like Genetic Algorithm-Bacterial Foraging Optimization (GA-BFO), Genetic Algorithm-Particle Swarm Optimization (GA-PSO) and other BFO-PSO algorithms to prove its exploration and exploitation ability. …”
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    Article
  3. 3

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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    Thesis
  4. 4

    Optimization of electrical wiring design in buildings using particle swarm optimization and genetic algorithm / Tuan Ahmad Fauzi Tuan Abdullah by Tuan Ahmad Fauzi, Tuan Abdullah

    Published 2017
    “…In this project, the main objective is to optimize the electrical distribution system design in buildings using optimization methods, which are Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). …”
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    Thesis
  5. 5

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
    Article
  6. 6

    Vehicle pick-up and drop-off schedule optimization in a university setting by Teo, Chun Kit

    Published 2024
    “…A simulated annealing-based multi-directional iterative local search algorithm is employed for solution optimization. …”
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    Final Year Project / Dissertation / Thesis
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    Mathematical modelling of mass transfer in a multi-stage rotating disc contactor column by Maan, Normah

    Published 2005
    “…This new modelling approach gives useful information and provides a faster tool for decision-makers in determining the optimal input parameter for mass…”
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    Thesis
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    On determination of input parameters of the mass transfer process by fuzzy approach. by Maan, Normah, Talib, Jamalludin, Arshad, Khairil Annuar, Ahmad, Tahir

    Published 2005
    “…This is an extension of the work done on the mass transfer process of a single drop in single stage RDC column. The algorithm is based on fuzzy approach and the assumptions made in mass transfer process as adopted in previous work are also being used. …”
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    Article
  11. 11

    Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

    Published 2022
    “…The study also developed an algorithm for predictive EMS using fuzzy model predictive control technique based on regression algorithm. …”
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    Thesis
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    Benchmark simulator with dynamic environment for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana

    Published 2014
    “…Characteristics of jobs and resources to be used in evaluating the performance of the scheduling algorithm must reflect the dynamic nature of real grid environment.Static models of jobs and resources cannot be used to generate jobs and resources in simulating the grid environment because of the dynamic nature of the grid.This paper presents a new graph representation of jobs and resources which is practical for hybrid metaheuristic model implementation such as ant colony optimization and genetic algorithm.A dynamic model that can generate jobs and resources similar to the jobs and resources in the real grid environment is also proposed.Jobs and resources may join in or drop out from the grid.Stochastic analysis is performed on the characteristics of jobs and resources.A simulator based on the dynamic expected time to compute, has been developed and can be used as a benchmark.The simulator can generate jobs and resources with the characteristics of jobs and resources in the real grid environment.This will facilitates the evaluation of dynamic job scheduling algorithm.…”
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    Conference or Workshop Item
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    Development of a scalable video compression algorithm by Khalifa, Othman Omran, Issa, Sinzobakwira, Olanweraju, Rashidah Funke, Al Khazmi, El Mahdi A

    Published 2012
    “…The result shows that the managed complexity algorithm based on Lagrangian Multiplier function outperforms the normal encoder. …”
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    Proceeding Paper
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    Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks by Saleh, Ahmed Mohammed Shamsan

    Published 2012
    “…Finally, we propose Self-Decision Route Selection scheme which is an improvement of the Hop-based Spanning Tree (HST) algorithm that is used in some routing protocols such as AODV and DSR. …”
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    Thesis
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    A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines by Tahan, M., Muhammad, M., Abdul Karim, Z.A.

    Published 2017
    “…Two back-propagation training algorithms, namely the Levenberg–Marquardt and Bayesian regularization algorithms, and the k-fold cross-validation technique, were employed to train the optimal networks using a training data set. …”
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    Article
  20. 20

    A real-time integrated fire detection and alarm (FDA) system for network based building automation by Anwar, Farhat, Islam, Rounakul, Hussain, Sabahat, Rashid, Muhammad Mahbubur, Shaikh, Zuhaib

    Published 2017
    “…The framework shares information through the algorithm and communicates with each fire alarm panels connected in peer to peer configuration to declare the network state in every second using network address. …”
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    Article