Search Results - (( user optimization method algorithm ) OR ( parameter optimization approach algorithm ))

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  1. 1
    A swarm intelligent approach for multi-objective optimization of compact heat exchangers

    A swarm intelligent approach for multi-objective optimization of compact heat exchangers by Yousefi M., Yousefi M., Martins Ferreira R.P., Darus A.N.

    Published 2023
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  2. 2
    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm

    Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

    Published 2020
    “…We applied a deep extreme learning machine approach to predict the user parameters. We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
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  3. 3
    Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks

    Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks by Hussein, Yassein Soubhi

    Published 2014
    “…The results demonstrated that our proposed method results in significant reductions of HOF, HOPP and packet loss ratio (PLR) compared to the conventional HHO and enhanced weighted performance HO parameter optimization (EWPHPO) algorithm. …”
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    Thesis
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  4. 4
    Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil

    Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

    Published 2024
    “…Extensive experimentation with genetic algorithm parameters has yielded promising results, notably a parameter set (population size = 12, generation size = 30, mutation rate = 0.2) demonstrating robust performance, achieving optimal timetables with swift convergence and minimal conflicts. …”
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  5. 5
    Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan Abdul Manan

    Classification of Google Play application using decision tree algorithm on sentiment analysis of text reviews / Aqil Khairy Hamsani, Ummu Fatihah Mohd Bahrin and Wan Dorishah Wan A... by Hamsani, Aqil Khairy, Mohd Bahrin, Ummu Fatihah, Wan Abdul Manan, Wan Dorishah

    Published 2023
    “…To achieve these objectives, the methods employed involve data preprocessing and implementing the Decision Tree (DT) algorithm for classification. …”
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  6. 6
    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks

    Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

    Published 2025
    thesis::doctoral thesis
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  7. 7
    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems

    Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

    Published 2018
    “…The major contribution of this research is to propose MTS method for solving UTSP in both sequential and parallel approach and it is shown that the algorithms are able to produce comparable results for most of the cases from literature and the computational times can be reduced significantly for more than 80% by the parallel execution. …”
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  8. 8
    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach

    Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

    Published 2022
    “…The other one is the network training’s environment optimization that is done through hyperparameter optimization by selecting and fine-tuning high impact parameters which include Optimizer, Learning Rate and Dropout to reduce error rate (loss function). …”
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  9. 9
    3D virtual modelling and stabilization control of triple links inverted pendulum on two-wheeled system using enhanced interval type-2 fuzzy logic control

    3D virtual modelling and stabilization control of triple links inverted pendulum on two-wheeled system using enhanced interval type-2 fuzzy logic control by Muhammad Firdaus, Masrom

    Published 2020
    “…Without a specific method introduced to determine the optimal values of input and output control gains, as well as the IT2FLC control parameters, optimization algorithm has been applied to enhance the system's performance in term of stability and disturbance rejection. …”
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  10. 10
    OFF-GRID SOLAR PHOTOVOLTAIC (PV) DESIGN BASED ON FUZZY TECHNIQUE FOR ORDER PERFORMANCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) APPROACH

    OFF-GRID SOLAR PHOTOVOLTAIC (PV) DESIGN BASED ON FUZZY TECHNIQUE FOR ORDER PERFORMANCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) APPROACH by NUR AFIQAH, JAHILAN

    Published 2022
    “…Precisely, the fuzzy TOPSIS algorithm has selected the best configuration of PV system with financial optimization feature. …”
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    Final Year Project Report / IMRAD
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  11. 11
    Distributed power control and beamforming for cognitive two-way relay networks using a game-theoretic approach

    Distributed power control and beamforming for cognitive two-way relay networks using a game-theoretic approach by Iranpanah, Havzhin, Mohd Ali, Borhanuddin, Hashim, Fazirulhisyam, Mohamad, Hafizal

    Published 2016
    “…We propose a distributed power control and beamforming algorithm that enables the users operating in the underlay mode to strategically adapt their power levels, and maximize their own utilities subject to the primary user (PU) interference constraint, as well as its own resource and target signal-to-interference-and-noise-ratio (SINR) constraints. …”
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    Conference or Workshop Item
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  12. 12
    Analysis and decentralised optimal flow control of heterogeneous computer communication network models

    Analysis and decentralised optimal flow control of heterogeneous computer communication network models by Ku-Mahamud, Ku Ruhana

    Published 1993
    “…The optimal local flow control with global objectives results in a team decision that does not favour any individual user, and depends only on the relative order of their packet generation rates. …”
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  13. 13
    Dynamic approaches for spectrum control in cognitive radio networks

    Dynamic approaches for spectrum control in cognitive radio networks by Mohamedou, Ahmed

    Published 2015
    “…Two artificial intelligence techniques are utilized which are Fuzzy Inference and Bayesian Inference. To optimize Fuzzy Inference scheduler, Genetic Algorithm is used. …”
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  14. 14
    Development of compound clustering techniques using hybrid soft-computing algorithms

    Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

    Published 2006
    “…Initially, the heuristics needs user intervention to select optimal values, which give poor results. …”
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    Monograph
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  15. 15
    Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem

    Heterogenous adaptive ant colony optimization with 3-opt local search for the travelling salesman problem by Tuani Ibrahim, Ahamed Fayeez, Keedwell, Edward, Collett, Matthew

    Published 2020
    “…The majority of optimization algorithms require proper parameter tuning to achieve the best performance. …”
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  16. 16
    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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  17. 17
    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences

    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences by Leong, Wah June, Sie, Long Kek, Teo, Kok Lay, Sim, Sy Yi

    Published 2018
    “…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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  18. 18
    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference

    Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

    Published 2018
    “…In our approach, the linear quadratic optimal control model, which is adding the adjusted parameters into the model used, is employed. …”
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  19. 19
    Machining optimization using Firefly Algorithm / Farhan Md Jasni

    Machining optimization using Firefly Algorithm / Farhan Md Jasni by Md Jasni, Farhan

    Published 2020
    “…Based on the previous research on the success of Firefly Algorithm, this approach will be able to optimize the machining parameter of milling operation. …”
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    Student Project
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  20. 20
    Hybrid ACO and SVM algorithm for pattern classification

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    Published 2013
    “…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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