Search Results - (( parameter optimization search algorithm ) OR ( evolution optimization based algorithm ))*

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  1. 1

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
    “…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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    Thesis
  2. 2

    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…Other metaheuristic approaches such as genetic algorithm, differential evolution algorithm, particle swarm optimization, and ant colony optimization are still preferable to address combinatorial optimization problems. …”
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    Article
  3. 3

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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  4. 4

    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

    Published 2012
    “…It is noted that active user intervention increases the acceleration of Genetic Algorithm towards an optimal solution. In proposed research work, the user is aided by a visualization based on the representation of multidimensional Genetic Algorithm data on 2-0 space. …”
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  5. 5

    Hybrid DE and PEM algorithm for identification of small scale Autonomous helicopter model by Legowo, Ari

    Published 2012
    “…The proposed hybrid identification method explored the evolutionary search optimization strength of DE for parameter initialization for PEM identification algorithm…”
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    Monograph
  6. 6

    A filtering algorithm for efficient retrieving of DNA sequence by Abdul Rahman, Mohd Nordin, Mohd. Saman, Md. Yazid, Ahmad, Aziz, Md. Tap, Abu Osman

    Published 2009
    “…An optimal alignment process based on the dynamic programming algorithms has shown to have O(n m) time and space complexity. …”
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    Article
  7. 7

    Application of manta ray foraging optimization with gradient-based mutation (cMRFO) for solving power system problems by Ahmad Azwan, Abd Razak, Ahmad Nor Kasruddin, Nasir

    Published 2023
    “…In this paper, the Manta Ray Foraging Optimization (MRFO) algorithm is applied to solve real parameter constrained optimization problems, using the Gradient-based Mutation MRFO (cMRFO) variant. …”
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    Conference or Workshop Item
  8. 8

    Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation by Tey, Kok Soon, Mekhilef, Saad, Seyedmahmoudian, Mehdi, Horan, Ben, Oo, Amanullah Than, Stojcevski, Alex

    Published 2018
    “…The main contribution of the proposed algorithm are the following: capability in tracking GMPP and faster respond against load variation; optimization algorithm can search for the GMPP within a larger operating region as it is implemented by using a single-ended primary-inductor converter; and easy tuning as less parameter has to be set in the algorithm. …”
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    Article
  9. 9

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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    Thesis
  10. 10

    Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

    Published 2018
    “…A trend that has emerged recently is to make the algorithm parameters automatically adapt to different problems during optimization, thereby liberating the user from the tedious and time-consuming task of manual setting. …”
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    Article
  11. 11
  12. 12

    Differential evolution with improved sub-route reversal repair mechanism for multiobjective urban transit routing problem by Tarajo, Buba Ahmed, Lee, Lai Soon

    Published 2018
    “…In this paper, an improved sub-route reversal repair mechanism is proposed to deal with the infeasibility. A population-based metaheuristic, namely, Differential Evolution (DE) algorithm is then proposed to handle the multiobjective UTRP with the aim of devising an efficient transit route network that optimizes both passengers' and operators' costs. …”
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    Article
  13. 13

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…Weakness such as trapped in local minima, slow convergence and finding a good rate between exploitation and exploration of the search space. This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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    Thesis
  14. 14

    Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai, V., Ahmed, Ali Najah, Malek, Marlinda Abdul, El-Shafie, Ahmed, El-Shafie, Amr

    Published 2018
    “…GP is a meta-heuristic search and optimization technique based on natural evolution. …”
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    Article
  15. 15

    Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems by Ahmad Azwan, Abdul Razak, Ahmad Nor Kasruddin, Nasir

    Published 2022
    “…In this paper, a new variant of Manta Ray Foraging Optimization (MRFO) algorithm is introduced to deal with real parameter constrained optimization problem. …”
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    Conference or Workshop Item
  16. 16

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

    Published 2014
    “…FLC can automatically optimize HO parameters i.e. Handover Margin (HOM) and Time-ToTrigger (TTT) based on a set of criteria, this is in order to minimize unwanted HOs known as HO Ping Pong (HOPP) and HO failure (HOF). …”
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  17. 17

    Chiller energy prediction in commercial building : A metaheuristic-enhanced deep learning approach by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
    “…Drawing on a diverse dataset from a commercial building, encompassing vital input parameters such as Chilled Water Rate, Building Load, Cooling Water Temperature, Humidity, and Dew Point, the study conducts a comprehensive comparison of metaheuristic algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Barnacles Mating Optimizer (BMO), Harmony Search Algorithm (HSA), Differential Evolution (DE), Ant Colony Optimization (ACO), and the latest RIME algorithm). …”
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    Article
  18. 18

    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
  19. 19

    Evolutionary algorithm for forecastng mean sea level based on meta-heuristic approach by Lai V., Ahmed A.N., Malek M.A., El-Shafie A., El-Shafie A.

    Published 2023
    “…GP is a meta-heuristic search and optimization technique based on natural evolution. …”
    Article
  20. 20

    Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems by Salman, Mustafa Ismael

    Published 2015
    “…Specifically, the downlink frequency domain scheduler will reconfigure the criteria priorities such that the EE is maximized as long as the QoS is guaranteed.On the other hand, the partial feedback algorithm will search for the threshold value that minimizes the uplink overhead given that the QoS is achieved at the downlink.Otherwise, optimizing QoS parameters will be targeted at the cost of other system parameters. …”
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