Search Results - (( parameter evaluation max algorithm ) OR ( parameter evaluation means algorithm ))

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  1. 1

    Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

    Published 2015
    “…Accordingly, different operation policies were constructed and evaluated in this research. Generally, this research is divided into two main stages. …”
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    Thesis
  2. 2

    Quality of service management algorithms in WiMAX networks by Saidu, Ibrahim

    Published 2015
    “…Simulation have been extensively used to evaluate the proposed algorithm. Finally, Discrete Event Simulator (DES) is designed and developed in order to evaluate the performance of the proposed algorithms. …”
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    Thesis
  3. 3

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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    Thesis
  4. 4

    Analysis of WiMAX Positioning Using Received- Signal-Strength Method by Awang Md Isa, Azmi, Mohamad Isa, Mohd Sa'ari, Mohd Zin, Mohd Shahril Izuan, Haron, Nor Zaidi, Ja'afar, Abd Shukur

    Published 2013
    “…By the performance evaluation, the user can plan better simulation system and can create more accurate algorithms for radio positioning.…”
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    Article
  5. 5

    Simulation model to improve QoS performance over fixed WiMAX using OPNET by Lawal, I.A., Md Said, A., Mu'azu, A.A.

    Published 2013
    “…The design has been evaluated using the simulation tool OPNET modeler 16.0. …”
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    Article
  6. 6

    A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

    Published 2020
    “…Five evaluation metrics were utilized; mean average percent error (MAPE), accuracy, symmetric mean absolute percent error (SMAPE), root mean square percent error (RMSPE) and fitness value. …”
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    Article
  7. 7

    Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

    Published 2022
    “…The quantum calculus provides an extra degree of freedom to search the local and global minima by inducing a q-parameter. Motivated by this fact, a quantum calculus-based noisy links incremental least mean squares (NL-qILMS) algorithm is proposed. …”
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    Article
  8. 8

    Reactive approach for automating exploration and exploitation in ant colony optimization by Allwawi, Rafid Sagban Abbood

    Published 2016
    “…The first component is a reactive max-min ant system algorithm for recording the neighborhood structures. …”
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    Thesis
  9. 9

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…Specifically, the PSO algorithm achieved a mean surface roughness improvement of 0.44% over GA, and 1.1% and 1.23% over ACO and FA, respectively. …”
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    Article
  10. 10

    An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

    Published 2022
    “…The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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    Book Chapter
  11. 11

    Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

    Published 2023
    “…The evaluation process was implemented on RK-Means, K-Means++, and OK-Means models. …”
    Article
  12. 12

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…In other words, in order to get a good result, the BPNN learning algorithm needs to be executed several times with different topology structures and parameter values in order to determine the best set of parameter values used in the BPNN. …”
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    Thesis
  17. 17

    Stock price predictive analysis: An application of hybrid barnacles mating optimizer with artificial neural network by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

    Published 2023
    “…The proposed hybrid predictive model of BMO-ANN is tested on time series data of stock price using six selected inputs to predict the next day’ closing prices. Evaluated based on Mean Square Error (MSE) and Root Mean Square Error (RMSPE), the proposed BMO-ANN exhibits significant superiority over the other identified hybrid algorithms. …”
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    Article
  18. 18

    Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

    Published 2025
    “…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
    Article
  19. 19

    Bouc-Wen hysteresis parameter optimization for magnetorheological damper using Cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed, G., Priyandoko, M. F. F., Ab Rashid

    Published 2020
    “…This paper proposed an optimized Phenomenological Bouc-Wen model for MR damper. Cuckoo search algorithm is used to optimize the parameters in phenomenological Bouc-Wen model. …”
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    Conference or Workshop Item
  20. 20

    Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar, A., Kanthasamy, R., Sait, H.H., Zwawi, M., Algarni, M., Ayodele, B.V., Cheng, C.K., Wei, L.J.

    Published 2022
    “…The performances of the algorithms were evaluated using the coefficient of determination (R2), root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE). …”
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    Article