Search Results - (( using scale data algorithm ) OR ( using optimization based algorithm ))

Refine Results
  1. 1

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…So far, various voting methods are proposed which are mostly proper for small-scale systems. In this research, we proposed optimal algorithms using Divide and Conquer, Brent’s theorem and parallel algorithms, appropriate for today’s large scale systems such as satellite processing systems, traffic control, weather forecasting which all face a large quantity of processing input data. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Algorithm development for optimization of a refrigeration system by Izzat, Mohamad Adnan

    Published 2010
    “…The thesis describes the step by step the method to find an algorithm by using experimental data. Vapor compression refrigeration system was studied as it is the most widely used refrigeration system especially in small scale of refrigeration application such as in domestic application. …”
    Get full text
    Get full text
    Undergraduates Project Papers
  4. 4
  5. 5

    Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution by Tijani, Ismaila B., Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus

    Published 2014
    “…This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data.The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. …”
    Get full text
    Get full text
    Get full text
    Article
  6. 6
  7. 7
  8. 8

    Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting by Ali, Noor Rasidah, Ku Mahamud, Ku Ruhana

    Published 2017
    “…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper by Qadori, Huthiafa Q., Ahmad Zukarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

    Published 2017
    “…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
    Get full text
    Get full text
    Get full text
    Article
  10. 10
  11. 11

    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
    “…The proposed approach utilizes genetic algorithms to dynamically produce optimized timetables based on individual student needs, with real-time data scraping from 'iCRESS' ensuring the system stays up to date with the latest course information for accurate timetable generation. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…This strategy includes a number of components that are a novel approach to clustering generation. In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

    Published 2011
    “…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
    Get full text
    Get full text
    Thesis
  14. 14
  15. 15

    Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

    Published 2018
    “…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. This is to remedy the problem of using the existing Min-Max (MM) and Decimal Scaling (DS) techniques, which have overflow weakness. …”
    Get full text
    Get full text
    Get full text
    Thesis
  16. 16
  17. 17

    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…In general, genetic based clustering algorithms showed the ability to reach near global optimal solution. …”
    Get full text
    Get full text
    Thesis
  18. 18
  19. 19

    Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids by Abduh Kaid, Monir Abdullah

    Published 2009
    “…This property has been successfully employed using Divisible Load Theory (DLT) , which has been proven to be a powerful tool for modeling divisible load problems in large scale data grid. …”
    Get full text
    Get full text
    Thesis
  20. 20

    DTWFF-pitch feature and faster neural network convergence for speech recognition by Sudirman, Rubita, Salleh, Sh. Hussain, Salleh, Shaharuddin

    Published 2007
    “…The processed features are pitch and Linear Predictive Coefficients (LPC) for input and reference templates, based on Dynamic Time Warping (DTW) algorithm. The first task is to extract pitch features using Pitch Scale Harmonic Filter algorithm. …”
    Get full text
    Get full text
    Get full text
    Article