Search Results - (( java implementation learning algorithm ) OR ( using vector time algorithm ))

Refine Results
  1. 1

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
    Get full text
    Get full text
    Get full text
    Thesis
  2. 2

    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Both of these algorithms are designed using 16 × 16 block size. In particular, the motion vector estimation, quality performance, computational complexity, and elapsed processing time are emphasised. …”
    Get full text
    Get full text
    Get full text
    Book Chapter
  3. 3

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  4. 4

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    A Test Vector Minimization Algorithm Based On Delta Debugging For Post-Silicon Validation Of Pcie Rootport by Toh , Yi Feng

    Published 2017
    “…Test results using test vector sets containing deliberately introduced erroneous test vectors show that the minimizer is able to isolate the erroneous test vectors. …”
    Get full text
    Get full text
    Thesis
  6. 6

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
    Get full text
    Get full text
    Get full text
    Thesis
  7. 7

    Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  8. 8

    Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak by Abdul Razak, Noorfadzli

    Published 2018
    “…The second stage focuses on using the vector to generate an admissible cubic path via Hermite interpolation technique integrated with time and tangent transformation scheme. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Lightning Fault Classification for Transmission Line Using Support Vector Machine by Asman S.H., Aziz N.F.A., Kadir M.Z.A.A., Amirulddin U.A.U., Roslan N., Elsanabary A.

    Published 2024
    “…In this study, two machine learning algorithms, Support Vector Machine (SVM) and k-Nearest Neighbor (kNN), were used and compared to classify faults due to lightning strikes, insulator failure, tree and crane encroachment. …”
    Conference Paper
  10. 10

    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

    Published 2021
    “…The training phase of the machine learning algorithm used proposed real-time training datasets benchmarked with two training datasets from CICIDS and NSL-KDD. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Smoothed functional algorithm with norm-limited update vector for identification of continuous-time fractional-order Hammerstein Models by Mok, Ren Hao, Mohd Ashraf, Ahmad

    Published 2024
    “…This article proposes an identification method of continuous-time fractional-order Hammerstein model using smoothed functional algorithm with a norm-limited update vector (NL-SFA). …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12
  13. 13

    Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

    Published 2024
    “…The study also introduces a novel optimization algorithm for selecting inputs. While the LSSVM model may not capture nonlinear components of the time series data, the extreme learning machine (ELM) model�MKLSSVM model can capture nonlinear and linear components of the time series data. …”
    Article
  14. 14

    Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous in nature, the values wil have to be discretized.The discretization process will result in loss of some information and, hence, affects the classification accuracy and seeks time.This paper presents an algorithm to optimize Support Vector Machine parameters using Incremental continuous Ant Colony Optimization without the need to discretize continuous values.Eight datasets from UCI were used to evaluate the performance of the proposed algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.Experimental results of the proposed algorithm also show promising performance in terms of classification accuracy and size of features subset.…”
    Get full text
    Get full text
    Get full text
    Article
  15. 15

    Dual vector control strategy for a three-stage hybrid cascaded multilevel inverter by Kadir, M.N.A., Mekhilef, Saad, Ping, H.W.

    Published 2010
    “…This paper presents a voltage control algorithm for a hybrid multilevel inverter based on a staged-perception of the inverter voltage vector diagram. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia by Lim, San Yee

    Published 2018
    “…The similarities between two or more multi-dimensional of stocks are quantified by using Random Vector (RV) coefficient. Based on the preliminary analysis, the computational of RV coefficient is difficult, time-consuming, and tedious when a large number of stocks are involved. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  17. 17

    Five phase space vector modulation voltage source inverter using large vector only / Mohd Syazimie Zulkifli by Zulkifli, Mohd Syazimie

    Published 2012
    “…Furthermore, this study does not include the zero vectors at the time switching and only active vector were used for the time switching for each sector. …”
    Get full text
    Get full text
    Thesis
  18. 18
  19. 19

    MATLAB/SIMULINK based analysis of voltage source inverter with space vector modulation by Jidin , Auzani

    Published 2009
    “…The modulation strategy uses switching time calculator to calculate the timing of voltage vector applied to the three-phase balanced-load. …”
    Get full text
    Get full text
    Article
  20. 20

    An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting by Maijama'a, Inusa Sani

    Published 2023
    “…Combining the enhanced algorithms results in SVR-eABO, whose forecasting ability has been assessed using MAE, MAPE, RMSE, PA and R2. …”
    Get full text
    Get full text
    Get full text
    Thesis