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1
Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
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. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
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. …”
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3
An Educational Tool Aimed at Learning Metaheuristics
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. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / 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. …”
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5
A Test Vector Minimization Algorithm Based On Delta Debugging For Post-Silicon Validation Of Pcie Rootport
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. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
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. …”
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7
Optimizing support vector machine parameters using continuous ant colony optimization
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.…”
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8
Real-Time Optimal Trajectory Correction (ROTC) for autonomous quadrotor / Noorfadzli Abdul Razak
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. …”
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9
Lightning Fault Classification for Transmission Line Using Support Vector Machine
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 -
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Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm
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. …”
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Smoothed functional algorithm with norm-limited update vector for identification of continuous-time fractional-order Hammerstein Models
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). …”
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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...
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. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
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.…”
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Dual vector control strategy for a three-stage hybrid cascaded multilevel inverter
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. …”
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A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia
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. …”
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Five phase space vector modulation voltage source inverter using large vector only / Mohd Syazimie Zulkifli
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. …”
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18
A parallel version of a binary method and vector addition chains precomputation for exponentiation in RSA / Siti Khatijah Nor Abdul Rahim and Siti Rozanae Ismail
Published 2006“…Exponentiation can be time consuming; however it depends on the algorithms and the implementation used. …”
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Research Reports -
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MATLAB/SIMULINK based analysis of voltage source inverter with space vector modulation
Published 2009“…The modulation strategy uses switching time calculator to calculate the timing of voltage vector applied to the three-phase balanced-load. …”
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An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting
Published 2023“…Combining the enhanced algorithms results in SVR-eABO, whose forecasting ability has been assessed using MAE, MAPE, RMSE, PA and R2. …”
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