Search Results - (( using estimation path algorithm ) OR ( parameter classifications using algorithm ))
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1
A Continuous Overlay Path Probing Algorithm For Overlay Networks
Published 2013“…Active measurement techniques performed by overlay nodes can provide bandwidth estimations of an end-to-end overlay path. This thesis describes a new algorithm called “COPPA,” which is an in-band path probing algorithm for measuring the end-to-end available bandwidth of an overlay path accurately and continuously. …”
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2
Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…However, this assumption may lead to inaccurate secondary path model. In this work, the modelling of acoustic path using FIR filters is incorporated for both algorithms for Wiener-Hammerstein structure. …”
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3
Analysis of Dijkstra’s and A* algorithm to find the shortest path
Published 2015“…There are so many algorithms used to find the shortest path such as Dijkstra, A* algorithm, Genetic algorithm, Floyd algorithm and Ant algorithm. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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6
Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…The warppartial least square method was utilized to estimate the multi-layer hypothesized path model. This model estimated warped coefficients using the overall linear trend found in linear segments of non-linear relationships. …”
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7
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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8
Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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10
Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja
Published 2004“…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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11
Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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12
Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity
Published 2014“…The proposed THF-NLFXLMS algorithm models the Wiener secondary path and applies the estimated degree of nonlinearity of the nonlinear secondary path in the control algorithm design. …”
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13
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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Conference or Workshop Item -
14
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. The value of parameter is already set to use when applying every dataset in an experiment. …”
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Undergraduates Project Papers -
15
GPS boundary navigation of DrosoBots using MATLAB simulation
Published 2010“…To implement this, region recognition and several path planning algorithms have been utilized. Besides that, pixilation of path is also used to estimate the coverage of the path planning. …”
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Proceeding Paper -
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…IPJAYA in this study was used to update the C and gamma parameters of the support vector machine (SVM). …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
Conference Paper -
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Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor
Published 2019“…Thehighest accuracy for classification map of Gunung Basor is by using maximum likelihood algorithm with an accuracy of 82.90%. …”
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Undergraduate Final Project Report -
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This study compares four machine learning algorithms Logistic Regression, Random Forest, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) in water quality classification based on contaminant parameters. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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