Search Results - (( using function path algorithm ) OR ( variables classification problem algorithm ))
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1
Classification for large number of variables with two imbalanced groups
Published 2020“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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Thesis -
2
Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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3
A-star (A*) algorithm implementation for robotics path planning navigation
Published 2018“…This thesis is about the implementation of Astar (A*) algorithm as path planning algorithm used in robotics navigation. …”
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Undergraduates Project Papers -
4
Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah
Published 1997“…The euler's path it using pseudo input and Heuristic algorithm to find the minimum interlace. …”
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5
Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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6
Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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Thesis -
7
Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Conference Paper -
8
Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group
Published 2014“…Consequently, the gradient of the potential functions would be used by the searching algorithm to generate path from starting to goal location. …”
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Study on numerical solution of a variable order fractional differential equation based on symmetric algorithm
Published 2019“…A fully symmetric classification of the boundary value problem for a class of fractional differential equations with variable sequences is determined by using a fully symmetric differential sequence sorting algorithm. …”
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False path identification algorithm framework for nonseparable controller-data path circuits
Published 2016“…This paper proposes an algorithm frame-work to deal with these false paths through identification for DFT test. …”
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Conference or Workshop Item -
11
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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12
False path identification algorithm framework for nonseparable controller-data path circuits
Published 2017“…This paper proposes an algorithm framework to deal with these false paths through identification for DFT test. …”
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13
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…The focus of this thesis is on solvingclustering and classification problems. Specifically, we will focus on new optimization methods for solving clustering and classification problems. …”
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Thesis -
14
The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
Published 2016“…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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15
Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries
Published 2016“…The path computed using the classic Dijkstra's algorithm is the shortest; however, it may not be the most feasible. …”
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Conference or Workshop Item -
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter
Published 2017“…This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant colony and support vector machine.A new direction for ant colony optimisation is to optimise mixed (discrete and continuous) variables.The optimised variables are then feed into selecting feature subset and tuning its parameters are two main problems of SVM.Most approaches related to tuning support vector machine parameters will discretise the continuous value of the parameters which will give a negative effect on the performance. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…However, the original HHO is developed to solve the continuous optimization problems, but not to the problems with binary variables. …”
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19
A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…A statistical test was used to demonstrate the efficiency of the proposed algorithm over the compared methods. …”
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Thesis -
20
Wi-fi fingerprint database construction using Chebyshev wavelet functions
Published 2015“…Next, the collected reference samples are used to construct area specific path-loss prediction function using Chebyshev wavelets. …”
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