Search Results - (( initial optimization path algorithm ) OR ( using optimization svm algorithm ))

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  1. 1

    Multi-robot path planning based on the improved nutcracker optimization algorithm and the dynamic window approach by Zhao, Jiangrong, Ding, Hongwei, Zhu, Yuanjing, Yang, Zhijun, Hu, Peng, Wang, Zongshan

    Published 2024
    “…This paper proposes a multi-robot path planning algorithm that integrates the improved nutcracker optimization algorithm with the improved dynamic window approach. …”
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    Article
  2. 2

    Search algorithms for path planning problems in harsh wireless sensor network environment by Hong, Siaw Swin

    Published 2017
    “…Each algorithm solves its respective problem with Enhanced D* solving long initial delay in dynamic environment, NBN solves harsh conditions with limited computational power, and FWN optimized the result of TSP path planning problem with minimal computational effort. …”
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    Thesis
  3. 3

    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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    Article
  4. 4

    Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

    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
  5. 5

    Performance comparison between genetic algorithm and ant colony optimization algorithm for mobile robot path planning in global static environment / Nohaidda Sariff by Sariff, Nohaidda

    Published 2011
    “…The objective is to verify and compare the effectiveness of both algorithms in finding the optimal robot path in different types of global map environments. …”
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    Thesis
  6. 6

    Guidance system based on Dijkstra-ant colony algorithm with binary search tree for indoor parking system by Mohammad Ata, Karimeh Ibrahim, Che Soh, Azura, Ishak, Asnor Juraiza, Jaafar, Haslina

    Published 2021
    “…Dijkstra and ACO are integrated to produce the smart guidance algorithm for the indoor parking system. Dijkstra algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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    Article
  7. 7

    An Integrated RRT*SMART-A* Algorithm for solving the Global Path Planning Problem in a Static Environment by Suwoyo, Heru, Adriansyah, Andi, Andika, Julpri, Ubaidillah, Abu

    Published 2023
    “…Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  8. 8

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSYAH, ANDI, ANDIKA, JULFRI, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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  9. 9

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by Suwayo, Heri, Adrishah, Andi, Andika, Juleri, Shamdudin, Abu Ubaidah, Zakaria, Mohamad Fauzi

    Published 2023
    “…Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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    Article
  10. 10

    AN INTEGRATED RRT*SMART-A* ALGORITHM FOR SOLVING THE GLOBAL PATH PLANNING PROBLEM IN A STATIC ENVIRONMENT by SUWOYO, HERU, ADRIANSHAH, ANDI, ANDIKA, JULPRI, SHAMSUDIN, ABU UBAIDAH, ZAKARIA, MOHAMAD FAUZI

    Published 2023
    “…Unlike RRT*, RRT*-Smart applies a path optimization by removing the redundant nodes from the initial path when it is gained. …”
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    Article
  11. 11

    Design and development of optimal path trace back using graph theory technique for accelerate DNA sequence alignment accelerator: article by Othman, Nor Shuhaida

    Published 2010
    “…The Smith-Waterman is been simplified into four modules which were initialization, score calculation, matrix filling and optimal path. …”
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    Article
  12. 12

    Path planning algorithm for a car like robot based on MILP method by Mohd Sadri, Mohd Pawzi

    Published 2013
    “…This project is presents an algorithm for path planning optimal routes mobile robot “like a car” to a target in unknown environment. …”
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    Thesis
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    Solving SVM model selection problem using ACOR and IACOR by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Ant Colony Optimization (ACO) has been used to solve Support Vector Machine (SVM) model selection problem.ACO originally deals with discrete optimization problem. …”
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    Article
  17. 17

    Design and development of optimal path trace back using graph theory technique for accelerate DNA sequence alignment accelerator by Othman, Nor Shuhaida

    Published 2010
    “…The Smith-Waterman is been simplified into four modules which were initialization, score calculation, matrix filling and optimal path. …”
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    Student Project
  18. 18

    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    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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    Article
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