Search Results - (( parameter classification using algorithm ) OR ( basic navigation using algorithm ))

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  1. 1

    Implementation of an autonomous mobile robot navigation algorithm using C language by Subra Mullisi, Shafeq Marwan

    Published 2009
    “…This report basically discusses the study and also work that has been done from previous of the chosen topic, which is Implementation of an Autonomous Mobile Robot Navigation Algorithm using 'C' language. …”
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    Final Year Project
  2. 2

    Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

    Published 2006
    “…Algorithms are developed for a simulated mobile robot that uses an array of range finders for navigation. …”
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    Monograph
  3. 3

    MAZE ROBOT: APPLYING AUTONOMOUS VEHICLE NAVIGATION ALGORITHM WITH EVENT-DRIVEN PROGRAMMING by ABDUL MALEK, NADHIRA

    Published 2011
    “…Hardware and software co-design method is used to construct the mobile robot. The basic navigation algorithm was developed using finite state machine (FSM). …”
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    Final Year Project
  4. 4

    Mobile robot navigation using GPS to solve target location achieving problem / Saiful Zaimy Yahaya, Rozan Boudville and Mohamad Faizal Abdul Rahman by Yahaya, Saiful Zaimy, Boudville, Rozan, Abdul Rahman, Mohamad Faizal

    Published 2010
    “…This research proposed mobile robot navigation using GPS to cope for the navigation problem in reaching the target location. …”
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    Research Reports
  5. 5

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

    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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    Thesis
  6. 6
  7. 7

    Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    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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    Article
  8. 8
  9. 9

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

    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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    Article
  10. 10

    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    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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    Thesis
  11. 11

    Design and development of autonomous omni-directional mobile robot with mecanum wheel by Jefri Effendi Mohd Salih

    Published 2008
    “…Motor driver and robot controller were also developed. Motion control algorithm using BasicStamp Editor software was developed to test the capabilities of the system’s mobility performance. …”
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    Thesis
  12. 12

    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.…”
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    Conference or Workshop Item
  13. 13

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    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
  14. 14
  15. 15

    Mobile Robot with Navigation Control and Communication by Mohammad Yatim, Amirah Izzati

    Published 2016
    “…Mobile Robot with Navigation Control and Communication is basically about a mobile robot where a list of instructions is needed to control the locomotion of the robot. …”
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    Final Year Project
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    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    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
  18. 18

    Classification of tropical rainforest using different classification algorithm based on remote sensing imagery: A study of Gunung Basor by Intan Noradybah Md Rodi

    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
  19. 19

    Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters by Teguh, Sutanto, Muhammad Rafli, Aditya, Haldi, Budiman, M.Rezqy, Noor Ridha, Usman, Syapotro, Noor, Azijah

    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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    Article
  20. 20

    An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani by Ab Ghani, Nur Laila

    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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    Thesis