Search Results - (( data classification approach algorithm ) OR ( using function path algorithm ))

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  1. 1
    A-star (A*) algorithm implementation for robotics path planning navigation

    A-star (A*) algorithm implementation for robotics path planning navigation by Emirul Ridzwan, Nor Azmi

    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
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  2. 2
    Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah

    Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah by Hanafiah, Sukri

    Published 1997
    “…The euler's path it using pseudo input and Heuristic algorithm to find the minimum interlace. …”
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    Thesis
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  3. 3
    Case Slicing Technique for Feature Selection

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Since the 1960s, many algorithms for data classification have been proposed. …”
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    Thesis
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  4. 4
    Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm

    Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm by Krishnan P.S., Paw J.K.S., Kiong T.S.

    Published 2023
    Conference Paper
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  5. 5
    Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group

    Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group by Azali Saudi, Jumat Sulaiman

    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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  6. 6
    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH

    DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

    Published 2005
    “…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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    Final Year Project
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  7. 7
    Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach

    Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach by Munnian, Ruthrakumar

    Published 2019
    “…Therefore, this study attempts a data mining approach to the analysis of failure in offline English alphabet recognition. …”
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    Monograph
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  8. 8
    False path identification algorithm framework for nonseparable controller-data path circuits

    False path identification algorithm framework for nonseparable controller-data path circuits by Shaheen, Ateeq U. R., Hussin, Fawnizu Azmadi, Hamid, Nor Hisham

    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
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  9. 9
    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    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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  10. 10
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…For the problem of missing data, a new approach was proposed based on data partitioning and function mode. …”
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  11. 11
    False path identification algorithm framework for nonseparable controller-data path circuits

    False path identification algorithm framework for nonseparable controller-data path circuits by Shaheen, A.-U.-R., Hussin, F.A., Hamid, N.H.

    Published 2017
    “…This paper proposes an algorithm framework to deal with these false paths through identification for DFT test. …”
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  12. 12
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…According to the experimental findings, the suggested EB has a major effect on the accuracy, recall, and F-measure of data classification. The classification performance using EB outperforms other existing approaches for all datasets.…”
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  13. 13
    An improve unsupervised discretization using optimization algorithms for classification problems

    An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

    Published 2024
    “…According to the experimental findings, the suggested EB has a major effect on the accuracy, recall, and F-measure of data classification. The classification performance using EB outperforms other existing approaches for all datasets.…”
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  14. 14
    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment

    The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment by Kok, Kai Yit

    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. 15
    Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media

    Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

    Published 2024
    “…The Multi-Class Multi-Level (MCML) classification algorithm was applied to perform detailed classification and address the limitations of the research scope using several approaches, including machine learning, deep learning, and transfer learning approaches. …”
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  16. 16
    Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries

    Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries by Fadzli, S.A., Abdulkadir, S.I., Makhtar, M., Jamal, A.A.

    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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  17. 17
    Indoor path planning using harmonic functions via half-sweep arithmetic mean method

    Indoor path planning using harmonic functions via half-sweep arithmetic mean method by Azali Saudi, Jumat Sulaiman

    Published 2019
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  18. 18
    Trademark image classification approaches using neural network and rough set theory

    Trademark image classification approaches using neural network and rough set theory by Saad, Puteh

    Published 2003
    “…The approaches contain five major stages, namely: image acquisition, image preprocessing, feature extraction, data transformation and classification. …”
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  19. 19
    Mutable composite firefly algorithm for gene selection in microarray based cancer classification

    Mutable composite firefly algorithm for gene selection in microarray based cancer classification by Fajila, Mohamed Nisper Fathima

    Published 2022
    “…However, the existing hybrid approaches with metaheuristic optimization algorithms in feature selection (specifically in gene selection) are not generalized enough to efficiently classify most cancer microarray data while maintaining a small set of genes. …”
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  20. 20
    A derivative-free optimization method for solving classification problem

    A derivative-free optimization method for solving classification problem by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June

    Published 2010
    “…Approach: The problem of data classification was studied as a problem of global, nonsmooth and nonconvex optimization; this approach consists of describing clusters for the given training sets. …”
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