Search Results - intelligence based ((using algorithm) OR (((matching algorithm) OR (bees algorithm))))

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  1. 1

    Application of Bee Colony Optimization (BCO) in NP-Hard Problems by Kamarudin, Muhammad Sariy Syazwan

    Published 2011
    “…This report presents the first stage of an ongoing research which is the problem solving of highly complex tasks using Bee-Inspired algorithms. Bee-Inspired algorithms are partially referring to the nature of bee swarm behaviour. …”
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    Final Year Project
  2. 2

    Optimal design of step – cone pulley problem using the bees algorithm by Yusof, Noor Jazilah, Kamaruddin, Shafie

    Published 2021
    “…The Bees Algorithm is used in this study to find the optimum solution for stepped-cone pulley design and found better results compared to other optimization algorithms.…”
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    Book Chapter
  3. 3

    Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

    Published 2023
    “…Currently available framework documentation approaches are not very effective for new framework users, and this scenario tends to discourage new users in using frameworks. The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
    Conference paper
  4. 4

    A Novel Map-matching Algorithm to Improve Vehicle Tracking System Accuracy by Dewandaru, Agung, Md Said, Abas, Matori, A. N.

    Published 2008
    “…Satellite-based Vehicle Tracking System accuracy can be improved by augmenting the positional information using road network data, in a process known as map-matching. …”
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    Article
  5. 5

    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…The review is based on how the algorithms deal with objective functions using MOO approaches, the benchmark MOPs used in the evaluation and performance metrics. …”
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    Article
  6. 6

    A quick gbest guided artificial bee colony algorithm for stock market prices prediction by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…In this respect, in the present manuscript, we propose an algorithm based on ABC to minimize the error in the trend and actual values by using the hybrid technique based on neural network and artificial intelligence. …”
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    Article
  7. 7

    Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

    Published 2017
    “…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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    Article
  8. 8

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…Due to the center biased nature of the videos, the HPSO algorithm uses an initial pattern (hexagon-shaped) to speed up the convergence of the algorithm. …”
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    Thesis
  9. 9

    A novel map-matching algorithm to improve vehicle tracking system accuracy by A.M., Said, A.N., Matori, A., Dewandaru

    Published 2007
    “…The satellite-based Vehicle Tracking System accuracy can be improved by augmenting the positional information using road network data, in a process known as map-matching. …”
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    Conference or Workshop Item
  10. 10

    A Map-matching Algorithm to Improve Vehicle Tracking Systems Accuracy by Dewandaru, Agung

    Published 2008
    “…The results showed that the proposed algorithm is able to improve the map-matching accuracy as compared to the point-to-curve algorithm. …”
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    Thesis
  11. 11

    Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain by Mohamad Zihin , Mohd Zain

    Published 2018
    “…BSA gave the best overall performance by showing improved solutions and more robust convergence in comparison with various metaheuristics used in this work. Multi-objective optimization problems are also addressed by proposing a modified multi-criterion optimization algorithm based on a Pareto-based Particle Swarm Optimization (PSO) algorithm called Multi-Objective Particle Swarm Optimization (MOPSO). …”
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    Thesis
  12. 12

    CAR LICENSE PLATE RECOGNITION BY USING TEMPLATE MATCHING ALGORITHM by Fariza, Mahyan, Termimi Hidayat, Mahyan, Asrani, Lit

    Published 2015
    “…Car License Plate Recognition (CLPR) system is one of the important areas in the intelligent traffic engineering field. CLPR is developed to recognize the car license plate with the implementation of Digital Image Processing (DIP) and Template Matching Algorithm (TMA) approaches by using the MATLAB software. …”
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    Proceeding
  13. 13

    A Map-matching Algorithm to Improve Vehicle Tracking Systems Accuracy by Agung Dewandaru, Agung

    Published 2008
    “…The results showed that the proposed algoritlimi is able to improve the neap-matching accuracy as compared to the point-to-curve algorithm. …”
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    Final Year Project
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  18. 18

    Car License Plate Recognition by Using Template Matching Algorithm by Arina, Yusuf, Asrani, Lit, Annisa, Jamali

    Published 2014
    “…CLPR is developed to recognise the car license plate with the implementation of Digital Image Processing (DIP) and Template Matching Algorithm (TMA) approach by using the MATLAB software. …”
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    Book
  19. 19

    Performance evaluation of automatic number plate recognition on android smartphone platform by Gunawan, Teddy Surya, Mutholib, Abdul, Kartiwi, Mira

    Published 2017
    “…On the other hand, the traditional algorithm using template matching only obtained 83.7% recognition rate with 0.98 second processing time. …”
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    Article
  20. 20

    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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    Book