Search Results - (( intelligence based bees algorithm ) OR ( intelligence system matching algorithm ))*

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  1. 1

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

    Published 2011
    “…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
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    Final Year Project
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    Optimal design of step – cone pulley problem using the bees algorithm by Yusof, Noor Jazilah, Kamaruddin, Shafie

    Published 2021
    “…Most of these algorithms were developed based on the collective behavior of social swarms of ants, bees, a flock of birds, and schools of fish. …”
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    Book Chapter
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    A Novel Map-matching Algorithm to Improve Vehicle Tracking System Accuracy by Dewandaru, Agung, Md Said, Abas, Matori, A. N.

    Published 2008
    “…The curve-to-curve matching algorithms measure the similarity between the track and possible road path. …”
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    Article
  5. 5

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

    Published 2007
    “…Map-matching algorithms attempt to pinpoint the vehicle in a particular road map segment (or any restricting track such as rails, etc), in spite of the digital map errors and navigation system inaccuracies. …”
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    Conference or Workshop Item
  6. 6

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

    Published 2023
    “…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
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    Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

    Published 2011
    “…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
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    Conference or Workshop Item
  8. 8

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

    Published 2008
    “…Keywords: map-matching, vehicle tracking systems, Multiple Hypotheses Technique, Global Positioning System.…”
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    Thesis
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    A Map-matching Algorithm to Improve Vehicle Tracking Systems Accuracy by Agung Dewandaru, Agung

    Published 2008
    “…Keywords: map-matching, vehicle tracking systems, Multiple Hypotheses Technique, Global Positioning System.…”
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    Final Year Project
  11. 11

    Performance Enhancement Of Artificial Bee Colony Optimization Algorithm by Abro, Abdul Ghani

    Published 2013
    “…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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    Thesis
  12. 12

    Artificial bee colony for inventory routing problem with backordering by Moin, N.H., Halim, H.Z.A.

    Published 2014
    “…We propose a metaheuristic method, Artificial Bee Colony (ABC) to solve the IRPB.The ABCalgorithm is a swarm based heuristics which simulates the intelligent foraging behaviour of a honey bee swarm and sharing that information of the food sources with the bees in the nest. …”
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    Conference or Workshop Item
  13. 13

    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
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    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. …”
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    Proceeding
  16. 16

    Assignation of PSM evaluator using genetic algorithm by Yap, Suet Lee

    Published 2012
    “…The purpose of this paper is to present a design of development for Assignation of PSM Evaluator using Genetic Algorithm(APEGA)system.This is an application system that is used to assist the Faculty of Computer System and Software Engineering(FSKKP)of University Malaysia Pahang(UMP)in matching the optimum evaluators for the students in PSM presentation carnival.In the methodology part,a development model which involves with client participation is designed in order to use in the development of this project.The target user of the system is PSM coordinator who is responsible in assigning the PSM evaluator.Assignation of PSM Evaluator using Genetic Algorithm APEGA)is expected to be able in developing a well-distributed matching and overcoming the relevant constraints in an intelligent way. …”
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    Undergraduates Project Papers
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    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
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    Review of Multi-Objective Swarm Intelligence Optimization Algorithms by Yasear, Shaymah Akram, Ku Mahamud, Ku Ruhana

    Published 2021
    “…The MOSI algorithms are based on the integration of single objective algorithms and multi-objective optimization (MOO) approach. …”
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    Article
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