Search Results - (( intelligence based gps algorithm ) OR ( intelligence based ((bee algorithm) OR (_ algorithm)) ))

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  1. 1

    Developing Bus Tracking System that predicts the arrival times of public buses at Universiti Teknologi PETRONAS (UTP) bus stops. by Mohd Akhir, Norhasiah

    Published 2004
    “…This project is developed based on the advancement of Information Technology (IT) system today that has enabled people to have an intelligent transport system which assists them in traveling. …”
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    Final Year Project
  2. 2

    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
  3. 3

    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
  4. 4

    Distance vector-hop range-free location algorithm for wireless sensor network by Zazali, Azyyati Adiah

    Published 2015
    “…Thus, this research has proposed two ideas. First is the intelligent nodes placement algorithm for sensor nodes in order to introduce algorithm with low complexity and low localization error. …”
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    Thesis
  5. 5

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

    Published 2008
    “…A simulator is developed as a test bed for the proposed algorithm for various scenarios, including the field experiment using Garmin e-Trex GPS Receiver. …”
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    Final Year Project
  6. 6

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

    Published 2008
    “…A simulator is developed as a test bed for the proposed algorithm for various scenarios, including the field experiment using Garmin e-Trex GPS Receiver. …”
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    Thesis
  7. 7
  8. 8

    A Novel Artificial Intelligence Based Timing Synchronization Scheme for Smart Grid Applications by Mohammad Kamrul, Hasan, Musse Mohamud, Ahmed, Aisha, Hassan Abdalla Hashim, Abdur Razzaque, Shayla Islam, Biswajeet, Pandey

    Published 2020
    “…Therefore, to reduce this clock offsets, a new algorithm is needed which may consider any alternative reference timestamps rather than GPS. …”
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    Article
  9. 9
  10. 10

    An Efficient Route Selection Based on AODV Algorithm for VANET by Nassir Sallom , Kadhim, Mohammed, Muamer N., Mazlina, Abdul Majid, Sinan Q., Mohamd

    Published 2016
    “…Simulation result shown that VANET modified algorithm based on average signal strength has the advantage of choosing the optimum route to deliver data and own enhanced ratio (17%) by comparing with a maximum signal strength route.…”
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    Conference or Workshop Item
  11. 11
  12. 12

    An Efficient Route Selection based on AODV Algorithm for VANET by Kadhim, Nassir, Mohammed, Muamer N., Mazlina, Abdul Majid, Mohamd, Sinan Q., Tao, Hai

    Published 2016
    “…Simulation tested two of distance ranges among nodes (Long & Short) and the result shown that VANET modified algorithm based on average signal strength has the advantage of choosing the optimum route to deliver data and own enhanced ratio according to the distances (17.5% & 24.1%) by comparing with a maximum signal strength route.…”
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    Article
  13. 13
  14. 14

    Design of real time intelligent buses notification system for passengers by Muhammad, Rauf

    Published 2012
    “…In this dissertation, a new real time intelligent public transport movement monitoring system and station reporting based on GPS and succession of RF Radio Chips is presented. …”
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    Thesis
  15. 15

    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
  16. 16

    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
  17. 17

    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
  18. 18

    Fuzzy logic-based arrival time estimation for indoor navigation using augmented reality by Mohammed Sohif, Muhammad Hidayat, Mardzuki, Muhammad Imran, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

    Published 2025
    “…This study proposes a mobile AR application for indoor navigation that uses an intelligent signage algorithm based on fuzzy logic to estimate arrival time. …”
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    Article
  19. 19

    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
  20. 20

    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