Search Results - (( developing agent optimisation algorithm ) OR ( java implementation phase algorithm ))

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  1. 1

    Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

    Published 2019
    “…This study aims to explore the potential of implementing multi-agent-based Genetic Algorithm (GA) with interactive metamodel to acquire regular optimisation on dynamic characteristic of traffic flow. …”
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    Thesis
  2. 2

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…All the algorithm for the engine has been developed by using Java script language. …”
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  3. 3

    Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman by Che Othman, Muhammad Nazree

    Published 2013
    “…This research presents an approach to solve the UC problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority Listing optimisation technique (MAEP-PL). …”
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  4. 4

    Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List by Othman M.N.C., Rahman T.K.A., Mokhlis H., Aman M.M.

    Published 2023
    “…This paper presents an approach to solve the unit commitment problem using a newly developed Multi-agent Evolutionary Programming incorporating Priority List optimisation technique (MAEP-PL). …”
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    Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System by Abidin, Zulkifli Zainal

    Published 2013
    “…In this thesis, a simple framework and methodology in developing a bio-inspired algorithm for cooperative swarming robotic application has been developed. …”
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  7. 7

    Optimisation and control of fed-batch yeast production using q-learning by Helen, Chuo Sin Ee

    Published 2013
    “…To cater for the process disturbance, Q-learning with exploration (QLE) has been included in this work for online optimisation. QLE signifies the importance of exploration from time to time based on the developed “past experience” in Q-table to optimise the process. …”
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  8. 8

    A performance of AFIRO among asynchronous iteration strategy metaheuristic algorithms by Ab Rahman, Tasiransurini, Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim

    Published 2023
    “…In the original paper, AFIRO was compared with the Particle Swarm Optimisation algorithm, Genetic Algorithm, and Grey Wolf Optimizer. …”
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  9. 9

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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