Search Results - (( evolution deviation selection algorithm ) OR ( java implementation matching algorithm ))

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  1. 1

    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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  2. 2

    Multi-floor indoor location estimation system based on wireless local area network by Chua, Tien Han

    Published 2007
    “…During location estimation, current histogram of RSS at unknown location will be compared to the database. The most probable match is selected and returned as estimated location based on Bayesian filtering algorithm. …”
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    Thesis
  3. 3

    Omega grey wolf optimizer (ωGWO) for optimization of overcurrent relays coordination with distributed generation by Noor Zaihan, Jamal

    Published 2019
    “…In Moreover, the robustness of GWO algorithm is establish with low standard deviation of 1.7142 seconds as compared to BBO. …”
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  4. 4

    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

    Published 2013
    “…The new proposed hybrid GA is able to produce 10 better or comparable solutions when compared to similar GA algorithms that employ two-parent crossover. In general this algorithm produces less than 6% deviation when compared to the best known solutions, especially in larger problems consisting of 20 jobs and 15 machines.…”
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  5. 5

    An Agent-Based System with Personalization and Intelligent Assistance Services for Facilitating Knowledge Sharing by Mohd Sharef, Nurfadhlina

    Published 2006
    “…KSFaci is embedded in web environment and is implemented using Java Servlet and runs under Apache server. …”
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  6. 6

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…The strength of the algorithm lies in the fact that it assists the evolution of a population of individuals who would thrive in the survival of the fittest towards the next generation. …”
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