Search Results - (( development time reporting algorithm ) OR ( java implication based algorithm ))

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    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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    Article
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    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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    Article
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    Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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    Article
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    Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

    Published 2004
    “…In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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    Article
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    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
    “…In this project, an algorithm will be developed to predict the amount of time needed for the incoming public bus to arrive, based on the current location of the bus and the current time. …”
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    Final Year Project
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    Intelligent DNA signature detection for internet worms by Ghazali, Osman

    Published 2011
    “…Active worms spread in an automated fashion flooding the Internet in a very short time.Slammer worm infected more than 90% of vulnerable machines within 10 minutes on January 25th, 2003.Hence it is necessary to monitor and detect the worms as soon as they are introduced to minimize the damage caused by them.This project concentrates on developing an anti-scanning worm detection system that can automatically detect and control the spread of internet scanning worms without any manual intervention.The Intelligent Failure Connection Algorithm (IFCA) developed in this project can detect both stealth and normal worms within a short time.Experiments conducted as part of the evaluation shows that IFCA detects a worm within two scanning cycles of the worm.This is faster than any of the currently available algorithms or mechanisms reported in the literature.The IFCA uses Artificial Immune System (AIS) for the purpose of monitoring and detecting the worms.The Traffic Signature Algorithm (TSA) developed in the project captures the traffic signature of the worm from the infector when it sends the traffic to the victim.The Intelligent DNA Signature Detection Algorithm (IDNASDA) algorithm works by breaking an infection session into different infection phases, each phase containing a number of different traffic such as Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), or User Datagram Protocol (UDP).Finally it converts the traffic signature to DNA signature.The tests carried out show that the IDNASD could detect DNA signature for MSBlaster worm.…”
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    Monograph
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    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…Core functionality of the simulator are job generation, volunteer generation, simulating algorithms, generating graphical charts and generating reports. …”
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    Final Year Project
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    Evaluation of outlier filtering algorithms for accurate measurement of travel time reliability incorporating lane-splitting situations / Obada M. A. Asqool by Obada , M. A. Asqool

    Published 2022
    “…The second stage was to investigate the sensitivity of the algorithm parameters for different days. To analyse TTR, Travel Time Index (TTI), Planning Time Index (PTI), and Buffer Time Index (BTI) were calculated with respect to the time of day (TOD), day of week (DOW), holidays, and election days. …”
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    Thesis
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