Search Results - (( developing e genetic algorithm ) OR ( java code classification algorithm ))

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    Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

    Published 2011
    “…A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
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    Article
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    Automated tournament management system with dynamic matchmaking using genetic algorithm / Wan Muhammad Aqil Wan Harun by Wan Harun, Wan Muhammad Aqil

    Published 2016
    “…Actives such as observation, interview and questionnaire has been done to gather the requirements for developing the system. CTMS are embedded with dynamic match making using genetic algorithm that can pairs players based on variation combination of criteria such as player’s gender, points and nation. …”
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    Thesis
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    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…Build up a user interface by using Visual Studio Code (VSC) to run the coding of Cascading Style Sheet (CSS), Hyper Text Markup Language (HTML) and JavaScript (JS) as a webpage and connect to Azure Machine Learning Model and this will allow the user from using the model from a webpage when they have active internet with any devices.…”
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    Multi-objective optimisation of assembly line balancing type-e problem with resource constraints by Masitah, Jusop

    Published 2016
    “…Apart from that, Elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) has not yet been implemented by previous researcher in the optimisation of Assembly Line Balancing Type-E (ALB-E) itself with resource constraints. …”
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    Thesis
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    Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems by Nazif, Habibeh

    Published 2010
    “…This thesis focuses on the development of a new stream of crossover within genetic algorithms, called Optimised Crossover Genetic Algorithm (OCGA) for solving combinatorial optimisation problems, which takes into account the objective function in finding the best ofspring solution among an exponentially large number of potential ofspring. …”
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    Adaptive genetic algorithm to improve negotiation process by agents e-commerce by Ebadi, Sahar

    Published 2011
    “…The proposed adaptive negotiation model is named Aspirated Genetic Algorithm (AGA) negotiation model which is a hybrid negotiation system composed of different negotiation strategies, Aspiration concept,genetic algorithm and Bayesian learning. …”
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    Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

    Published 2010
    “…The methodology developed a combined optimization technique. Also capacitor placement employing Genetic Algorithm is presented in achieving the proper arrangement of capacitor in a distribution network. …”
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    Development of group method of data handling based on genetic algorithm to predict incipient motion in rigid rectangular storm water channel by Ebtehaj, I., Bonakdari, H., Khoshbin, F., Hin, Ch. Joo Bong, Ab Ghanid, A.

    Published 2017
    “…Also, a sensitivityanalysis is presented to study the performance of each input combination in predictingincipient motion (15) Development of Group Method of Data Handling based on Genetic Algorithm to predict incipient motion in rigid rectangular storm water channel. …”
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    Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm by Salami, Momoh Jimoh Eyiomika, Tijani, Ismaila, Isqeel , Abdullateef Ayodele, Aibinu, Abiodun Musa

    Published 2013
    “…A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). …”
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    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…On the other hand, the superior performance of the genetic algorithm that implements an extended diversity control mechanism demonstrates that more competent genetic algorithms can be designed through customized operators. …”
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    Thesis