Search Results - (( developing wealth selection algorithm ) OR ( java code classification algorithm ))

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  1. 1

    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
  2. 2

    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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    Monograph
  3. 3

    Multi-agent and artificial neural networks prediction framework development for stock investment strategy by Phang, Wai San

    Published 2016
    “…Kuala Lumpur Stock Exchange (KLSE) was selected as the targeted stock market. Four types of agents were developed, including the Web Mining Agent (WMA), the Wealth Forecasting Agent (WFA), the Strategy Agent (SA), and the Wealth Planning Agent (WPA). …”
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    Thesis
  4. 4

    Multi agent and artificial neural networks prediction framework development for stock investment strategy by Phang, Wai San

    Published 2016
    “…Kuala Lumpur Stock Exchange (KLSE) was selected as the targeted stock market. Four types of agents were developed, including the Web Mining Agent (WMA), the Wealth Forecasting Agent (WFA), the Strategy Agent (SA), and the Wealth Planning Agent (WPA). …”
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    Thesis
  5. 5

    Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

    Published 2005
    “…Energy is considered a prime agent in the generation of wealth and also a significant factor in economic development. …”
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    Thesis
  6. 6

    Forecasting time series data using hybrid grey relational artificial neural network and auto regressive integrated moving average model by Salleh, Roselina, Shamsuddin, Siti Mariyam

    Published 2007
    “…Accordingly, the aim of this research is to develop a new hybrid model by combining a linear and nonlinear model for forecasting time series data. …”
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    Book Section
  7. 7