Search Results - (( developing equation mining algorithm ) OR ( java optimization sensor algorithm ))

  • Showing 1 - 5 results of 5
Refine Results
  1. 1

    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

    Published 2019
    “…Wireless sensor networks operate through commonly self-organized sensor nodes to transfer data in a multi-hop approach to a central sink. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

    Published 2019
    “…Wireless sensor networks operate through commonly self-organized sensor nodes to transfer data in a multi-hop approach to a central sink. …”
    Get full text
    Get full text
    Get full text
    Article
  3. 3

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  4. 4

    Application of data mining techniques for economic evaluation of air pollution impact and control by Lukman, Iing

    Published 2007
    “…It was different from the common formula of GNP. The formula or equation model of urban SO2 concentration was also found through the GMDH algorithms. …”
    Get full text
    Get full text
    Thesis
  5. 5

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
    Get full text
    Get full text
    Get full text
    Thesis