Search Results - (( basic evaluating gaps algorithm ) OR ( java implementation tree algorithm ))

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  1. 1

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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  2. 2

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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    Thesis
  3. 3

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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    Thesis
  4. 4

    A phonetically rich and balanced lexical corpus using zipfian distribution for an under resourced language / Aminath Farshana by Aminath , Farshana

    Published 2018
    “…The performance of the proposed method was also evaluated by comparing the results with an existing benchmark method (greedy algorithm). …”
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    Thesis
  5. 5

    Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks by Han, Fengrong

    Published 2022
    “…Accordingly, this study aspires to bridge the research gap by exploring a new DV-Hop algorithm to build a fast, costefficient, strong range-free localization scheme. …”
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  6. 6

    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

    Published 2014
    “…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
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    Thesis