Search Results - (( java application sensor algorithm ) OR ( _ identification learning algorithm ))

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  1. 1

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

    Published 2019
    “…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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    Article
  2. 2

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. …”
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    Thesis
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    Adaptive Linear System Identification over Simulated Wireless Environment by Elamin, Musab Jabralla Omer Elamin

    Published 2009
    “…The work looks thoroughly on three forms of instantaneous learning algorithms which are: first order algorithms (e.g. least mean square (LMS)), second order algorithms (e.g. …”
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    Thesis
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    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

    Published 2010
    “…This thesis proposes derivative free learning, using finite difference, methods for fixed size RBF network in comparison to gradient based learning for the application of system identification. …”
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    Thesis
  8. 8

    Date store management in sliding window based on-line identification algorithms by Asirvadam , Vijanth Sagayan, McLoone, Sean, Irwin, George W

    Published 2001
    “…Sliding window identification algorithms use information from a store of data to optimise on-line learning. …”
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    Conference or Workshop Item
  9. 9

    Wavelet network based online sequential extreme learning machine for dynamic system modeling by Mohammed Salih, Dhiadeen, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil

    Published 2013
    “…The proposed model used as system identification for nonlinear dynamic systems. The main advantage of OSELM over conventional algorithms is the ability of updating network weights sequentially through data sample-by-sample in a single learning step. …”
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    Conference or Workshop Item
  10. 10

    Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

    Published 2014
    “…The model is implemented using both unsupervised and supervised machine learning techniques in the form of Frequent Pattern Growth (FP-Growth) algorithm as feature transformation method and multivariate Bernoulli naïve Bayes classification model as the classifier. …”
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    Thesis
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    A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…However, other than RMSE, the maximum absolute error (MAE) for each of identification samples is very important. This paper propose a novel hybrid learning algorithm for the design of IT2FLS. …”
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    Article
  13. 13

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The proposed algorithm is able to improve the weaknesses in PQF model in updating and learning the important attributes for software quality assessment. …”
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    Thesis
  14. 14

    Identification and control of a small-scale helicopter by Deboucha, A., Taha, Z.

    Published 2010
    “…This identification process is based on the well-known gradient descent learning algorithm. …”
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    Article
  15. 15

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…System identification is getting more intensive from researcher to develop an algorithm with work efficiently and more accurate. …”
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    Student Project
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    Wavelet network: online sequential extreme learning machine for nonlinear dynamic systems identification by Mohammed Salih, Dhiadeen, Mohd Noor, Samsul Bahari, Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil

    Published 2015
    “…A single hidden layer feedforward neural network (SLFN) with online sequential extreme learning machine (OSELM) algorithm has been introduced and applied in many regression problems successfully. …”
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    Article
  17. 17

    Opposition- based simulated kalman filters and their application in system identification by Kamil Zakwan, Mohd Azmi

    Published 2017
    “…From literature, Opposition-based Learning (OBL) has been employed to increase the diversity (exploration) of search algorithm by allowing current population to be compared with an opposite population. …”
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    Thesis
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    Human activity recognition via accelerometer and gyro sensors by Tee, Jia Lin

    Published 2023
    “…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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    Final Year Project / Dissertation / Thesis
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    Approach For Optimizing Course Recommendation Based On Integrating Modified Felder-Silverman Learning Style Model With Meta-Heuristics Algorithm by Ashraf, Erum

    Published 2023
    “…It involves identifying potential courses learning style, validated through genetic and surrogate meta-heuristics optimization algorithms, and employing Felder-Silverman model for learning style identification. …”
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    Thesis
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    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…The combination of gist, MTH and SIFT features increased the performance of image identification and showed 49% accuracy. Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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    Thesis