Search Results - (( java application sensor algorithm ) OR ( using composition means algorithm ))

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    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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    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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    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction by Hammid, Ali Thaeer, M. H., Sulaiman, Awad, Omar I.

    Published 2018
    “…The results display that the regression coefficient, root-mean-square error, mean absolute error, and mean bias error values of the suggested model are 99.86%, 1.87%, 0.91%, and 0.31%, respectively. …”
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    State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission by Gholizadeh, S., Leman, Z., Baharudin, B.T.H.T.

    Published 2023
    “…Three different ensemble learning methods namely, XGboost, LightGBM, and CatBoost were chosen to predict damages and AE parameters. SHAP values were used to select AE key features and K-means algorithms were employed to classify damage severity. …”
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    Prediction of optimum compositions of parenteral nanoemulsion system loaded with low solubility drug for treatment of schizophrenia by artificial neural network by Samiun, Wan Sarah, Basri, Mahiran, Masoumi, Hamid Reza Fard, Khairudin, Nurshafira

    Published 2016
    “…The particle size of samples in various compositions was measured as output. To obtain the optimum topologies, ANNs were trained by Incremental Back Propagation (IBP), Genetic Algorithm (GA), Batch Back Propagation (BBP), Quick Propagation (QP), and Levenberg-Marquardt (LM) algorithms for testing data set. …”
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    Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

    Published 2018
    “…The classical benchmark problems and composite benchmark functions from Congress on Evolutionary Computation (CEC) 2005 special session is used for validate SDAA. …”
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    Thesis
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    Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

    Published 2006
    “…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. Ultimately, the algorithm development program designed earlier is linked up directly to the robotic model for program implementation and verification. …”
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    Conference or Workshop Item
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    Development of a novel natural frequencies prediction tool for laminated composite plates using integrated artificial neural network (ANN) - simulink MATLAB / Mohd Arif Mat Norman by Mat Norman, Mohd Arif

    Published 2024
    “…The prediction tool utilises an Artificial Neural Network (ANN) with a two-layer feed-forward algorithm and ten hidden layers, using Levenberg-Marquardt as the training algorithm. …”
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    Thesis
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    Pemodelan data indeks komposit Kuala Lumpur menggunakan neurofuzzy by Mohd. Yunos, Zuriahati

    Published 2006
    “…Root Mean Square Error (RMSE) and Mean Absolute Percentage of Error (MAPE) are chosen to measure the prediction accuracy. …”
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    Thesis
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    Modeling financial environments using geometric fractional Brownian motion model with long memory stochastic volatility by Al Haqyan, Mohammed Kamel Mohammed

    Published 2018
    “…All parameters involved in the developed model are estimated by using innovation algorithm. A simulation study is then conducted to determine the performance of the new model. …”
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    Thesis
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    Empirical analysis of parallel-NARX recurrent network for long-term chaotic financial forecasting by Abdulkadir, S.J., Yong, S.-P.

    Published 2014
    “…The experimental results based on mean absolute percentage error (MAPE) and other forecasting error metrics shows that P-NARX network trained with Bayesian regulation slightly outperforms Levenberg-marquardt, Resilient back-propagation and one-step-secant training algorithm in forecasting daily Kuala Lumpur Composite Indices. …”
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    Conference or Workshop Item
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    Recovery of tree community composition across different types of anthropogenic disturbances and characterization of their effect using Landsat time series in Bornean tropical monta... by Keiko Ioki, Daniel James, Phua, Mui How, Satoshi Tsuyuki, Nobuo Imai

    Published 2022
    “…We also investigated the use of metrics from spectral trajectories of a Landsat time series (LTS) change detection algorithm (LandTrendr) to identify characteristics of disturbance events and their linkage to the recovery of tree community composition, with field validation. …”
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