Search Results - (( variable generation drops algorithm ) OR ( java application mining algorithm ))

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

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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    Article
  4. 4

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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    Conference or Workshop Item
  5. 5

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    “…(iv) In addition, IWD has two variables that have a large effect on the performance and the convergence of the algorithm (Alijla et al., 2013). …”
    thesis::doctoral thesis
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    DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS by AYOUB MOHAMMED, MOHAMMED ABDALLA

    Published 2011
    “…It was found that (by the Group Method of Data Handling algorithm), length of the pipe, wellhead pressure, and angle of inclination have a pronounced effect on the pressure drop estimation under these conditions. …”
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    Thesis
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    Development of a Universal Artificial Neural Network Model for Pressure Loss Estimation in Pipeline Systems; A comparative Study by Ayoub, Mohammed Abdalla, Demiral, B.M.R

    Published 2010
    “…The data covered a wide range of variables such as oil rate (up to 25000 STB/D), water cut (up to 60%), angles of inclination (from -80 to 210), pipe length up to 26.0 km and pressure drop (from 10 to 250 psi). the model has been generated using the Back-propagation technique with Bayesian Regularization training algorithm for predicting pressure drop in pipelines under various angles of inclination. …”
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    Conference or Workshop Item
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    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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    Thesis
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    The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells by Ayoub, Mohammed Abdalla

    Published 2010
    “…Moreover, the output from the ANNs will be utilized plus selected other input parameters as controlling variables for optimizing the production from a multiphase producing field using Genetic Algorithms (GA).…”
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    A high-performance control scheme for photovoltaic pumping system under sudden irradiance and load changes by Talbi, Billel, Krim, Fateh, Rekioua, Toufik, Mekhilef, Saad, Laib, Abdelbaset, Belaout, Abdesslam

    Published 2018
    “…An improved variable step size perturb and observe (P&O) algorithm is proposed to reduce the steady-state PV power fluctuation, to accelerate the tracking operation under sudden irradiance changes, and to protect IM under load drops. …”
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  13. 13

    Artificial neural network for anomalies detection in distillation column by Taqvi, S.A., Tufa, L.D., Zabiri, H., Mahadzir, S., Shah Maulud, A., Uddin, F.

    Published 2017
    “…The effect of these faults on process variables i.e. changes in distillate and bottom composition, distillate and bottom temperature, bottom flow rate, and the pressure drop is observed. …”
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    Article
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    A multi-nets ANN model for real-time performance-based automatic fault diagnosis of industrial gas turbine engines by Tahan, M., Muhammad, M., Abdul Karim, Z.A.

    Published 2017
    “…Two back-propagation training algorithms, namely the Levenberg–Marquardt and Bayesian regularization algorithms, and the k-fold cross-validation technique, were employed to train the optimal networks using a training data set. …”
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    Minimization of torque ripple and flux droop using optimal DTC switching and sector rotation strategy by Ahmad Tarusan, Siti Azura

    Published 2022
    “…Another drawback of conventional DTC is that the presence of voltage drop in a stator resistance at low operating speeds causes a droop in stator flux performance. …”
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    Thesis