Search Results - (( java implementation mining algorithm ) OR ( layer perception study algorithm ))

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  1. 1

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
    “…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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    Thesis
  2. 2

    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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    Article
  3. 3

    Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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    Conference or Workshop Item
  4. 4

    Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

    Published 2009
    “…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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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
  6. 6

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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    Thesis
  7. 7

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
  8. 8

    An application of artificial neural network on short term load forecasting using back propagation algorithm / Elia Erwani Hassan by Hassan, Elia Erwani

    Published 1998
    “…The Back Propagation Algorithm, which consists of the multi-layered perception model, makes possible to train the ANN training pattems. …”
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    Thesis
  9. 9

    IoT Soil Moisture Monitoring and Irrigation System Development by Chew, Kim Mey, Syvester Tan, Chiang Wei, Gary Loh, Chee Wyai, Nancy, Bundan, Yiiong, Siew Ping

    Published 2020
    “…At the same time, with a self-sufficient and self-organized irrigation system based on the water-control algorithm. The developed system covered the three layers in IoT architecture: perception layer, network layer and application layer. …”
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    Proceeding
  10. 10

    Forecasting The Growth of Manufacturing Industry in Malaysia Using Artificial Neural Network by Zakaria, Norzaini

    Published 2006
    “…The effectiveness of ANN for predicting one criterion, Y form several predictors, X, is investigated. Comparative studies are examined between the result of the predictions from the ANN model trained with Multi-Layer Feed forward Perception, a Generalised Regressions Neural Network (GRNN) algorithm and the result obtained from traditional statistical approach.…”
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    Thesis
  11. 11

    Application of artificial neural network in discriminating the agarwood oil quality using significant chemical compounds / Mohd Hezri Fazalul Rahiman … [et al.] by Rahiman, Mohd Hezri Fazalul, Ismail, Nurlaila, Taib, Mohd Nasir, Mohd Ali, Nor Azah, Tajuddin, Saiful Nizam

    Published 2014
    “…Data Processing - ANN Application ( Data pre-processing using Z-score, ANN design structure/architecture - parameter optimisation, training and testing the algorithm) Result & Discussion: ANN parameter optimisation - final error for learning rate, momentum rate and hidden layer size ANN final design parameter - Nodes in input layer: 7, Nodes in hidden layer size: 2, Output layer size: 1, learning rate: 0.9, Momentum rate: 0.7, Error goal: 0.01, Epochs: 100 ANN prediction: high accuracy for training and testing prediction (refer to the figure in poster) Patent & List of contributions: 1. …”
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    Book Section
  12. 12

    Multivariate Time Series Forecasting Of Crude Palm Oil Price Using Machine Learning Techniques by Hashim, Ummi Rabaah, Kanchymalay, kasturi, Salim, Naomie, Sukprasert, Anupong, Krishnan, Ramesh

    Published 2017
    “…Experiments were conducted using multi-layer perception, support vector regression and Holt Winter exponential smoothing techniques.The results were assessed by using criteria of root mean square error (RMSE),means absolute error (MAE),means absolute percentage error (MAPE) and Direction of accuracy (DA).Among these three techniques, support vector regression(SVR) with Sequential minimal optimization (SMO) algorithm showed relatively better results compared to multi-layer perceptron and Holt Winters exponential smoothing method. …”
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    Article
  13. 13

    Artificial neural network modeling of grinding of ductile cast iron using water based sio2 nanocoolant by M. M., Rahman, K., Kadirgama, Azma Salwani, Ab Aziz

    Published 2014
    “…An artificial neural network model is developed for predicting the surface roughness and MRR. Multi-layer perception and a batch back propagation algorithm are used. …”
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    Article
  14. 14

    Cyber-Crime Detection: Experimental Techniques Comparison Analysis by Aljarboua E.F., Bte Md. Din M., Bakar A.A.

    Published 2023
    “…The objective of this research paper is to conduct experimental techniques comparison analysis for cyber-crime detection by reviewing all possible machine learning algorithms for automatic detection. The key focus of the study is on the use of eight classifiers models which are Logistic Regression (LR), Decision Tree (DT), K-nearest Neighbors (KNN), Support Vector Machine (SVM), Naive Bayes (NB), Random Forest (RF), eXtreme Gradient Boosting (XGBoost) and Multiple layer perception (MLP). …”
    Conference Paper
  15. 15

    Optimization of abrasive machining of ductile cast iron using water based SiO2 nanocoolant : a radial basis function by Azma Salwani, Ab Aziz

    Published 2012
    “…Artificial neural network (ANN) model is developed for predicting the results of the surface roughness and MRR. Multi-Layer Perception (MLP) along with batch back propagation algorithm are used. …”
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    Undergraduates Project Papers
  16. 16