Search Results - (( layer selection means algorithm ) OR ( java application testing algorithm ))

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  1. 1

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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    Final Year Project
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    Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

    Published 2008
    “…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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    Article
  3. 3

    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

    Published 2020
    “…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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    Journal
  4. 4

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Three algorithms of Linear (PURELIN), hyperbolic tangent sigmoid (TANSIG) and logistic sigmoid (LOGSIG) activation functions were selected for output layer. …”
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    Thesis
  5. 5

    An Improved Wavelet Neural Network For Classification And Function Approximation by Ong , Pauline

    Published 2011
    “…First, the types of activation functions used in the hidden layer of the WNN were varied. Second, the proposed enhanced fuzzy c-means clustering algorithm—specifically, the modified point symmetry-based fuzzy c-means (MPSDFCM) algorithm—was employed in selecting the locations of the translation vectors of the WNN. …”
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    Thesis
  6. 6

    Removal of heavy metals from water by functionalized carbon nanotubes with deep eutectic solvents: An artificial neural network approach / Seef Saadi Fiyadh by Seef Saadi , Fiyadh

    Published 2019
    “…Moreover, various indicators were implemented to evaluate the ANN model’s productivity including relative root mean square error (RRMSE), mean square error (MSE), root mean square error (RMSE), mean absolute percentage error (MAPE) and relative error (RE). …”
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    Thesis
  7. 7

    Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System by Ismail, F. B., Al-Kayiem, Hussain H.

    Published 2010
    “…Comparisons have been made between the results from the two algorithms based on the Root Mean Square Error. The one hidden layer with one neuron using BFG training algorithm provides the best optimum neural network structure. …”
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    Article
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    Implementation of (AES) Advanced Encryption Standard algorithm in communication application by Moh, Heng Huong

    Published 2014
    “…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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    Undergraduates Project Papers
  12. 12

    Development of a hybrid dynamic fuzzy encoder and decoder model for colour QR code by Badawi, Bakri

    Published 2022
    “…With the fuzzy encoder algorithm, the number of layers required to overcome the static colour limitation could be selected. …”
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    Thesis
  13. 13

    Reliable multiclass cancer classification of microarray gene expression profiles using an improved wavelet neural network by Zainuddin, Zarita, Pauline, Ong

    Published 2011
    “…First, the types of activation functions used in the hidden layer of the WNN were varied. Second, the proposed enhanced fuzzy c-means clustering algorithm—specifically, the modified point symmetry-based fuzzy c-means (MSFCM) algorithm—was employed in selecting the locations of the translation vectors of the WNN. …”
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    Article
  14. 14

    The basics of multi-layer feedforward neural networks / Nurul Aityqah Yaccob and Farizuwana Akma Zulkifle by Yaccob, Nurul Aityqah, Zulkifle, Farizuwana Akma

    Published 2025
    “…The coefficients assigned to these predictors are called "weights," and the forecasts are generated through a linear combination of the inputs. The weights are selected in the neural network framework using a "learning algorithm" that minimizes a "cost function," such as the mean squared error (MSE). …”
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    Monograph
  15. 15

    Classification System for Heart Disease Using Bayesian Classifier by Magendram, Anusha

    Published 2007
    “…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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    Thesis
  16. 16

    Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture by Chong, Jin Hui

    Published 2010
    “…The computational complexity (total number of arithmetic operations) of proposed LC-QR algorithm is significantly lower than the conventional QR decomposition, zero-forcing (ZF) and minimum mean square error (MMSE) detection algorithm. …”
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    Thesis
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    Human odour detection approach using machine learning by Ahmed Qusay Sabri

    Published 2019
    “…Besides, numerous neural network topologies are tested by means of a selection of number of neurons and hidden layers. …”
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    Thesis