Search Results - (( java application rsa algorithm ) OR ( parameter identification learning algorithm ))

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  1. 1
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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  2. 2
    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING

    AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

    Published 2021
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  3. 3
    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe

    An improved RSA cryptosystem based on thread and CRT / Saheed Yakub Kayode and Gbolagade Kazeem Alagbe by Yakub Kayode, Saheed, Kazeem Alagbe, Gbolagade

    Published 2017
    “…Java programming language is used to implement the algorithm. …”
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  4. 4
    Secure Image Steganography Using Encryption Algorithm

    Secure Image Steganography Using Encryption Algorithm by Siti Dhalila, Mohd Satar, Roslinda, Muda, Fatimah, Ghazali, Mustafa, Mamat, Nazirah, Abd Hamid, An, P.K

    Published 2016
    “…A system based on the proposed algorithm will be implemented using Java and it will be more secured due to double-layer of security mechanisms which are RSA and Diffie-Hellman.…”
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  5. 5
    RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION

    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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  6. 6
    A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems

    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
    “…The proposed algorithm benefits from the combination of extreme learning machine (ELM) and non-dominated sorting genetic algorithm (NSGAII) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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  7. 7
    Digitally signed electronic certificate for workshop / Azinuddin Baharum

    Digitally signed electronic certificate for workshop / Azinuddin Baharum by Baharum, Azinuddin

    Published 2017
    “…Digital Signature was encrypted by RSA Algorithm, a very powerful asymmetrical encryption. …”
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  8. 8
    Wavelet network based online sequential extreme learning machine for dynamic system modeling

    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
    “…This attains good performance at extremely fast learning. The initial kernel parameters of WN played a big role to ensure fast and better learning performance. …”
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  9. 9
    Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter

    Simultaneous computation of model order and parameter estimation for system identification based on opposition-based simulated Kalman filter by Badaruddin, Muhammad, Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Ahmad Afif, Mohd Faudzi, Pebrianti, Dwi

    Published 2018
    “…Simultaneous Model Order and Parameter Estimation (SMOPE) has been proposed to address system identification problem efficiently using optimization algorithms. …”
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  10. 10
    Improved intrusion detection algorithm based on TLBO and GA algorithms

    Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

    Published 2021
    “…Optimization algorithms are widely used for the identification of intrusion. …”
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  11. 11
    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System

    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    Published 2020
    “…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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  12. 12
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…The statistical analysis value (mean) was taken from the parameter deviation index to see how much our proposed algorithm has improved. …”
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  13. 13
    Wavelet network: online sequential extreme learning machine for nonlinear dynamic systems identification

    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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  14. 14
    Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification

    Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification by Hakim, S.J.S., Abdul Razak, H.

    Published 2013
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  15. 15
    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model

    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model by Yaacob, Mohd. Shafiek, Jamaluddin, Hishamuddin

    Published 2001
    “…The method of selection of the input variables, the number of rules, and the learning rate are briefly discussed. Three methods for choosing the initial parameter of the fuzzy model are considered, namely the on-line, the off-line, and the random initial parameters. …”
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  16. 16
    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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  17. 17
    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems

    Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems by Salih, Dhiadeen Mohammed

    Published 2015
    “…Recently, an online sequential extreme learning machine (OSELM) algorithm has been introduced based on extreme learning machine (ELM) theories for single hidden layer feedforward neural networks (SLFN) and has been applied for different online applications. …”
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  18. 18
    Deep Learning Based Face Attributes Recognition

    Deep Learning Based Face Attributes Recognition by Saidi, Mohamad Hazim

    Published 2018
    “…The automated face identification application is helpful in assisting forensic to survey an area with the implementation of Machine Learning (ML). …”
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    Monograph
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  19. 19
    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…This sampling technique enables the identification of 10 related data features including temperature, voltage, and current, recorded during each charging cycle from the LIB parameters. …”
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  20. 20
    Twisted pair cable fault diagnosis via random forest machine learning

    Twisted pair cable fault diagnosis via random forest machine learning by Ghazali, N. B., Seman, F. C., Isa, K., Ramli, K. N., Z. Abidin, Z., Mustam, S. M., Haek, Haek, Z. Abidin, A. N., Asrokin, A.

    Published 2022
    “…Firstly, the line operation parameters and loop line testing parameters are collected and used to analyze. …”
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