Search Results - (( java implementation success algorithm ) OR ( parameter activation function algorithm ))

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  1. 1

    Pairwise testing tools based on hill climbing algorithm (PTCA) by Lim, Seng Kee

    Published 2014
    “…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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    Undergraduates Project Papers
  2. 2

    Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework by Asaad Aref, Ibrahim

    Published 2004
    “…Java Media Framework library and the RTP protocol for audio transmission were used as development tools.The developed system designed in this thesis together with experimental results proved that the system could be implemented successfully. …”
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    Thesis
  3. 3

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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    Final Year Project
  4. 4

    An approach for cross-site scripting detection and removal based on genetic algorithms. by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia

    Published 2014
    “…The proposed approach is, so far, only implemented and validated on Java-based Web applications, although it can be implemented in other programming languages with slight modifications. …”
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    Conference or Workshop Item
  5. 5
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    Cross-site scripting detection based on an enhanced genetic algorithm by Hydara, Isatou, Md Sultan, Abu Bakar, Zulzalil, Hazura, Admodisastro, Novia Indriaty

    Published 2015
    “…The proposed approach is, so far, only implemented and validated on Java-based Web applications, although it can be implemented in other programming languages with slight modifications. …”
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    Conference or Workshop Item
  7. 7

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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    Thesis
  8. 8

    Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

    Published 2022
    “…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
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    Article
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  10. 10

    Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions by Ahmed, Mashuk, Nasser, Abdullah B., Kamal Z., Zamli, Heripracoyo, Sulistyo

    Published 2022
    “…CS and JA have implemented in the same platform (Intellij IDEA Community Edition 2020.2.3) using the same language (Java). …”
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    Conference or Workshop Item
  11. 11

    The PID controller parameter tuning based on a modified differential evolutionary optimization algorithm for the intelligent active vibration control of a combined single link robo... by Moloody, Abbas, As’arry, Azizan, Hong, Tang Sai, Raja Kamil, ., Zolfagharian, Ali

    Published 2025
    “…Here, in this research by comprising three of the most effective variational techniques now, a Modified Differential Evolutionary Optimization Algorithm (MDEOA) method is suggested to handle the challenge of adjusting the PID controller parameters for the Intelligent Active Vibration Control (IAVC) of a Combined Single Link Robotics Flexible Manipulator (CSLRFM) in order to reduce the undesired effects of vibration. …”
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    Article
  12. 12

    The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

    Published 2012
    “…The activation functions are adjusted by the adaptation of gain parameters together with adaptive momentum and learning rate value during the learning process. …”
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    Thesis
  13. 13

    A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

    Published 2016
    “…The learning phase of wavelet neural network entails the task of finding the optimal set of parameter, which includes wavelet activation function, translation centers, dilation parameter, synaptic weight values, and bias terms. …”
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    Article
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  15. 15

    Loudspeaker nonlinearity compensation with inverse tangent hyperbolic function-based predistorter for active noise control by Sahib, Mouayad Abdulredha, Raja Ahmad, Raja Mohd Kamil

    Published 2014
    “…In active noise control (ANC), the performance of the filtered-x least mean squares (FXLMS) algorithm is degraded by the saturation of the loudspeaker in the secondary path. …”
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    Article
  16. 16

    The tuning of error signal for back-propagation algorithms by Rengasamy, Renugah

    Published 2008
    “…This new algorithm is proven to be a better algorithm. The main purpose of this study is to evaluate the efficiency of improved two-term error function by applying three different values of ß parameter in the activation function. …”
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    Thesis
  17. 17

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There have two most uses activation function namely tansig and logsig. The essence of this study is that it compares the effect of activation functions (tansig and logsig) in the performance of time series forecasting since activation function is the core element of any artificial neural network model. …”
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    Thesis
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    Embedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA system by Krishnan P.S., Kiong T.S., Koh J., Yap D.

    Published 2023
    “…In this paper, an embedded parallel and distributed genetic algorithm (EPDGA) with dynamic parameter setting on a multiprocessor system is proposed. …”
    Conference paper
  20. 20

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…The performance of ANNs depend on many factors, including the network structure, the selection of activation function, the learning rate of the training algorithm, and initial synaptic weight values, the number of input variables, and the number of units in the hidden layer. …”
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    Thesis