Search Results - (( java implementation means algorithm ) OR ( parameters activation function algorithm ))
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A web-based implementation of k-means algorithms
Published 2022“…The K-means algorithm has been around for over a century. …”
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Final Year Project / Dissertation / Thesis -
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Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. …”
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Journal -
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
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Biometrics electronic purse
Published 1999“…This paper looked into using biometrics as a mean of authentication, thus requiring a new generation of Smart Card technology to be implemented in banking and multiple applications environment. …”
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Proceeding Paper -
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
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 -
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Movie recommendation system / Najwa Syamimie Hasnu
Published 2020“…PHPMyAdmin is used to store the dataset and also acts as a database for user information. The algorithm chosen was implemented using Java Programming language and was tested using Root Means Square Error (RMSE) formula.…”
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Thesis -
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Image clustering comparison of two color segmentation techniques
Published 2010“…This project proposed a two color segmentation techniques such as K-means and Fuzzy C-means clustering algorithm that are accurately segment the desired images, which have the same color as the pre-selected pixels with background subtraction. …”
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Thesis -
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Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations
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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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...
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 -
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The effect of adaptive parameters on the performance of back propagation
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 -
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A harmony search-based learning algorithm for epileptic seizure prediction
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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Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant
Published 2014“…The error function is minimized directly by approximate Frechet tuning algorithm without explicit estimation of the model. …”
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Article -
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Loudspeaker nonlinearity compensation with inverse tangent hyperbolic function-based predistorter for active noise control
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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The tuning of error signal for back-propagation algorithms
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 -
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / 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
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 -
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
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 -
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Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The NLFXLMS algorithm is a stochastic gradient algorithm that incorporates the derivative of a nonlinear plant model which is represented by the scaled error function (SEF) in the controller design. …”
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