Search Results - (( java adaptation optimization algorithm ) OR ( basic based training algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu
Published 2005“…The methodology used in the development of this project is basically based on the eight major steps. There are problem assessment, data acquisition, cropping, pre-processing, design, training, testing and documentation. …”
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Thesis -
3
Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…Another structure of MLP trained using backpropagation algorithm is used to detect and locate the base of the young corn tree using the skeleton of the segmented image. …”
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4
Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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Static image of hand gesture for numerical sign language recognition system using backfrofagation neural network / Erman Ibrahim
Published 2007“…This project is about recognizing hand gesture for sign language using backpropagation (BP) algorithm that is one of the training algorithms used in the Artificial Neural Network (ANN). …”
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Thesis -
7
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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9
A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…This stochastic learning method is a useful addition to the existing methods for determining the center and smoothing factors of radial basis function neural networks, and it can also help the network more efficiently train. GDP forecasting is aided by the genetic algorithm radial basis neural network, which allows the government to make timely and effective macrocontrol plans based on the forecast trend of GDP in the region. …”
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Improving neural networks training using experiment design approach
Published 2005“…Randomly select the m data set for conventional training algorithm. One more data (m+ 1) is entered to train the NN again. …”
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11
EMG motion pattern classification through design and optimization of neural network
Published 2012“…Different types of ANN models are basically structured with many interconnected network elements which can develop pattern classification strategies based on a set of input/training data. …”
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Proceeding Paper -
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A Novel Method for Fashion Clothing Image Classification Based on Deep Learning
Published 2023“…Furthermore, the study adopted the approximate dynamic learning rate update algorithm in the model training to realize the learning rate’s self-adaptation, ensure the model’s rapid convergence, and shorten the training time. …”
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Computerized simulation system for ECM radar system
Published 2007“…Finally before code generation, the flow chart of the simulation algorithm was used. The system is based on C++ Builder application; it has the capability of OO programming with the enhancement of Visual Component Library (VCL). …”
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Thesis -
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EMG motion pattern classification through design and optimization of Neural Network
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Working Paper -
15
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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16
Model Identification Using Neuro-Fuzzy Approach
Published 2018“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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Model Identification Using Neuro-Fuzzy Approach
Published 2018“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
Published 2021“…For BrC detection, an efficient and reliable model namely Ensemble BrC Detection Network (EBrC-Net) and three misclassification reduction (McR) algorithms are developed. The proposed EBrC-Net model is based on deep learning (DL) based approach. …”
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