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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
Published 2002“…In this paper we present a parallel algorithm to solve the above problem for arbitrary graphs using a Hopfield Neural Network model of computation. …”
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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…The proposed model was developed and implemented using MATLAB software. …”
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025“…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …”
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A neural networks algorithm for data path synthesis
Published 2003“…The algorithm is driven by a motion equation that determines the neurons firing conditions based on the modified Hopfield neural network model of computation. …”
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs†
Published 2010“…The proposed algorithm has a time complexity of O(1) for a neural network with n vertices and k colours. …”
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Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …”
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A systematic review of text classification research based on deep learning models in Arabic language
Published 2020“…The evaluation criteria used in the algorithms of different neural network types and how they play a large role in the highly accurate classification of Arabic texts are discussed. …”
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Evolutionary algorithms for state justification in sequential automatic test pattern generation
Published 2005“…A common search operation in sequential Automatic Test Pattern Generation is to justify a desired state assignment on the sequential elements. State justification using deterministic algorithms is a difficult problem and is prone to many backtracks, which can lead to high execution times. …”
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NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES
Published 2020“…., Boeing 737, is analyzed using the Artificial Neural Network and Weibull regression models. One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. …”
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A New Hamiltonian Semi-Analytical Approach to Vibration Analysis of Piezoelectric Multi-Layered Plates
Published 2024“…A new Hamiltonian semi-analytical method is established to investigate the free vibration characteristics of piezoelectric multilayered plates. …”
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Modelling Exchange Rates during Currency Crisis using Neural Networks
Published 2006“…The models are built using the feedforward ANN structure trained by the backpropagation algorithm. …”
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
Published 2025“…Drawing on more than fifteen harmonized datasets that span pyrimidines, ionic liquids, graphene oxides, and additional compound families, we benchmark traditional algorithms, such as artificial neural networks, support vector machines, k-nearest neighbors, random forests, against advanced graph-based and deep architectures including three-level directed message-passing neural networks, 2D3DMol-CIC, and graph convolutional networks. …”
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