بدائل البحث:
modeling algorithm » scheduling algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data algorithms » jaya algorithm (توسيع البحث)
presented » present (توسيع البحث)
element » elements (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data algorithms » jaya algorithm (توسيع البحث)
presented » present (توسيع البحث)
element » elements (توسيع البحث)
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A Neural Networks Algorithm for the Minimum Colouring Problem Using FPGAs†
منشور في 2010"…This paper presents a hardware implementation to solve the graph colouring problem (chromatic number χ(G)) for arbitrary graphs using the Hopfield neural network (HNN) model of computation. …"
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A neural networks algorithm for data path synthesis
منشور في 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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A Parallel Neural Networks Algorithm for the Clique Partitioning Problem
منشور في 2002"…The clique partitioning problem has important applications in many areas including VLSI design automation, scheduling, and resources allocation. 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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Modelling Exchange Rates during Currency Crisis using Neural Networks
منشور في 2006"…The models are built using the feedforward ANN structure trained by the backpropagation algorithm. …"
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conferenceObject -
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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
منشور في 2023"…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …"
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
منشور في 2025"…The BRNN model, refined using the Adagrad optimization algorithm, efficiently integrates the learned features from both branches. …"
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Multiclass feature selection with metaheuristic optimization algorithms: a review
منشور في 2022"…Datasets can be classified using various methods. Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …"
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors
منشور في 1992"…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …"
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masterThesis -
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A systematic review of text classification research based on deep learning models in Arabic language
منشور في 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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Mobile Robot Trajectory Tracking Using Neural Networks
منشور في 2009احصل على النص الكامل
doctoralThesis -
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NEURAL NETWORK MODEL FOR PLANNED REPLACEMENT OF BOEING 737 BRAKES
منشور في 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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Optimum sensors allocation for drones multi-target tracking under complex environment using improved prairie dog optimization
منشور في 2024"…This hybrid approach, the Improved Prairie Dog Optimization Algorithm (IPDOA) with the Genetic Algorithm (GA), utilizes the strengths of both algorithms to improve the overall optimization performance. …"
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“Adaptive Control Technique Using Multilayer Feedforward Neural Networks”
منشور في 2005"…This paper presents a new method for implementing adaptive controllers using multilayer feedforward neural networks (MFNN). …"
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A method for data path synthesis using neural networks
منشور في 2017"…The method is based on the modified Hopfield neural network model of computation and the McCulloch-Pitts binary neuron model. …"
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conferenceObject -
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Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks
منشور في 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. …"