بدائل البحث:
training algorithms » learning algorithms (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
based training » based learning (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
element » elements (توسيع البحث)
training algorithms » learning algorithms (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
based training » based learning (توسيع البحث)
data modeling » data models (توسيع البحث), spatial modeling (توسيع البحث)
element » elements (توسيع البحث)
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
منشور في 2021"…We also developed a binary template matching-based algorithm, which gives 93.64% accuracy 6X faster. …"
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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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Using genetic algorithms to optimize software quality estimation models
منشور في 2004"…This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …"
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
منشور في 2022الموضوعات: -
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
منشور في 2023"…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …"
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
منشور في 2021الموضوعات: -
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Bird’s Eye View feature selection for high-dimensional data
منشور في 2023"…However, high dimensional data often contains irrelevant features, outliers, and noise, which can negatively impact model performance and consume computational resources. …"
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Efficient Approximate Conformance Checking Using Trie Data Structures
منشور في 2021الموضوعات: "…Estimation error,Runtime,Computational modeling,Data structures,Approximation algorithms,Encoding,Computational efficiency…"
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TIDCS: A Dynamic Intrusion Detection and Classification System Based Feature Selection
منشور في 2020"…TIDCS reduces the number of features in the input data based on a new algorithm for feature selection. …"
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Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment
منشور في 2022"…This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …"
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Development of an Optimization Algorithm for Internet Data Traffic
منشور في 2020"…In this paper, an optimization algorithm is proposed to reduce net data traffic, which works at Internet layer in the TCP/IP reference model. …"
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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
منشور في 2024"…This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. …"
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