بدائل البحث:
modeling algorithm » scheduling algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
modeling algorithm » scheduling algorithm (توسيع البحث)
using algorithm » cosine algorithm (توسيع البحث)
data algorithm » jaya algorithm (توسيع البحث), deer algorithm (توسيع البحث)
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Using genetic algorithms to optimize software quality estimation models
منشور في 2004"…In the first approach, we assume the existence of several models, and we use a genetic algorithm to combine them, and adapt them to a given data set. …"
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masterThesis -
3
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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Predictive Model of Psychoactive Drugs Consumption using Classification Machine Learning Algorithms
منشور في 2023"…Eighteen classification models were built using different classification algorithms such as Gaussian Naive Bais, Logistic Regression, k-nearest neighbors, Random Forest, and Decision Tree. …"
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
منشور في 2022"…Distributed clustering algorithms, however, can fulfil this gap. They extract a classification model from the distributed objects even when they are in different sites and locations. …"
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masterThesis -
8
An ant colony optimization algorithm to improve software quality prediction models
منشور في 2011"…As a result, the prediction models built on one data set show a significant deterioration of their accuracy when they are used to classify new, unseen data. …"
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article -
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
منشور في 2022"…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …"
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An Effective Hash Based Assessment and Recovery Algorithm for Healthcare Systems
منشور في 2019"…Finally, the experimental results prove the improvements provided by our hash based algorithm over previously suggested models.…"
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masterThesis -
13
Cryptocurrency Exchange Market Prediction and Analysis Using Data Mining and Artificial Intelligence
منشور في 2020"…One of the best algorithms in terms of the result is the Long Short Term Memory (LSTM) since it is based on recurrent neural networks which uses loop as a method to learn from heuristics data. …"
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Allocation and re-allocation of data in a grid using an adaptive genetic algorithm
منشور في 2006"…Allocation and re-allocation of data in a grid using an adaptive genetic algorithm. …"
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احصل على النص الكامل
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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Efficient Approximate Conformance Checking Using Trie Data Structures
منشور في 2021"…By encoding the proxy behavior using a trie data structure, we obtain a logarithmically reduced search space for alignment computation compared to a set-based representation. …"
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Delay Optimization in LoRaWAN by Employing Adaptive Scheduling Algorithm With Unsupervised Learning
منشور في 2023"…This paper aims to optimize the delay in LoRaWAN by using an Adaptive Scheduling Algorithm (ASA) with an unsupervised probabilistic approach called Gaussian Mixture Model (GMM). …"
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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
منشور في 2022"…Moreover, the image pixels in different and more similar areas of the image are located next to one another in a group and classified using the specified thresholds. As a result, the embedding capacity in each class can increase by reducing the value of the difference between two consecutive pixels, and the distortion of the marked image can decrease after inserting the personal data using the DE method. …"
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