Search alternatives:
training algorithm » learning algorithms (Expand Search)
could algorithm » mould algorithm (Expand Search), carlo algorithm (Expand Search), colony algorithm (Expand Search)
based training » based learning (Expand Search)
data finding » data mining (Expand Search), data hiding (Expand Search)
training algorithm » learning algorithms (Expand Search)
could algorithm » mould algorithm (Expand Search), carlo algorithm (Expand Search), colony algorithm (Expand Search)
based training » based learning (Expand Search)
data finding » data mining (Expand Search), data hiding (Expand Search)
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A multi-class discriminative motif finding algorithm for autosomal genomic data. (c2015)
Published 2016“…Our algorithm first performs a feature selection step to define differentiable SNPs. …”
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masterThesis -
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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masterThesis -
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Web Based Online Hybrid Teaching Method of Network Music Course
Published 2022“…The experimental results show that the average accuracy of the improved algorithm is 79.63% in the limited training times, and has better adaptability. …”
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A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT
Published 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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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm
Published 2022“…The slime mould algorithm (SMA) gives good results in finding the best solutions to optimization problems. …”
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Genetic and heuristic algorithms for regrouping service sites. (c2000)
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masterThesis -
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A genetic algorithm for corrective retesting. (c1995)
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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“…The complex gas hydrate prevention unit is simulated using the MLPNN model trained by 20 different optimization algorithms. This study investigates the gradient-based, evolutionary, and Bayesian-based optimization algorithms. …”
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Improved search-tree algorithms for the cluster edit problem. (c2011)
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masterThesis -
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An image processing and genetic algorithm-based approach for the detection of melanoma in patients
Published 2018“…The second phase classifies lesions using a Genetic Algorithm. Our technique shows a significant improvement over other well-known algorithms and proves to be more stable on both training and testing data.…”
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Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering
Published 2022“…This paper proposes a new data clustering method using the advantages of metaheuristic (MH) optimization algorithms. …”
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…The proposed improved ABO method consists in reducing the number of samples in the training data set using the Euclidean distance and extracting the most significant features from the reduced data using ABO algorithm. …”
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AI and IoT-based concrete column base cover localization and degradation detection algorithm using deep learning techniques
Published 2023“…This paper proposes a novel automated algorithm for the health monitoring of concrete column base cover degradation based on IoT and the state-of-the-art deep learning framework, Convolutional Neural Network (CNN). …”
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Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
Published 2021“…We also developed a binary template matching-based algorithm, which gives 93.64% accuracy 6X faster. …”
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A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…Machine learning (ML) methods are widely used in IDS. Due to a limited training dataset, an ML-based IDS generates a higher false detection ratio and encounters data imbalance issues. …”
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