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modeling algorithm » scheduling algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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Indexing Arabic texts using association rule data mining
Published 2019“…The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. …”
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123
Big Data Energy Management, Analytics and Visualization for Residential Areas
Published 2020“…A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. …”
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
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doctoralThesis -
125
An efficient approach for textual data classification using deep learning
Published 2022“…Textual data contains much useless information that must be pre-processed. …”
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Bee colony algorithm for assigning proctors to exams. (c2013)
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masterThesis -
127
Eye-Clustering: An Enhanced Centroids Prediction for K-means Algorithm
Published 2024“…The proposed method, named Eye-means, emulates the natural ocular process of estimating initial centroids. To achieve this goal, supervised machine learning was employed to train models on graphs with labeled data points, where each graph contains a set of points and a label indicating the centroid determined by K-means. …”
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masterThesis -
128
Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…Whilst different models are proposed for STLF, they are based on small historical datasets and are not scalable to process large amounts of big data as energy consumption data grow exponentially in large electric distribution networks. …”
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CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…Soft voting and hard voting strategies are employed to ensemble these CNN models. The pre-trained DenseNet201 network is used for CNN feature extraction from each task-specific handwritten image data. …”
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130
CNN feature and classifier fusion on novel transformed image dataset for dysgraphia diagnosis in children
Published 2023“…Soft voting and hard voting strategies are employed to ensemble these CNN models. The pre-trained DenseNet201 network is used for CNN feature extraction from each task-specific handwritten image data. …”
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131
Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review
Published 2025“…Artificial intelligence (AI), with its ability to process vast amounts of data and detect intricate patterns, offers a solution to the limitations of traditional mammography, including missed diagnoses and false positives. …”
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Convergence and steady-state analysis of the normalized least mean fourth algorithm
Published 2007article -
133
Convergence and steady-state analysis of the normalized least mean fourth algorithm
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134
The buffered work-pool approach for search-tree based optimization algorithms
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conferenceObject -
135
An ant colony optimization algorithm to improve software quality prediction models
Published 2011“…We use an ant colony optimization algorithm in the adaptation process. The approach is validated on stability of classes in object-oriented software systems and can easily be used for any other software quality characteristic. …”
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Autism Detection of MRI Brain Images Using Hybrid Deep CNN With DM-Resnet Classifier
Published 2023“…The preprocessed images are segmented with hybrid Fuzzy C Means (FCM) and Gaussian Mixture Model (GMM) which partition the image into sub groups to make it easier for classification by reducing the complexity. …”
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Unsupervised Deep Learning for Classification Of Bats Calls Using Acoustic Data
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doctoralThesis -
139
Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining
Published 2021“…An integrated web application is developed to mock up the end-to-end process in ecommerce. Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. …”
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140