Search Results - (((( pattern clustering algorithm ) OR ( pattern bat algorithm ))) OR ( deep learning algorithm ))
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Meta-heuristics and deep learning for energy applications: Review and open research challenges (2018?2023)
Published 2025Subjects:Review -
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A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications
Published 2022“…Without human input, these algorithms discover patterns or groupings in the data. …”
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Enhancement of text representation for Indonesian document summarization with deep sequential pattern mining
Published 2023“…Second, the proposed SPM approach is combined with Deep Belief Network (DBN), called DeepSPM, based on the unsupervised Deep Learning method. …”
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4
Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques
Published 2024“…Clustering algorithms such as K-means, spectral clustering, and the Gaussian Mixer Model have been tested with manifold learning approaches for adaptive feature selection. …”
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DC-GAN-based synthetic X-ray images augmentation for increasing the performance of EfficientNet for COVID-19 detection
Published 2021“…Currently, many deep learning models are being used to classify COVID‐19 and normal cases from chest X‐rays. …”
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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Monograph -
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A Data Mining Approach to Enhancing Birth and Death Registration Processes
Published 2025“…Future research may explorer the integration of deep learning models for further automate the registration process and enhance predictive accuracy.…”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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10
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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Bat algorithm for rough set attribute reduction
Published 2023“…In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. …”
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Naive bayes-guided bat algorithm for feature selection.
Published 2013“…Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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13
Nature inspired meta-heuristic algorithms for deep learning: recent progress and novel perspective
Published 2019“…The deep learning architectures not exploit by the nature inspired algorithms for optimization are unveiled. …”
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Proceeding Paper -
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Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
Published 2018“…However, deep learning algorithms, such as deep belief networks showed promising results in many domains, especially in image processing. …”
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15
Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
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Citation Index Journal -
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Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor
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17
A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market
Published 2023“…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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The Effect Of Linkages In The Hierarchical Clustering Of Auto-Regressive Algorithm For Defect Identification In Heat Exchanger Tubes
Published 2019“…The clustering results from the ‘ward’ linkages were represented via a dendrogram showing the hidden pattern between clusters. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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Performance of correlational filtering and deep learning based single target tracking algorithms / ZhongMing Liao and Azlan Ismail
Published 2023“…Therefore, reviewing the visual target tracking algorithms based on deep learning from different perspectives is important. …”
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