Search Results - (( java application optimized algorithm ) OR ( knowledge detection clustering algorithm ))
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An Evolutionary Stream Clustering Technique for Outlier Detection
Published 2020“…Later, this algorithm will be extended to optimize the model in detecting outlier on data streams. …”
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Unsupervised Anomaly Detection with Unlabeled Data Using Clustering
Published 2005“…We present a clustering-based intrusion detection algorithm, unsupervised anomaly detection, which trains on unlabeled data in order to detect new intrusions. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…These results prove the superiority of BOCEDS algorithm over the existing clustering algorithms. …”
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On density-based data streams clustering algorithms: A survey
Published 2017“…Recently, a lot of density-based clustering algorithms are extended for data streams. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…The system trains the NN on previously labelled data, and its knowledge is used to calculate the core online-offline clustering block error. …”
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A buffer-based online clustering for evolving data stream
Published 2019“…The sensitivity of clustering parameters is also measured. The proposed algorithm is then applied to real-world weather data streams to demonstrate its capability to detect changes in data stream and discover arbitrarily shaped clusters. …”
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar
Published 2016“…This unsupervised learning usually leads to undirected knowledge discovery. The cluster detection algorithm searches for clusters of data which are similar to one another by using similarity measures. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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KM-NEU: an efficient hybrid approach for intrusion detection system
Published 2014“…The K-means clustering algorithm is engaged for grouping analogous nodes into k clusters using the similarity measures such as attack and non-attack, whereas the Neural Network Multi-Layer Perceptron classifies the clustered data into detail categories such as R2L, Probing, DoS, U2R and Normal. …”
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An improved hybrid learning approach for better anomaly detection
Published 2011“…In recent years, data mining approach for intrusion detection have been proposed and used such as neural networks, clustering, genetic algorithms, decision trees, and support vector machines. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Data stream clustering by divide and conquer approach based on vector model
Published 2016“…The continuous effort on data stream clustering method has one common goal which is to achieve an accurate clustering algorithm. …”
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Parameter estimation of K-distributed sea clutter based on fuzzy inference and Gustafson-Kessel clustering
Published 2011“…The algorithm also improves the calculations of shape and width of membership functions by means of clustering in order to improve the accuracy. …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…In response to the current issues of poor real-time performance, high computational costs, and excessive memory usage of object detection algorithms based on deep convolutional neural networks in embedded devices, a method for improving deep convolutional neural networks based on model compression and knowledge distillation is proposed. …”
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Ant colony optimization algorithm for load balancing in grid computing
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