Search Results - (( java implementation path algorithm ) OR ( knowledge based streaming algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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A study of density-grid based clustering algorithms on data streams
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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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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…Data stream clustering plays an important role in data stream mining for knowledge extraction. …”
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A buffer-based online clustering for evolving data stream
Published 2019“…In this study, we present a fully online density-based clustering algorithm called buffer-based online clustering for evolving data stream (BOCEDS). …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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An adaptive density-based method for clustering evolving data streams / Amineh Amini
Published 2014“…This study proposes a density-based algorithm for clustering evolving data streams. …”
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An Evolutionary Stream Clustering Technique for Outlier Detection
Published 2020“…Nearly all traditional density-based clustering algorithms can be extended to the latest ones for data streams study purposes. …”
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A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube
Published 2023“…TSHC when added to Buffer?based Online Clustering for Evolving Data Stream (BOCEDS) results in a superior evolving data stream clustering algorithm. …”
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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction
Published 2024“…Lately, a fully online buffer-based clustering algorithm for handling evolving data streams (BOCEDS) was developed. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Thus, using neural network-based semi-supervised stream data learning is inadequate due to capture the changes in the distribution and characteristics of various classes of data while avoiding the effect of the outdated stored knowledge in neural networks (NN). …”
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The Security Level Of Two Xored-based A5 Crypto System
Published 2024“…Five (5) statistical tests were used to test the strength of the algorithm. Both of the proposed modified XORed-based A5/1 algorithms successfully passed the five (5) statistical tests.…”
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Hazard identification on fractionation column using rule based expert system
Published 2001“…The process-general knowledge which consists of rule-based expert system is developed from simulation result obtained from HYSIS process simulator. …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Published 2020“…However, using neural network-based semi-supervised stream data learning is not adequate due to the need for capturing quickly the changes in the distribution and characteristics of various classes of the data whilst avoiding the effect of the outdated stored knowledge in neural networks (NN). …”
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A review on big data stream processing applications: contributions, benefits, and limitations
Published 2021“…Many techniques have been proposed and studied to handle big data and give decisions based on off-line batch analysis. Today, we need to make a constructive decision based on online streaming data analysis. …”
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Clustering for binary data sets by using genetic algorithm-incremental K-means
Published 2018“…For the purpose of this research, GA was combined with the Incremental Kmeans (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. …”
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Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb
Published 2019“…Based on the outcome of the analysis, this research proposed a novel framework namely real-time anomaly detection based on big data technologies (RTADBDT), along with supporting implementation algorithms. …”
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