Search Results - (( developing reduction clustering algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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Parallelization of noise reduction algorithm for seismic data on a beowulf cluster
Published 2010“…This paper presents the parallelization of a sequential noise reduction algorithm for seismic data processing into a parallel 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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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Improved clustering using robust and classical principal component
Published 2017“…k-means algorithm is a popular data clustering algorithm. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…The experimental results showed that the accuracy of the algorithm over the NSL-KDD dataset was 99.72%, with a memory reduction of 10%. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…For floor localisation, the strategy is based on developing the algorithm to determine the floor by utilising fingerprint clustering technique. …”
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Customer mobile behavioral segmentation and analysis in telecom using machine learning
Published 2021“…Lastly, a dashboard was developed using Microsoft Power BI to visualize the clustering results in meaningful analysis. …”
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Data-driven dynamic clustering framework for mitigating the adverse economic impact of Covid-19 lockdown practices
Published 2020“…The findings signify the promises of dynamic clustering for lockdown coverage reduction, reduced economic loss, and military unit deployment reduction, as well as assess potential impact of uncooperative civilians on the contamination rate. …”
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A reliable unicast routing protocol for mobile ad hoc network
Published 2013“…It is also shown that the algorithm contributed greatly to reducing control overhead and although we have extra control packets overhead due to the cluster formation and maintenance, we see 27% to 38% control packets overhead reduction in different network conditions.…”
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Low area Programmable Memory Built-In Self-Test (PMBIST) for small embedded ram cores / Nur Qamarina Mohd Noor
Published 2013“…The proposed clustered FSM-based and microcode-based P-MBIST achieves around 15% and 32% of area reduction respectively. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Energy efficient cluster head distribution in wireless sensor networks
Published 2013“…In general, low energy adaptive cluster hierarchy (LEACH) is one of the most common clustering protocols used to elect the cluster head. …”
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Thesis -
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Such approach is highly dependable on the clustering algorithm parameterization, and is not capable to deal with the normal system’s specification changes. …”
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