Search Results - (( data replication testing algorithm ) OR ( parallel classification clustering algorithm ))
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Development of a parallel clustering of bilingual corpora based on reduced terms
Published 2015“…The quality of clustering bilingual text documents is highly influenced by the quality of the bag-of-word presentation of Malay text articles presented to the clustering algorithm. …”
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Design and analysis of management platform based on financial big data
Published 2023“…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
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Random sampling method of large-scale graph data classification
Published 2024“…Since the data blocks in this model are much smaller than the entire data set, it is more efficient to analyze them on a standalone small machine, and multiple data blocks can be analyzed on multiple nodes of the cluster in parallel. Finally, we classified the graphs of data blocks using the SVM algorithm. …”
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A novel deadlock detection algorithm for neighbour replication on grid environment
Published 2012“…The aim of this research is to handle the deadlock problem in NRG to preserve the consistency of data and increase the throughput. The NRGDD simulation model has been developed to test the algorithm on NRG. …”
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Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman
Published 2021“…Each technique was replicated, trained and tested accordingly. M4 competition dataset was used in this research, with 100,000 time series data and multiple data frequency, which is enough to replicate the real-world situation. …”
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Finite element modeling and updating for dynamic study of exhaust structure
Published 2020“…Hence, this paper is carried out to reduce the discrepancies between numerical prediction results with measured test data on FE model of exhaust structure by implementing FE model updating using SOL200 algorithm. …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data
Published 2019“…Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.…”
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…Additionally, the Wilcoxon rank test was used to perform the significance analysis between the proposed SCSOKNN method and six other algorithms for a p-value less than 5.00E-02. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…A new method to initialize the clustering centers was also proposed to improve the results of segmentation. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa
Published 2018“…A new method to initialize the clustering centers was also proposed to improve the results of segmentation. …”
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Securing IoT networks using machine learning-resistant physical unclonable functions (PUFs) on edge devices
Published 2026“…The NIST statistical test suite was applied to the CRP data of the RO PUF to evaluate its randomness quality. …”
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A self-adaptive agent-based simulation modelling framework for dynamic processes
Published 2023“…Case studies for simulating dynamic processes of new student registration (administrative domain), transport request (transportation domain) and crime investigation (security domain) with real data collected through interview and document reviews to test the proposed idea. …”
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Finger-Vein Biometric Identification Using Convolutional Neural Network
Published 2016“…An identification rate of 100.00% is achieved, with an 80/20 percent ratio for separation of training and test samples, respectively. An additional number of subjects have also been tested, in which for 81 subjects an accuracy of 99.38% is achieved.…”
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Access control model based on trust, purpose, and role in materialized view for privacy protection
Published 2019“…This study focuses on data privacy protection in materialized view. Materialized view is a replica of a table which is created in a very large system where data are replicated from the master tables. …”
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Performance Prediction of Compulsory Subjects and Recommendation of Subject Options for China’s New College Entrance Examination
Published 2026“…The dataset was split 80/20 for training and testing. Four machine learning algorithms: Naïve Bayes (NB), Decision Tree (DT), Artificial Neural Networks (ANNs), and Support Vector Machines (SVMs) were evaluated using accuracy, precision, recall, F1 score, and Matthews Correlation Coefficient (MCC). …”
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Mobile Crowd Steering Evacuation Model via Agent Based Simulation by Applying the Social Force Model
Published 2025“…In addition, simulated data can overcome the lack of genuine datasets for specific crowd situations. …”
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Medical identity theft in telemedicine: solving the privacy and security issues
Published 2015“…Hence, the proposed algorithm enables quick and excellent detection capability of any modification done to the medical images.…”
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Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property
Published 2013“…Datasets of transacted terrace houses over the period 1999-2009 from Selangor, Malaysia were obtained and geocoded for analyses using cadastral and topographic maps and online mapping services. A complete data analysis was carried out on the datasets. Furthermore, various spatial, temporal and spatio-temporal neighbourhood and weighting schemes, optimization algorithms and lag and error modelling scenarios were created and tested with the data. …”
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