Search Results - (( evolution classification model algorithm ) OR ( data replication method algorithm ))
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Dynamic replication algorithm in data grid: Survey
Published 2008“…For improving the performance of file accesses and to ease the sharing amongst distributed collaboration, such a system needs replication services. Data replication is a common method used to improve the performance of data access in distributed systems. …”
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Book Section -
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Enhanced replication strategy with balanced quorum technique and data center selection method in cloud environment
Published 2022“…In order to mitigate the issues, ‘cloud data replication’ is commonly implemented for better data performance and promising business continuity. …”
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Thesis -
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Classification of Immunosignature Using Random Forests for Cancer Diagnosis
Published 2015“…In this work, we will develop a robust classification model that can be utilized in cancer diagnosis using immunofingerprint data. …”
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Proceeding Paper -
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Deep learning detector for pests and plant disease recognition
Published 2020“…Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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Final Year Project / Dissertation / Thesis -
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The motivation of implementation is to make sure the data replication is easy to maintain and cost effective. …”
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Thesis -
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Finally, a new logic mining model namely Y-Type Random 2-Satisfiability Reverse Analysis was proposed, which showed optimal performances in terms of several metrics as compared to the existing classification models. …”
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Thesis -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…However, the learning complexity of classification is increased due to the expansion number of learning model. …”
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Digital economy tax compliance model in Malaysia using machine learning approach
Published 2021“…The experimental results show that the ensemble method can improve the single classification model’s accuracy with the highest classification accuracy of 87.94% compared to the best single classification model. …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Feature selection was used to sort out key features for further classification. News classification into factors affecting stock market turning point was done using Naïve Bayes, Deep Learning, Generalized Linear Model (GLM) and Support Vector Machine (SVM). …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The SVM is a training algorithm for learning classification and regression rules from data [7]. …”
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ios Mobile Malware Deep Analysis And Classification For Social Media And Online Banking Exploitation
Published 2024thesis::master thesis -
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Diagnosis of voice disorders using band energy spectrum in wavelet domain
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Working Paper -
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data
Published 2019“…In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. 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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