Search Results - (( variable estimation mining algorithm ) OR ( java applications cloud algorithm ))
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Expectation maximization clustering algorithm for user modeling in web usage mining system
Published 2009“…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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Securing cloud data system (SCDS) for key exposure using AES algorithm
Published 2021“…After that we use to build securing cloud data system (SCDS) for key exposure using the AES algorithm for encrypting and decrypting our website cloud data and files. …”
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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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Computer remote monitoring via mobile phones using socket programming / Samih Omer Fadlelmola Elkhider
Published 2011“…The approach of the mobile cloud is clearly occurring with web host servers expands thus large number of data around the world stored in huge servers, consumers of mobile devices and small computing devices have high performance expectations usually, therefore mobile cloud computing theorizes that the cloud will soon become a disruptive force in the mobile world, eventually becoming the dominant way in which mobile applications operates. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions
Published 2022“…Descriptive data mining has been widely applied in hydrology as the regionalisation algorithms to identify the statistically homogeneous rainfall regions. …”
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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Identification of debris flow initiation zones using topographic model and airborne laser scanning data
Published 2017“…MARSpline multivariate data mining predictive approach was implemented using morphometric indices and topographical derived parameter as independent variables. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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