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    Clustering Of Electricity Consumption Behavior Dynamics Toward Big Data Applications project in Java Spring Framework with source code and document.

    Java Spring Framework project   Last updated on - January 5, 2020
    Kalaiselvi Elumalai
    Kalaiselvi Elumalai
    php java big data Html Css Javascript Jquery 
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    In this page Clustering Of Electricity Consumption Behavior Dynamics Toward Big Data Applications project is a desktop application which is developed in Java Spring Framework platform. This Java Spring Framework project with tutorial and guide for developing a code. Clustering Of Electricity Consumption Behavior Dynamics Toward Big Data Applications is a open source you can Download zip and edit as per you need. If you want more latest Java Spring Framework projects here. This is simple and basic level small project for learning purpose. Also you can modified this system as per your requriments and develop a perfect advance level project. Zip file containing the source code that can be extracted and then imported into Eclipse. Here Project Source code for BE, BTech, MCA, BCA, Engineering, Bs.CS, IT, Software Engineering, Computer Science students and Devloper. Student can submit in college for final year project. This script developed by Kalaiselvi Elumalai. This desktop application 100% working smooth without any bug. It is developed using java,hadoop and Database hdfs. This software code helpful in academic projects and research paper for final year computer science. You can explore great collection of other Java Spring Framework projects.

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    About Clustering Of Electricity Consumption Behavior Dynamics Toward Big Data Applications project

    project Name

    Clustering Of Electricity Consumption Behavior Dynamics Toward Big Data Applications

    Project Complexityadvanced
    Duration15 Days
    project ID2437
    Developer NameKalaiselvi Elumalai
    Publish DateJanuary 5, 2020
    project PlatformJava Spring Framework
    Programming Languagejava,hadoop
    Front End
    Back End
    IDE ToolEclipse
    Database Integrationhdfs
    project Typedesktop Application
    No of project Download228
    project Total View5397
    Today Trends2
    Current Month Trends80
    Last Month Trends74

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    Features and function of the Clustering Of Electricity Consumption Behavior Dynamics Toward Big Data Applications project

    In a competitive retail market, large volumes of smart meter data provide opportunities for load serving entities (LSEs) to enhance their knowledge of customers' electricity consumption behaviors via load profiling. Instead of focusing on the shape of the load curves, this paper proposes a novel approach for clustering of electricity consumption behavior dynamics, where “dynamics” refer to transitions and relations between consumption behaviors, or rather consumption levels, in adjacent periods. First, for each individual customer, symbolic aggregate approximation (SAX) is performed to reduce the scale of the data set, and time-based Markov model is applied to model the dynamic of electricity consumption, transforming the large data set of load curves to several state transition matrixes. Second, a clustering technique by Fast Search and Find of Density Peaks (CFSFDP) is primarily carried out to obtain the typical dynamics of consumption behavior, with the difference between any two consumption patterns measured by the Kullback–Liebler (K-L) distance, and to classify the customers into several clusters. To tackle the challenges of big data, the CFSFDP technique is integrated into a divide-and-conquer approach toward big data applications. A numerical case verifies the effectiveness of the proposed models and approaches.

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