Improved neural network prediction performances of electricity demand : modifying inputs through clustering

K. A. D. Deshani, Liwan Liyanage Hansen, M. D. T. Attygalle, A. Karunaratne

    Research output: Chapter in Book / Conference PaperConference Paperpeer-review

    Abstract

    ![CDATA[Accurate prediction of electricity demand can bring extensive benefits to any country as the forecast values help the relevant authorities to take decisions regarding electricity generation, transmission and distribution much appropriately. The literature reveals that, when compared to conventional time series techniques, the improved artificial intelligent approaches provide better prediction accuracies. However, the accuracy of predictions using intelligent approaches like neural networks are strongly influenced by the correct selection of inputs and the number of neuro-forecasters used for prediction. This research shows how a cluster analysis performed to group similar day types, could contribute towards selecting a better set of neuro-forecasters in neural networks. Daily total electricity demands for five years were considered for the analysis and each date was assigned to one of the thirteen day-types, in a Sri Lankan context. As a stochastic trend could be seen over the years, prior to performing the k-means clustering, the trend was removed by taking the first difference of the series. Three different clusters were found using Silhouette plots, and thus three neuro-forecasters were used for predictions. This paper illustrates the proposed modified neural network procedure using electricity demand data.]]
    Original languageEnglish
    Title of host publicationSecond International Conference on Computational Science and Engineering (CSE-2014), Dubai, UAE, April 04- 05, 2014
    PublisherAIRCC
    Pages137-147
    Number of pages11
    ISBN (Print)9781921987304
    DOIs
    Publication statusPublished - 2014
    EventInternational Conference of Data Base and Data Mining (DBDM-2014) -
    Duration: 4 Apr 2014 → …

    Conference

    ConferenceInternational Conference of Data Base and Data Mining (DBDM-2014)
    Period4/04/14 → …

    Keywords

    • clustering
    • Silhouette plots

    Fingerprint

    Dive into the research topics of 'Improved neural network prediction performances of electricity demand : modifying inputs through clustering'. Together they form a unique fingerprint.

    Cite this