Skip to content
naulon
Not checkedNot checked for notices yet.

Electrical energy demand forecasting model using artificial neural network: A case study of Lagos State Nigeria

Khadeejah Adebisi Abdulsalam, Olubayo Moses Babatunde

International Journal of Data and Network Science · 2019

doi:10.5267/j.ijdns.2019.5.002 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Electrical Energy is an essential commodity which significantly contributes to the economic development of any country. Many non-linear factors contribute to the final output of electrical energy demand. In order to efficiently predict electrical energy demand, many time-series analysis and multivariate techniques have been suggested. In order for these methods to accurately work, an enormous quantity of historical dataset is essential which sometimes are not available, inadequate and inaccurate. To overcome some of these challenges, this paper presents an Artificial Neural Network based method for Electrical Energy Demand Forecasting using a case study of Lagos state, Nigeria. The predicted values are compared with actual values to estimate the performance of the proposed technique.

Abstract licence: CC BY

References1

    1 more reference, whose wording the paper’s licence keeps private.

    Reads

    Read by people on this page

    None yet.

    Checked or read by AI through naulon

    None yet.

    A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

    Are you an author?

    Is this your paper?

    Claim it to add your note and be paid when agents cite it. Free.