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Database of Consumption in CAMEROON (2020)

Domain:

environment and energy

Record type:

datasetpaper
Creator:
NZOFraJeaHer
Publisher:
Zenodo
Host:avatar
Many techniques have been used to predict the exact electrical load and reduce losses. Among these techniques, artificial intelligence models (fuzzy logic and ANN) offer greater efficiency compared to conventional techniques (e.g. regression and time series). In this article, a fuzzy logic model is presented for forecasting annual electrical energy consumption in Cameroon. This model is developed according to the evolution of the population, the gross domestic product (GDP) and historical data of the annual consumption of electricity in Cameroon. The development of an effective fuzzy rule base has allowed us to forecast future annual consumption over a ten-year period with a MAPE of 0.011%. A comparison of the results obtained with those of similar models allowed us to conclude that fuzzy logic offers very high accuracy in terms of forecast error. 

Visit

doi.orgzenodo.org

Tags

annual consumption of electrical energy; Fuzzy logic; annual forecast; fuzzy rules; fuzzification; defuzzification; forecasting; volatility

Licenses

Restricted Accessinfo:eu-repo/semantics/restrictedAccess

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