Hacer SekerciSekerci, Hacer2025-10-062019978-1-7281-2868-9978172812868910.1109/asyu48272.2019.89464452-s2.0-85078334685http://dx.doi.org/10.1109/asyu48272.2019.8946445https://gcris.yasar.edu.tr/handle/123456789/6263https://doi.org/10.1109/asyu48272.2019.8946445https://doi.org/10.1109/ASYU48272.2019.8946445This project aims an economic analysis by estimating the electrical load of an organized industry zone in Izmir Turkey and creating a scenario close to reality. The electrical load of the organizing industry was estimated by artificial neural network method using electricity consumption values. In this method a multilayer perceptron model use for feed-forward algorithm and for a backpropagation training algorithm Levenberg-Marquard algorithm is used. The results obtained by artificial neural network and multiple linear regression method were compared with each other.Turkishinfo:eu-repo/semantics/closedAccessformatting, Electricity consumption, load demand, artificial neural network, power market, short-term forecastingLoad DemandPower MarketElectricity ConsumptionArtificial Neural NetworkShort-Term ForecastingFormattingConference Object