Akademik Veri Yönetim Sistemi
Geçmişten Günümüze Uluslararası Ergani Sempozyumu, Diyarbakır, Türkiye, 24 Kasım 2022, cilt.1, sa.1, ss.1-10, (Tam Metin Bildiri)
When development projects or moves are considered, obtaining population and electrical energy data for the coming years is considered as one of the important priorities. In our country, both the population and the use of electrical energy are increasing day by day. For this reason, it is important to accurately predict both the population numbers that will increase and the amount of electrical energy to be consumed. This forecast will help to solve problems that may be encountered later on. Such studies are tried to be foreseen with strategic plans and future forecasts. Increasing information and communication technologies and artificial intelligence applications are used more and more in the field of both population and energy estimation. Necessary measures are taken early according to the population estimation Please send your abstracts (in word and pdf) to erganisempozyumu@dicle.edu.tr in the following years. According to the electrical energy forecast for the following years, the networks are built more healthily, faults are detected and resolved better, needs are determined more accurately, interruptions are reduced, forecasts are increased, illegal use is reduced and quality is increased. Classical machine learning and deep learning methods are used to develop a consumption forecasting model by learning different patterns from the data. In this study, ready-made population and annual electricity consumption datasets for Diyarbakir are used. Population data is used for Ergani. Prediction studies are made with machine learning on this data and it is aimed to determine the model that will make the most accurate prediction.
Keywords: Machine Learning, Electricity Consumption Forecast, Population Forecast, Regression, Diyarbakir