Forecasting the primary energy demand in Turkey and analysis of cyclic patterns

By V. Ediger, H. Tatlıdil. 2002

183 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/6f74cb3b1beae8fd773dc770082f736634e3951e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Alper Ünler
2. Zafer Dilaver
3. L. Hunt
4. Erkan Erdogdu
5. S. Akar
6. Halim Ceylan
7. Soner Haldenbilen
8. Ozgur Baskan

In Renewable Energy, Sustainability and the Environment

1. Zafer Dilaver
2. Erkan Erdogdu
3. L. Hunt
4. Alper Ünler
5. S. Akar
6. Murat Kankal
7. A. Akpınar
8. Murat Ihsan Kömürcü

Citations in the corpus

• Modelling and forecasting Turkish residential electricity demand (2011, methodology): “The MENR utilized different models in order to determine energy demand functions and to make future projections.”
• Electricity Demand Analysis Using Cointegration and ARIMA Modelling: A case study of Turkey (2007, background): “The papers written in this area include that of Engle et al. (1989); Hunt and Manning (1989), Hunt and Lynk (1992), Bentzen and Engsted (1993, 2001), Fouquet et al. (1993), Hunt and Witt (1995); and Beenstock and Goldin (1999).”
• Natural gas demand in Turkey (2009, unknown): “Finally, State Institute of Statistics (SIS) and SPO have developed some mathematical models [20].”
• Improvement of energy demand forecasts using swarm intelligence: The case of Turkey with projections to 2025 (2008, background): “Deviations from realization in the MAED applications between the years 1986 and 2000 (Ediger and Tatlidil, 2002).”
• ARIMA forecasting of primary energy demand by fuel in Turkey (2007, methodology): “Since Ediger and Tatlıdil (2002), various techniques have been applied in energy demand forecasting of Turkey, such as degree-day, linear and multivariate regression, autoregression, genetic algorithm, and artificial neural network (Table 1).”
• Energy Access Scenarios to 2030 for the Power Sector in Sub-Saharan Africa (2012, unknown): “13 See e.g., Abraham and Nath, 2001; Adams and Shachmurove, 2008; Basu et al., 1991; Ediger and Tatlidil, 2002; García-Ascanio and Maté, 2010; Pappas et al., 2008; Price and Sharp, 1985 and Ünler, 2008.”
• Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables (2011, background): “Ediger and Tatlidil [38] proposed an approach that uses the analysis of cyclic patterns in historical curves to forecast the primary energy demand in Turkey.”
• Industrial electricity demand for Turkey: A structural time series analysis (2011, methodology): “Turkish Industrial Energy Demand Page 8 of 35 Causality Studies: The focus is whether statistical causality (usually defined as Granger Causality) between energy consumption and economic variables, such as GDP exists.”