Adem Akpınar

TL;DR: In this paper, the authors deal with the modeling of the energy consumption in Turkey in order to forecast future projections based on socioeconomic and demographic variables (GDP, population, import and export amounts, and employment) using ANN and regression analyses.

TL;DR: In this paper, the existence and variability of wave energy resource potential of the Black Sea based on 15-year hindcast data is described in detail, and the hindcasts of wave parameters were carried out by using the third generation wave prediction model (Simulated WAves Nearshore - SWAN), which is one of the most popular numerical wave models and has been widely used for estimating ocean waves.

TL;DR: In this article, the SWAN model has been applied in a third generation and non-stationary mode with spherical coordinates to study the wind-wave climate and wave energy potential in the region, and its verification.

TL;DR: In this article, the authors applied the ANN (artificial neural network) model with the TLBO (teaching-learning-based optimization) algorithm to estimate energy consumption in Turkey.

TL;DR: In this paper, the impact of using different wind field products on the performance of the third generation wave model SWAN in the Black Sea and its capability for predicting both normal and extreme wave conditions during 1996 was evaluated.