The energy demand estimation commands great importance for both developing and developed countries in terms of the economy and country resources. In this study, the differential evolution algorithm (DE) was used to forecast the long-term energy demand in Turkey. In addition to being employed for solving regular optimization problems, DE is also a global, meta-heuristic algorithm that enables fast, reliable and operative stochastic searches based on population. Considering the correlation between the increase in certain economic indicators in Turkey and the increase of energy consumption, two equations were used-one applying the linear form and the other the quadratic form. Turkey's long-term energy demand from 2012 to 2031 was estimated through the DE method in three different scenarios and in terms of the gross domestic product, import, export and population. To prove the success of the DE method in addressing the energy demand problem, the DE method was compared to other methods found in the literature. Results showed that the proposed DE method was more successful than the other methods. Furthermore, the future projections of energy demand obtained using the proposed method were compared to the indicators of energy demand estimated and observed by the Ministry of Energy and Natural Resources.

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Wind turbines -which are significant in terms of clean energy production globally -are environmentally friendly, consistent and economical systems. Wind turbines, due to developing technology, have become one of the most widely used renewable energy resources, and every country has worked to satisfy its electricity demands with the help of wind energy. As the importance of wind energy increases all around the world, the importance of wind turbine placement also rises. In this study, the aim was to position wind turbines over a certain area of a wind farm to obtain maximum turbine power with minimum investment cost, thereby achieving the highest power efficiency. The experimental studies were conducted over a 2×2 km area; this area was divided into a 10×10 grid, and a 20×20 grid for more efficient placement. Because these operations occurred in a binary search space, Invasive Weed Optimization (IWO) -normally used to solve unceasing optimization problems -was used in this study by obtaining fourteen different binary Invasive Weed Optimization (BIWO1 to BIWO14) algorithms with the help of ten different transfer functions (four from the sshaped family, four from the v-shaped family, two based on modulo 2, ceil, ceil-round, ceil-floor and round-floor). The proposed method was compared with other studies carried out in the binary search space found in published literature. As a result, it was seen that the proposed algorithm was an efficient algorithm for solving the problem of wind turbine placement to achieve an optimal placement.

Öz Günümüzde, bilişim teknolojilerinin gelişmesiyle birlikte haberleşme ve bilgi güvenliğinin sağlanması için şifrelemenin önemi giderek artmaktadır. Özellikle internet teknolojisinin gelişmesiyle birlikte veri güvenliğinin sağlanması için birçok şifreleme algoritmaları kullanılmaktadır. Şifreleme algoritmaları simetrik ve asimetrik olmak üzere iki başlık altında incelenmektedir. Bu çalışmada ise simetrik ve asimetrik şifreleme algoritmalarının genel özelliklerine yer vermekle birlikte literatürde önemli bir yere sahip asimetrik şifreleme algoritmalarından biri olan RSA algoritması incelenerek RSA algoritmasının şifreleme yöntemleri üzerindeki etkisi analiz edilmiştir. RSA algoritmasının yapısı, genel özellikleri, avantajı ve dezavantajı hakkında bilgilere yer verilmiştir.