Yaşar University

About: Yaşar University is a education organization based out in Izmir, Turkey. It is known for research contribution in the topics: Exergy & Job shop scheduling. The organization has 760 authors who have published 1436 publications receiving 20813 citations. The organization is also known as: Yaşar Üniversitesi.

Estimating the short-term and long-term wind speeds: implementing hybrid models through coupling machine learning and linear time series models

Abstract: Wind speed data are of particular importance in the design and management of wind power projects. In the current study, three types of linear time series models including autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA) were employed to estimate short-term (i.e., daily) and long-term (i.e., monthly) wind speeds. The required data were gathered, respectively, from the Tabriz and Zahedan stations in the northwest and southeast of Iran. The MA models outperformed the AR and ARMA on the both daily and monthly scales. Daily and monthly wind speed values, as a function of lagged wind speed data, were then estimated using two machine learning models of random forests (RF) and multivariate adaptive regression splines (MARS). It was found that the RF and MARS provided similar results; however, RF performed slightly better than the MARS. Finally, the stand-alone time series and machine learning models were coupled to improve the accuracy of the wind speed estimation. Accordingly, the hybrid RF-AR, RF-MA, RF-ARMA, MARS-AR, MARS-MA, and MARS-ARMA models were implemented. It was concluded that, the hybrid models outperformed the stand-alone RF and MARS for both short- and long-term wind speed estimations where, the RF-AR and MARS-AR hybrid models provided the best performances. The hybrid models tested in the present study could be effective alternatives to the stand-alone machine learning-based RF and MARS models for the estimation of wind speed time series.

Can the Youth Bulge Pose a Challenge for Turkey? A Comparative Analysis Based on MENA Region-Driven Factors:

Abstract: One common characteristic of Middle East and North Africa (MENA) countries that have experienced internal conflicts in recent decades is their large youth cohorts, known as the youth bulge. As Turk...

Scalable parallel implementation of migrating birds optimization for the multi-objective task allocation problem

Abstract: As the distributed computing systems have been widely used in many research and industrial areas, the problem of allocating tasks to available processors in the system efficiently has been an important concern Since the problem is proven to be NP-hard, heuristic-based optimization techniques have been proposed to solve the task allocation problem Particularly, the current cloud-based systems have been grown massively requiring multiple features like lower cost, higher reliability, and higher throughput; therefore, the problem has become more challenging and approximate methods have gained more importance Migrating birds optimization (MBO) algorithm offers successful solutions, especially for quadratic assignment problems Inspired by the movement of the birds, it exhibits good results by its population-based approach Since the algorithm needs to deal with many individuals in the population, and the neighbor solution generation phase takes substantial time for large problem instances, we need parallelism to have execution time improvements and make the algorithm practical for large-scale problems In this work, we propose a scalable parallel implementation of the MBO algorithm, PMBO, for the multi-objective task allocation problem We redesigned the implementation of the MBO algorithm so that its computationally heavy independent tasks are executed concurrently in separate threads We compare our implementation with three parallel island-based approaches The experimental results demonstrate that our implementation exhibits substantial solution quality improvements for difficult problem instances as the computing resources, namely parallelism, increase Our scalability analysis also presents that higher parallelism levels offer larger solution improvement for the PMBO over the island-based parallel implementations on very hard problem instances

İki̇li̇ ve çok tarafli anlaşmalarin türki̇ye'ni̇n i̇hracati üzeri̇ndeki̇ etki̇si̇ effect of bilateral and multilateral agreements on turkey's export

Abstract: OZET: Bu calismada Turkiye'nin tarafi oldugu ikili ve cok tarafli ekonomik ve ticari anlasmalarin, Turkiye'nin 113 ulkeye olan ihracati uzerinde etkisi olup olmadigi 1996-2006 yillari arasi verileri ile Genel Cekim Modeli cercevesinde test edilmistir. Sonuc olarak imzalanan ikili anlasmalarin Turkiye'nin ihracati uzerinde istatistiksel olarak anlamli bir etkisi bulunmazken, Gumruk Birligi Anlasmasinin disinda Turkiye'nin tarafi oldugu cok tarafli anlasmalarin Turkiye'nin ihracati uzerinde istatistiksel olarak anlamli pozitif etkisi oldugu sonucuna varilmistir. Anahtar Kelimeler: Ihracat; Genel Cekim Modeli; Uluslararasi Anlasmalar; Panel Veri Analizi ABSTRACT: Whether bilateral and multilateral trade and economic agreements has effect on Turkey's export to 113 countries is tested between 1996-2006 and within Gravity Model framework. Results show that while bilateral agreements has no statistically significant effect on Turkey's export, except for Customs Union, multilateral agreements have statistically significant and positive effect on Turkey's export.

Design and implementation of chaotic system based robust delta robot for blending graphene nanoplatelets

Abstract: In this paper, a new blending method for Graphene nanoplatelets was developed. A chaotic system based robust delta robot was designed. Both the speed of the mixer motor and position of the propeller were chaotically changed. Performance of the systems was evaluated by a material analysis method. The results showed that the proposed method has a better performance than statically mounted mixers.