Autor: Tosun, Murat - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: An alternative approach to jerk in motion along a space curve with applications
Autorzy:: Özen, Kahraman Esen
Dündar, Furkan Semih
Tosun, Murat
Powiązania:: https://bibliotekanauki.pl/articles/279665.pdf
Data publikacji:: 2019
Wydawca:: Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:: jerk
kinematics of a particle
plane and space curves
Opis:: Jerk is the time derivative of an acceleration vector and, hence, the third time derivative of the position vector. In this paper, we consider a particle moving in the three dimensional Euclidean space and resolve its jerk vector along the tangential direction, radial direction in the osculating plane and the other radial direction in the rectifying plane. Also, the case for planar motion in space is given as a corollary. Furthermore, motion of an electron under a constant magnetic field and motion of a particle along a logarithmic spiral curve are given as illustrative examples. The aforementioned decomposition is a new contribution to the field and it may be useful in some specific applications that may be considered in the future.
Źródło:: Journal of Theoretical and Applied Mechanics; 2019, 57, 2; 435-444
1429-2955
Pojawia się w:: Journal of Theoretical and Applied Mechanics
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: The Use of Artifi cial Neural Networks (ANN) in Forecasting Housing Prices in Ankara, Turkey
Autorzy:: Kitapci, Olgun
Tosun, Ömür
Tuna, Murat Fatih
Turk, Tarik
Powiązania:: https://bibliotekanauki.pl/articles/540608.pdf
Data publikacji:: 2017
Wydawca:: Uniwersytet Warszawski. Wydawnictwo Naukowe Wydziału Zarządzania
Tematy:: Housing,
artifi cial neural networks,
forecasting,
prices,
Turkey
Opis:: The purpose of this paper is to forecast housing prices in Ankara, Turkey using the artificial neural networks (ANN) approach. The data set was collected from one of the biggest real estate web pages during April 2013. A three-layer (input layer – one hidden layer – output layer) neural network is designed with 15 different inputs to forecast the future housing prices. The proposed model has a success rate of 78%. The results of this paper would help property investors and real estate agents in developing more effective property pricing management in Ankara. We believe that the artifi cial neural networks (ANN) proposed here will serve as a reference for countries that develop artifi cial neural networks (ANN) method-based housing price determination in future. Applying the artifi cial neural networks (ANN) approach for estimation of housing prices is relatively new in the field of housing economics. Moreover, this is the fi rst study that uses the artificial neural networks (ANN) approach for analyzing the housing market in Ankara/Turkey.
Źródło:: Journal of Marketing and Consumer Behaviour in Emerging Markets; 2017, 1(5); 4-14
2449-6634
Pojawia się w:: Journal of Marketing and Consumer Behaviour in Emerging Markets
Dostawca treści:: Biblioteka Nauki

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