The prediction of nonlinear polar motion based on artificial neural network (ann) and fuzzy inference system (fis)

Date

2016-07-08

Author

Kucak, Ramazan Alper
Uluğ, Raşit
Akyılmaz, Orhan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

61
views

0
downloads

URI

https://hdl.handle.net/11511/95059

Conference Name

30 Years of Nonlinear Dynamicsin Geosciences Conference

Collections

Graduate School of Natural and Applied Sciences, Conference / Seminar

Suggestions

OpenMETU
Core

The Prediction of Nonlinear Polar Motion Based on Artificial Neural Network (ANN) and Fuzzy Inference System (FIS) Kuçak, Ramazan Alper ; Uluğ, Raşit; Akyılmaz, Orhan (Springer International Publishing, 2018-01-01) The Earth rotation movement characterizes the situation of the whole Earth movement, as well as the interaction between the Earth’s various layers such as the Earth’s core, mantle, crust, and atmosphere. Prediction of the Earth rotation parameters (ERPs) is important for near real-time applications including navigation, precise positioning, remote sensing and landslide monitoring, etc. In such studies, the analysis of time series is also important for highly accurate and reliable predictions. Therefore, pre...
The application of artificial neural networks for the prediction of water quality of polluted aquifer Gumrah, F; Oz, B; Guler, B; Evin, S (2000-04-01) From hydrocarbon reservoirs, beside of oil and natural gas, the brine is also produced as a waste material, which may be discharged at the surface or re-injected into the ground. When the wastewater is injected into the ground, it may be mixed with fresh water source due to to several reasons. Forecasting the pollutant concentrations by knowing the historical data at several locations on a field has a great importance to take the necessary precautions before the undesired situations are happened.
The estimation of uniaxial compressive strength conversion factor of trona and interbeds from point load tests and numerical modeling Öztürk, Hasan (2017-07-01) The point load (PL) test is generally used for estimation of uniaxial compressive strength (UCS) of rocks because of its economic advantages and simplicity in testing. If the PL index of a specimen is known, the UCS can be estimated using conversion factors. Several conversion factors have been proposed by various researchers and they are dependent upon the rock type. In the literature, conversion factors on different sedimentary, igneous and metamorphic rocks can be found, but no study exists on trona. In ...
The development and application of beam tracing algorithm to predict the acoustics of urban design patterns Şaşmaz, Mehmet; Çalışkan, Mehmet; Department of City and Regional Planning (2003)
The study of compression techniques to materialize transitive closures in deductive database Çınkır, Kaan; Toroslu, İsmail Hakkı; Department of Computer Engineering (1995)

Citation Formats

R. A. Kucak, R. Uluğ, and O. Akyılmaz, “The prediction of nonlinear polar motion based on artificial neural network (ann) and fuzzy inference system (fis),” presented at the 30 Years of Nonlinear Dynamicsin Geosciences Conference, Rodos, Yunanistan, 2016, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/95059.