Kaotik zaman serilerinin yapay sinir ağlarıyla kestirimi: Deprem verisi durumu







































































ABSTRACT The purpose of this thesis is how successful chaotic time-series can be predicted after the progress has been made in chaos analysis and artificial intelligence. Since the accurate recordings began in 1971 magnitudes of the earthquakes occured in Marmara region between 1971 and 2005 are utilized to generate the time-series. It is thought that because of the deterministic, dynamic, nonlinear, complex structure of chaos which follows a definite order fits also in earthquakes features, thus it is appropriate for this thesis outline. As an addition, earthquakes which have been tried to be predicted for centuries and have caused huge casualties makes these types of studies meaningful and necessary. In order to acquire this goal there are used some signal processing methods, analysis tools presented after chaos theory, artificial neural networks and some programs for both analysis and prediction. There has been acquired significant success rates from the prediction of the time-series which are chaotic and long enough with minimum level of anomaly. Short-term prediction results has been better than long-term predictions. However, success in prediction of the general trend has not reflected to the prediction of major earthquakes. Keywords: Chaotic Time-series Prediction, Earthquake Prediction, Chaos Theory, Artificial Neural Networks, Time-series Analysis.
xi



11. SAYFAYA BENZER SAYFALAR

Türkiye'nin uzun dönem elektrik yük talep tahmini - Sayfa 4
iv LONG TERM ELECTRIC LOAD DEMAND FORECASTING OF TURKEY Mustafa YAMAÇLI Electric and Electronic Engineering, M.S.Thesis, 2010 Thesis Supervisor: Assistant Professor Bekir MUMYAKMAZ SUMMARY The importance of electrical energy in the age of technology now is increasing day by day. The utilities, which are responsible for the production; transmission and distribution of the electricity, are tryin...
İktisadi zaman serilerinde kaos ve doğrusal olmayan davranışlar - Sayfa 6
ABSTRACT The goal of this thesis is to analyse the nonlinear dynamics in time series which is using in econometric models ; in context the literature, using data which belong to Turkish economy, tested stochastic process in deterministic process and investigated confidence of parameters and argued effect of chaos theory to economics with models. in this thesis using, M1, M2 ve M2Y money supplies...
Terkos gölüne gelen aylık debinin çeşitli metotlarla tahmini - Sayfa 20
hydroelectric dams. Different prediction methods can be used to determine the amount of water in the future. The estimation might be fulfilled either conventionally through various time-series analysis methods such as Autoregressive (AR), Moving Averages (MA) and Autoregressive Moving Averages (ARMA) or through artificial intelligence techniques. During application of hydrology, there might be s...

11. SAYFADAKI ANAHTAR KELIMELER

this
that
which
with
networks
neural


11. SAYFA ICERIGI

ABSTRACT The purpose of this thesis is how successful chaotic time-series can be predicted after the progress has been made in chaos analysis and artificial intelligence. Since the accurate recordings began in 1971 magnitudes of the earthquakes occured in Marmara region between 1971 and 2005 are utilized to generate the time-series. It is thought that because of the deterministic, dynamic, nonlinear, complex structure of chaos which follows a definite order fits also in earthquakes features, thus it is appropriate for this thesis outline. As an addition, earthquakes which have been tried to be predicted for centuries and have caused huge casualties makes these types of studies meaningful and necessary. In order to acquire this goal there are used some signal processing methods, analysis tools presented after chaos theory, artificial neural networks and some programs for both analysis and prediction. There has been acquired significant success rates from the prediction of the time-series which are chaotic and long enough with minimum level of anomaly. Short-term prediction results has been better than long-term predictions. However, success in prediction of the general trend has not reflected to the prediction of major earthquakes. Keywords: Chaotic Time-series Prediction, Earthquake Prediction, Chaos Theory, Artificial Neural Networks, Time-series Analysis.
xi

İlgili Kaynaklar







single.php