AN ANALYSIS OF THE FISH POPULATIONS BY USING ANN AND WAVELET TECHNIQUES

Yıl 2013, Cilt: 3 Sayı: 1, 469 - 472, 01.06.2013

Guven Ozdemir Ahmet Tokgozlu Yasemin Kahramaner Zafer Aslan

Öz

Air - sea climate, environmental and biological conditions show various differences on several spatio-temporal
scales. Climate change associated with anthropogenic activity and natural global multi-decadal climate variations effects on
air-sea interactions and water surface–atmosphere–biosphere climate system. In the first part of this paper is related with
Artificial Neuro Network analyses for prediction of fish stocks in Marmara and Black Sea. The second part of this study is
based on wavelet analyses and, the results were compared with former wavelet and harmonic analyses to explain seasonal
effects of NAO and ENSO on fish population. The influence of climatic oscillations (based on NAO and ENSO) on monthly
catch rates of fish population such as sea bass, Atlantic bonito,blue fish sea (pomatomus population between 1991-2012) in
Black Sea and Marmara have been analyzed by discrete wavelet transform (DWT) with Meyer and Daubechie's. Wavelet
analysis is an efficient method of time series analysis to study non-stationary data. Wavelet analyses allowed us to quantify
both the pattern of variability in the time series and non-stationary associations between fish population and climatic signals.
Phase analyses were carried out to investigate dependency between the two signals. We reported strong relations between
fish stock and climate series for the 4- and 5-yr periodic modes, i.e. the periodic band of the El Niño Southern Oscillation
signal propagation in the Black Sea and Marmara Sea. These associations were non-stationary, evidenced from 1995 to
2012. It is recognized that other factors in small, meso and large scales may modulate fish stocks beginning from 1995 and
more clearly from 2005

Anahtar Kelimeler

Fish Stocks Management, Climate Signals, ANN, Wavelet Analysis, ENSO, NAO

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