Abstract
We studied behaviour pattern of anchovy (Engraulis japonicus) shoal by a method of shoal echo integration and tested species identification by a method of artificial neural network using the acoustic data collected in the East China Sea in March 1994 and in the southern coastal waters of the East Sea of Korea in March 1995. Between areas, frequency distribution of 10 shoal descriptors was different, which showed characteristics of shoal behaviour in size, bathymetric position and acoustic strength. The range and mean of shoal size distribution in length and height was wider and bigger in the southern coastal waters of the East Sea than in the East China Sea. Relative shoal size of China Sea. Fractal dimension of shoal was almost same in both areas. Mean volume reverbration index of shoal was 3 dB higher in the southern coastal waters of the East Sea than in the East China Sea. The depth layer of shoal distribution was related to bottom depth in the southern coastal waters of the East Sea, while it was between near surface and central layer in the East China Sea. Principal component analysis of shoal descriptors showed the correlation between shoal size and acoustic strength which was higher in the southern coastal waters of the East Sea, than in the East China Sea. Correlation was also found among the bathymetric positions of shoal to some degree higher in the southern coastal waters of the East Sea than in the East China Sea. The anchovy shoal of two areas was identified by artificial neural network. The contribution factor index (Cio) of the shoal descriptors between two areas were almost identical feature. The shoal volume reverberation index (Rv) was showed the highest contribution to the species identification, while shoal length and shoal height showed relatively high negative contribution to the species identification.