TY  - JOUR
AU  - Kabir, Abu Nasir Mohammad Enamul 
AU  - Hasan, Hussain Muhammad Imran 
AU  - Rashid, Mohd Abdur 
AU  - Azmi, Azralmukmin 
AU  - Hossain, Md. Zakir 
AU  - Shahjahan, Md. 
PY  - 2013
TI  - Resemblance of Rain Fall in Bangladesh with Correlation Dimension and Neural Network Learning
JF  - American Journal of Applied Sciences
VL  - 10
IS  - 10
DO  - 10.3844/ajassp.2013.1172.1180
UR  - https://thescipub.com/abstract/ajassp.2013.1172.1180
AB  - Rain fall and Temperature are undoubtedly two important factors that balance water in the environment. Adequate study of the rain behavior helps to forecast it. The time series obtained from different stations of the country throughout the several years are collected and analyzed. The dynamics of rain fall time series is analyzed with Correlation Dimension (CD) to characterize the several zones of Bangladesh. In addition a Neural Network (NN) predictor model was designed to realize complexity of rain fall. We found the interesting similarity between CD and NN predictor. The findings are useful in explaining why several zones show behavioral regularity and change.