RESEMBLANCE OF RAIN FALL IN BANGLADESH WITH CORRELATION DIMENSION AND NEURAL NETWORK LEARNING | Science Publications

American Journal of Applied Sciences

Md. Zakir Hossain¹  Mohd Abdur Rashid¹  Azralmukmin Azmi¹  Abu Nasir Mohammad Enamul Kabir¹  Md. Shahjahan¹  Hussain Muhammad Imran Hasan¹ 

关键词: Rain Fall;    Time Series Analysis;    Complexity;    Neural Network;    Learning and Prediction;   

DOI  :  10.3844/ajassp.2013.1172.1180

学科分类：自然科学（综合）

来源: Science Publications

【 摘 要 】

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.

【 授权许可】

Unknown