Application of gene expression programming for seasonal rainfall forecasting in Western Australia using potential climate indices

نویسندگان

چکیده

Abstract This study presents the development of rainfall forecast models using potential climate indices for Kimberley region Western Australia, 100 years and data four stations. Three different modeling techniques: multiple linear regression (MLR), autoregressive moving average with exogenous input (ARIMAX), gene-expression programming (GEP) were applied to develop prediction models. Preliminary analysis suggests that Tropical Indian Ocean (WTIO) Southern Oscillation Index (SOI) have significant impacts on summer generation region. Developed models’ performances evaluated Pearson correlation coefficient ( $$r$$ r ), root mean square error $$RMSE$$ RMSE absolute $$(MAE)$$ ( M A E ) , Nash–Sutcliffe efficiency $$(NSE)$$ N S refined Willmot index agreement $${d}_{r}$$ d ). It is found GEP model exclusively outperforms other two alternatives. In calibration period, resulted in a (r) values ranging from 0.76 0.85, which are significantly higher than achieved MLR (0.32 0.44) ARIMAX (0.53 0.83) models, while validation ranged 0.74 0.87 GEP, 0.35 0.51 0.59 0.77 Considering statistical statistics it can be concluded best representative seasonal forecasting

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Forecasting copper price using gene expression programming

Forecasting the prices of metals is important in many aspects of economics. Metal prices are also vital variables in financial models for revenue evaluation, which forms the basis of an effective payment regime using resource policymakers. According to the severe changes of the metal prices in the recent years, the classic estimation methods cannot correctly estimate the volatility. In order to...

متن کامل

A comparison of two seasonal rainfall forecasting systems for Australia

There are at present two major governmental seasonal rainfall forecasting programs in Australia. The first of these programs is run by the Australian Government through the Bureau of Meteorology and commenced in 1989. The second is run by the Queensland Government (QG) through its Department of Environment and Resource Management (and its predecessors) and commenced in 1994. Both programs issue...

متن کامل

Improvement of Gene Expression Programming Model Performance using Wavelet Transform for the Estimation of Long-Term Rainfall in Rasht City

Rainfall may be considered as the most important source of drinking water and watering land in different areas all over the world. Therefore, simulation and estimation of the hydrological phenomenon is of paramount importance. In this study, for the first time, the long-term rainfall in Rasht city was simulated using an optimum hybrid artificial intelligence (AI) model over a 62 year period fro...

متن کامل

Optimization of Gene Expression Programming Model using Wavelet Transform for Simulating Long-term Rainfall in Anzali City

Due to drought and climate change, estimation and prediction of rainfall is quite important in various areas all over the world. In this study, a novel artificial intelligence (AI) technique (WGEP) was developed to model long-term rainfall (67 years period) in Anzali city for the first time. This model was combined using Wavelet Transform (WT) and Gene Expression Programming (GEP) model. Firstl...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Climate Dynamics

سال: 2023

ISSN: ['0930-7575', '1432-0894']

DOI: https://doi.org/10.1007/s00382-023-06764-0