In this work a feed-forward NN based NAR model for forecasting time series is presented. The learning rule used to adjust the NN weights is based on the LevenbergMarquardt method. In function of the long or short term stochastic dependence of the time series, we propose an online heuristic law to set the training process and to modify the NN topology. The approach is tested over five time serie...

Synthetic rainfall data has a large number of uses. Specifically, the behaviour of a reservoir under most scenarios can be best understood when evaluated using a large number of synthetic inputs. These synthetic values are all equally probable to occur but many of them may not have appeared in the historical record. Stochastic weather generators produce these synthetic data that were statistica...

Identification of the precise nature and attributes of the time series of climatological data is very important and is usually the first step for water resources planning and management. Such exercise is very important for hydro-climatic extremes. In many instances, a climatic time series is generally not statistically independent but is comprised of patterns of persistence, cycles, trends or s...

The urban centers within northeastern Brazil are mainly influenced by the intense rainfalls, which can occur after long periods of drought, when flood events can be observed during such events. Thus, this paper aims to study the rainfall frequencies in such region through the wavelet transform. An application of wavelet analysis is done with long time series of the total monthly rainfall amount...

in this paper, we propose a new residual analysis method using fourier series transform into fuzzy time series model for improving the forecasting performance. this hybrid model takes advantage of the high predictable power of fuzzy time series model and fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...

The MS Excel file with VBA (Visual Basic for Application) macros named STORAGE (STOchastic RAinfall GEnerator) is introduced herein. a temporal stochastic simulator aiming at generating long and high-resolution rainfall time series, it based on the implementation of Neymann–Scott Rectangular Pulse (NSRP) model. characterized by two innovative aspects. First, its calibration (i.e., parametric es...

Social networks are a valuable source of information to support the detection and monitoring of targeted events, such as rainfall episodes. Since the emergence of Web 2.0, several studies have explored the relationship between social network messages and authoritative data in the context of disaster management. However, these studies fail to address the problem of the temporal validity of socia...

Global position of the monthly mean Anticyclone (AC) time series, 300 mb aloft in the North-East Indian subcontinent over the range 0-45°N,60-130°E, were identified from the NCEP/ NCAR reanalysis dataset (1958-1998). Seasonal averagelatitude and longitude of the AC centres in the time series show two extreme complementary characters; 10.34°N (min), 102.27°E (max)in March and 29.08°N (max), 86.4...

abstractthe understanding of water resources for the purpose of ground and surface water management as two inseparable systems is great importance. in this study by examining the time series of climatic variables (precipitation), hydrological (flow and consume) and the level of water table, the parameters associated with each other and with fluctuating water table can be realized. there was a d...

The relationship between the incidence of norovirus-associated gastroenteritis outbreaks (NAGOs) in Victoria, Australia for the period 2002-2007 and rainfall was examined. Statistical analysis involving the correlation between time series indicated that there was a statistically significant (p < 0.05) correlation between monthly NAGO incidence and average monthly rainfall. There was a lag of an...