The Analysis and Predictions of Agricultural Drought Trend in Guangdong Province Based on Empirical Mode Decomposition
نویسندگان
چکیده
This paper utilizes the Empirical Mode Decomposition (EMD) to carry on the analysis and the predictions of the agriculture drought trend in Guangdong Province, trying to provide a reference for predictions and forecasting of the agricultural drought trend. After decomposing the anomaly signals of precipitation and undulating signals of agriculture drought condition, four IMF components were obtained respectively. According to Guangdong’s practical situations, the four components can be interpreted to be four fluctuating cycles: light-disaster, medium disaster, heavy disaster, mega disaster. Their quasi-periods are: Light disaster for three years, medium disaster for 5-7 years, heavy disaster for 13-15 years and 26-28 years for mega disaster. To predict the next few years of drought in Guangdong province by the change cycles of medium disaster, heavy disaster and mega disaster, the results are as follows: medium disaster will happen between 2009 and 2011 and probably in 2010; heavy disaster will happen between 2017 and 2019 and probably in 2018; mega disaster will happen between 2030 and 2032, and probably in 2031.
منابع مشابه
A Fault Diagnosis Method for Automaton based on Morphological Component Analysis and Ensemble Empirical Mode Decomposition
In the fault diagnosis of automaton, the vibration signal presents non-stationary and non-periodic, which make it difficult to extract the fault features. To solve this problem, an automaton fault diagnosis method based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD) was proposed. Based on the advantages of the morphological component analysis method i...
متن کاملA Fault Diagnosis Method for Automaton Based on Morphological Component Analysis and Ensemble Empirical Mode Decomposition
In the fault diagnosis of automaton, the vibration signal presents non-stationary and non-periodic, which make it difficult to extract the fault features. To solve this problem, an automaton fault diagnosis method based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD) was proposed. Based on the advantages of the morphological component analysis method i...
متن کاملBlind Voice Separation Based on Empirical Mode Decomposition and Grey Wolf Optimizer Algorithm
Blind voice separation refers to retrieve a set of independent sources combined by an unknown destructive system. The proposed separation procedure is based on processing of the observed sources without having any information about the combinational model or statistics of the source signals. Also, the number of combined sources is usually predefined and it is difficult to estimate based on the ...
متن کاملEstimation of genetic and phenotypic trends for body weight traits of sheep in Guilan province of Iran
The main objective of the present study was to estimate genetic and phenotypic trends for body weight traits in Guilan province sheep. Traits included were birth weight (BW, n=14,549), 3-month weight (3MW, n=13,109) and 6-month weight (6MW, n=10,141). Data and pedigree information used in this study were collected during 1994 to 2011 by the Agricultural Organization of Guilan province in Iran. ...
متن کاملEmpirical Mode Decomposition based Adaptive Filtering for Orthogonal Frequency Division Multiplexing Channel Estimation
This paper presents an empirical mode decomposition (EMD) based adaptive filter (AF) for channel estimation in OFDM system. In this method, length of channel impulse response (CIR) is first approximated using Akaike information criterion (AIC). Then, CIR is estimated using adaptive filter with EMD decomposed IMF of the received OFDM symbol. The correlation and kurtosis measures are used to sel...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2010