Assessment on Agricultural Drought Risk Based on Variable Fuzzy Sets Model

Drought is one of the major natural disasters causing huge agricultural losses annually. Regional agricultural drought risk assessment has great significance for reducing regional disaster and agricultural drought losses. Based on the fuzzy characteristics of agricultural drought risk, variable fuzzy sets model was used for comprehensively assessing agricultural drought risk of Liaoning Province in China. A multi-layers and multi-indices assessment model was estab-lished according to variable fuzzy sets theory, and agricultural drought risk of all 14 prefecture-level cities was respec-tively estimated in terms of dangerousness, vulnerability, exposure and drought-resistibility. By calculating the combi-nation weights of four drought risk factors, agricultural drought risk grade of each city was obtained. Based on the as-sessment results, the spatial distribution maps of agricultural drought risk were drawn. The results shows that eastern cities have lower drought dangerousness than western cities in Liaoning Province totally. Most cities are located in low drought vulnerability region and high drought exposure region. Because of frequent and severe drought since 2000, most cities are located in lower drought-resistibility region. Comprehensive agricultural drought risk presents apparent spatial characteristics, escalating from the east to the west. Drought dangerousness is the most important factor influencing comprehensive agricultural drought risk. Through the spatial distribution maps of drought risk, decision makers could find out drought situation and make decisions on drought resistance conveniently.

Multi-Span and Multiple Relevant Time Series Prediction Based on Neighborhood Rough Set

Rough set theory has been widely researched for time series prediction problems such as rainfall runoff.Accurate forecasting of rainfall runoff is a long standing but still mostly signicant problem for water resource planning and management,reservoir and river regulation.Most research is focused on constructing the better model for improving prediction accuracy.In this paper,a rainfall runoff forecast model based on the variable-precision fuzzy neighborhood rough set(VPFNRS)is constructed to predict Watershed runoff value.Fuzzy neighborhood rough set dene the fuzzy decision of a sample by using the concept of fuzzy neighborhood.The fuzzy neighborhood rough set model with variable-precision can reduce the redundant attributes,and the essential equivalent data can improve the predictive capabilities of model.Meanwhile VFPFNRS can handle the numerical data,while it also deals well with the noise data.In the discussed approach,VPFNRS is used to reduce superuous attributes of the original data,the compact data are employed for predicting the rainfall runoff.The proposed method is examined utilizing data in the Luo River Basin located in Guangdong,China.The prediction accuracy is compared with that of support vector machines and long shortterm memory(LSTM).The experiments show that the method put forward achieves a higher predictive performance.