%0 Journal Article
%T A Study of Straw Resources Prediction Based on the BP Neural Network: A Case Study of Jiangsu Province<br>基于BP神经网络的江苏省秸秆资源量预测
%A DING Mei
%A JI Chunlei
%A ZOU Biying
%A ZHAO Yanwen
%A <br>丁美
%A 籍春蕾
%A 邹碧莹
%A 赵言文
%J 资源科学
%D 2011
%I 
%X Straw is the largest renewable resource on the Earth. There are about 60-80 million ton of straw resources produced each year in China. It is necessary to predict the amount of straw resources in order to reasonably develop and use straw resources, which would be helpful in easing increasingly serious contradictions among resources shortage, environmental pollution, and economic development. Jiangsu Province, rich in straw resources, is one of the biggest agricultural provinces. The Back-Propagation (BP) neural network method was used to identify and predict a non-linear procedure for resources assessment. First of all, the author systematically analyzed comprehensive utilization and trend factors of straw resources in Jiangsu. Currently, straw resources are primarily utilized as fertilizer, energy, industrial raw materials, animal feed, and base materials. The trend factors of straw resources are the economic output of crops, the ratio, and the collection coefficient of straw. This study examined straw resources in Jiangsu Province using data from statistical yearbooks during the period 1990-2008 and data collected in 2009 combined with the BP neural network method, predicting trends in straw resources with indices of theoretical amount, per capita amount, and per planting area amount. Results show that the relative errors of the established BP neural network model were basically ~5% and the average relative errors were ~ 2%. The prediction of the BP network model showed a higher fitting degree with reference to reality, which is indicative of its good ability to adapt to the data. Using the established BP neural network model, the author predicted the amount of straw resources in the next five years, showing that the theoretical amount would vary between 3.9~4.1 million tons, the per capita amount would vary between 650~900 kg, and per planting area amount would vary between 4.7~5.5 tons per hm2. The development trend of the theoretical estimates would be generally stable in Jiangsu Province while the trends in per capita amount and per planting area amount would decline. The findings of this study would be useful for providing recommendations on development and utilization of straw resources in Jiangsu Province.
%K BP neural network
%K Straw resources
%K Prediction
%K Development proposal
%K Jiangsu Province<br>BP神经网络
%K 秸秆资源
%K 预测
%K 开发建议
%K 江苏省
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=B5EDD921F3D863E289B22F36E70174A7007B5F5E43D63598017D41BB67247657&cid=B47B31F6349F979B&jid=9DEEAF23637E6E9539AD99BE6ABAB2B3&aid=3D120F67FFBE1E3761F9724ED6954ECE&yid=9377ED8094509821&vid=27746BCEEE58E9DC&iid=708DD6B15D2464E8&sid=E485F20140D2A09D&eid=D4F188B92D16530A&journal_id=1007-7588&journal_name=资源科学&referenced_num=0&reference_num=13