基于人工神经网络的山区生态安全预测研究——以石家庄区西部山区为例

Li Yan-qing, Huang Zhi-ying, Ge Jing-feng, Jia Qiang, Chen Jing, Fan Yu-zhong
{"title":"基于人工神经网络的山区生态安全预测研究——以石家庄区西部山区为例","authors":"Li Yan-qing, Huang Zhi-ying, Ge Jing-feng, Jia Qiang, Chen Jing, Fan Yu-zhong","doi":"10.1109/CINC.2010.5643781","DOIUrl":null,"url":null,"abstract":"Ecological environment security had aroused more and more attentions, and became the focus of human society. The thesis took western mountain areas in Shijiazhuang District for study area, established ecological security prediction indexes under the model of Pressure-State-Response(PSR), and predicted standardized value of each index by using artificial neural network model, then predicted the development trend of ecological security condition in the next 9 years through ecological security calculation and trend curve. Results were as follows: the overall ecological security degree would present rising trend, it would be “better” state in 2007∼2015, and the maximum value would be 0.6940 in 2015, increased by 74.96% than that of 1996 and 21.58% than that of 2006. However, the ecological security degrees would be less than 0.8 each year, showing that the regional ecological environment problems were not completely solved, should take further measures to protect the ecological environment.","PeriodicalId":227004,"journal":{"name":"2010 Second International Conference on Computational Intelligence and Natural Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on ecological security prediction in mountain areas based on the artificial neural network —Taken western mountain areas in Shijiazhuang District for example\",\"authors\":\"Li Yan-qing, Huang Zhi-ying, Ge Jing-feng, Jia Qiang, Chen Jing, Fan Yu-zhong\",\"doi\":\"10.1109/CINC.2010.5643781\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ecological environment security had aroused more and more attentions, and became the focus of human society. The thesis took western mountain areas in Shijiazhuang District for study area, established ecological security prediction indexes under the model of Pressure-State-Response(PSR), and predicted standardized value of each index by using artificial neural network model, then predicted the development trend of ecological security condition in the next 9 years through ecological security calculation and trend curve. Results were as follows: the overall ecological security degree would present rising trend, it would be “better” state in 2007∼2015, and the maximum value would be 0.6940 in 2015, increased by 74.96% than that of 1996 and 21.58% than that of 2006. However, the ecological security degrees would be less than 0.8 each year, showing that the regional ecological environment problems were not completely solved, should take further measures to protect the ecological environment.\",\"PeriodicalId\":227004,\"journal\":{\"name\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Second International Conference on Computational Intelligence and Natural Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINC.2010.5643781\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on Computational Intelligence and Natural Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINC.2010.5643781","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

生态环境安全日益引起人们的重视,成为人类社会关注的焦点。本文以石家庄区西部山区为研究区,建立压力-状态-响应(PSR)模型下的生态安全预测指标,利用人工神经网络模型预测各指标的标准化值,通过生态安全计算和趋势曲线预测未来9年生态安全状况的发展趋势。结果表明:总体生态安全程度呈上升趋势,2007 ~ 2015年处于“较好”状态,2015年最大值为0.6940,比1996年和2006年分别增长74.96%和21.58%;然而,生态安全度每年都低于0.8,表明区域生态环境问题并未完全解决,应采取进一步措施保护生态环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Research on ecological security prediction in mountain areas based on the artificial neural network —Taken western mountain areas in Shijiazhuang District for example
Ecological environment security had aroused more and more attentions, and became the focus of human society. The thesis took western mountain areas in Shijiazhuang District for study area, established ecological security prediction indexes under the model of Pressure-State-Response(PSR), and predicted standardized value of each index by using artificial neural network model, then predicted the development trend of ecological security condition in the next 9 years through ecological security calculation and trend curve. Results were as follows: the overall ecological security degree would present rising trend, it would be “better” state in 2007∼2015, and the maximum value would be 0.6940 in 2015, increased by 74.96% than that of 1996 and 21.58% than that of 2006. However, the ecological security degrees would be less than 0.8 each year, showing that the regional ecological environment problems were not completely solved, should take further measures to protect the ecological environment.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Evolutionary design of ANN structure using genetic algorithm Performance analysis of spread spectrum communication system in fading enviornment and Interference Comprehensive evaluation of forest industries based on rough sets and artificial neural network A new descent algorithm with curve search rule for unconstrained minimization A multi-agent simulation for intelligence economy
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1