A Prediction of Groundwater Quality Using Grey System Neural Network United Model

被引：2

作者：

Zhu, Changjun ^{[1
,2
]}

Hao, Zhen Chun ^{[2
]}

Ju, Qin ^{[2
]}

机构：

[1] Hebei Univ Engn, Coll Urban Construct, Handan 056038, Peoples R China

[2] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Jiangsu, Peoples R China

来源：

CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年

基金：

中国国家自然科学基金;

关键词：

grey prediction; united grey neural network; groundwater quality; RBF neural network;

D O I：

10.1109/CCDC.2009.5191466

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

At present, classic methods are often used to predict groundwater level, but the result is not ideal. In view of the defect that the grey method can only predict the tendency approximately and artificial neural network can not predict the future tendency really, a new united grey neural network model was developed. This paper mainly analyses the groundwater quality and establishes their mathematical model based on the groundwater monitoring data of one area by united grey neural network method. It predicts various tendency of groundwater quality in this area in the future. Case study indicates that precision of the model is rather high and its popularization significance is better than the other models, and has some practical value when being used in the prediction of groundwater quality analysis..

引用

页码：3216 / +

页数：2

共 50 条

[1] United Grey System-Neural Network Model and its Application in Prediction of Groundwater Level
Zhu, Changjun
Ju, Qin
2009 INTERNATIONAL CONFERENCE ON INDUSTRIAL MECHATRONICS AND AUTOMATION, 2009, : 434 - +
[2] Prediction of Reservior Runoff Using RBF Neural Network-Grey System United Model
Zhang, Juan
Zhu, Changjun
2009 IITA INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS ENGINEERING, PROCEEDINGS, 2009, : 43 - 46
[3] Artificial Neural Network Model for the Prediction of Groundwater Quality
Khudair, Basim H.
Jasim, Mustafa M.
Alsaqqar, Awatif S.
CIVIL ENGINEERING JOURNAL-TEHRAN, 2018, 4 (12): : 2959 - 2970
[4] Prediction of soft ground settlement based on BP neural network-grey system united model
Peng Tao
Yang An-ying
Liang Xing
Yuan Qin
ROCK AND SOIL MECHANICS, 2005, 26 (11) : 1810 - 1814
[5] Integrated model for product quality forecasting system using grey theory and neural network
College of Mechanical and Electronic Engineering, Wenzhou University, Wenzhou 325035, Zhejiang, Guangdong, China
J. Theor. Appl. Inf. Technol., 1 (285-291):
[6] Energy Consumption Forecasting Using United Grey System-Bayesian Regularization Neural Network Model
Hu, Xiaohui
Zhan, Lvjun
Xue, Yun
Liu, Guixi
Fan, Zhe
NATURAL RESOURCES AND SUSTAINABLE DEVELOPMENT II, PTS 1-4, 2012, 524-527 : 3087 - +
[7] Prediction of airport energy consumption using a hybrid grey neural network model
Chen, Jingjie
Xiao, Chen
Qian, Wengao
PROGRESS IN RENEWABLE AND SUSTAINABLE ENERGY, PTS 1 AND 2, 2013, 608-609 : 1252 - 1256
[8] Intelligent Forecasting System Using Grey Model Combined with Neural Network
Yang, Shih-Hung
Chen, Yon-Ping
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2011, 13 (01) : 8 - 15
[9] Network traffic prediction based on Grey Neural Network Integrated model
Liu, Yuan
Cao, Jianhua
2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31, 2008, : 4360 - +
[10] Air Quality Prediction Using a Deep Neural Network Model
Cho, Kyunghak
Lee, Byoung-Young
Kwon, Myeongheum
Kim, Seogcheol
JOURNAL OF KOREAN SOCIETY FOR ATMOSPHERIC ENVIRONMENT, 2019, 35 (02) : 214 - 225

← 1 2 3 4 5 →