Midlands State University Library

FRFI model application in groundwater non-point source pollution evaluation (Record no. 161918)

MARC details
000 -LEADER
fixed length control field 02442nam a22002657a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ZW-GwMSU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230502102331.0
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fixed length control field 230502b |||||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency MSU
Transcribing agency MSU
Description conventions rda
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name MA, Rong
245 ## - TITLE STATEMENT
Title FRFI model application in groundwater non-point source pollution evaluation
Remainder of title a case study in the Luoyang Basin of North Henan province, China
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Verlag
Name of producer, publisher, distributor, manufacturer Springer
Date of production, publication, distribution, manufacture, or copyright notice 2013
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
Content type code txt
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
Media type code n
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Source rdacarrier
Carrier type term volume
Carrier type code nc
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Environmental earh sciences
Volume/sequential designation Volume , number ,
520 ## - SUMMARY, ETC.
Summary, etc. The traditional non-point source (NPS) pollution models mainly focus on the flow path of NPS pollutants and attenuation during the flow. Extensive data set preparation and complex results analysis for these models are the most common problems encountered by the model user. In this study a new model, fuzzy-rough sets and fuzzy inference (FRFI), was introduced to evaluate groundwater NPS pollution. The proposed model involves two steps: the algorithm of fuzzy-rough sets attribute reduction (FRSAR) was applied to yield minimal decision rules from the fuzzy information system (FIS); the fuzzy inference technique was then used to forecast a groundwater synthesis pollution index based on the minimal decision rules. This model was applied in the Luoyang Basin, examining NPS pollution factors and hydrochemical variables data to validate the effectiveness of this model. The results indicate that it is only required to collect five NPS pollution factors or three hydrochemical variables; the groundwater synthesis pollution index can be predicted using the FRFI model. The prediction error is restricted to 2.9–6.1 % and 0.8–1.6 %, respectively. Therefore, the costs of computation and monitoring can be decreased, and the user is not required to prepare massive model parameters for the FRFI model. According to analyze the correlation between NPS pollution factors and hydrochemical variables, prevention measures are provided for treatment of the endemic disease and eutrophication. The FRFI model can be suitable for groundwater NPS pollution evaluation systems.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element non-point source pollution
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element fuzzy-rough sets
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element fuzzy inference technique
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name SHI, Jiansheng
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name LIU, Jichao
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/s12665-012-1712-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Journal Article
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Serial Enumeration / chronology Total Checkouts Full call number Date last seen Price effective from Koha item type Public note
    Library of Congress Classification     Main Library Main Library - Special Collections 02/05/2023 Vol.68 , No.1 (Jan 2013)   GE105 ENV 02/05/2023 02/05/2023 Journal Article For in-house use only