Midlands State University Library

Chlorophyll a simulation in a Lake ecosystem using a model with wavelet analysis and artificial neural network (Record no. 162444)

MARC details
000 -LEADER
fixed length control field 02186nam a22002897a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ZW-GwMSU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230530113244.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230530b |||||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency MSU
Transcribing agency MSU
Description conventions rda
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name WANG, Fei
245 ## - TITLE STATEMENT
Title Chlorophyll a simulation in a Lake ecosystem using a model with wavelet analysis and artificial neural network
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New York
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
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
Carrier type code nc
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Environmental Management
Volume/sequential designation Volume , number ,
520 ## - SUMMARY, ETC.
Summary, etc. Accurate and reliable forecasting is important for the sustainable management of ecosystems. Chlorophyll a (Chl a) simulation and forecasting can provide early warning information and enable managers to make appropriate decisions for protecting lake ecosystems. In this study, we proposed a method for Chl a simulation in a lake that coupled the wavelet analysis and the artificial neural networks (WA–ANN). The proposed method had the advantage of data preprocessing, which reduced noise and managed nonstationary data. Fourteen variables were included in the developed and validated model, relating to hydrologic, ecological and meteorologic time series data from January 2000 to December 2009 at the Lake Baiyangdian study area, North China. The performance of the proposed WA–ANN model for monthly Chl a simulation in the lake ecosystem was compared with a multiple stepwise linear regression (MSLR) model, an autoregressive integrated moving average (ARIMA) model and a regular ANN model. The results showed that the WA-ANN model was suitable for Chl a simulation providing a more accurate performance than the MSLR, ARIMA, and ANN models. We recommend that the proposed method be widely applied to further facilitate the development and implementation of lake ecosystem management.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element chlorophyll a simulation
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element wavelet transformation
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element artificial neural networks
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name WANG, Xuan
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name CHEN, Bin
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name ZHAO, Ying
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name YANG, Zhifeng
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/s00267-013-0029-5
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 30/05/2023 Vol.51 , No.5 (May 2013)   GE300 ENV 30/05/2023 30/05/2023 Journal Article For In House Use Only