Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net

Author

Heng LYU
Xingguo LI
Kai CAO, Singapore Management UniversityFollow

Publication Type

Journal Article

Publication Date

8-2006

Abstract

A two-layer BP neural net model is constructed with four input nodes of TM1, 2, 3, 4 band reflectances, and one output node of suspended solid concentration (SSC) to retrieve SSC of Lake Taihu. The results demonstrated that BP neural net is very fit to quantitatively retrieve water quality of case II water with complex optic characteristic, and has much higher accuracy than the common linear model. A test was made and the results suggest that 13 had relative error (RE)RE of less than 30%, accounting for 81.25% of the total samples.

Discipline

Databases and Information Systems | OS and Networks

Research Areas

Data Science and Engineering

Publication

Geomatics and Information Science of Wuhan University

Volume

31

Issue

8

First Page

683

Last Page

686

Citation

LYU, Heng; LI, Xingguo; and CAO, Kai. Quantitative retrieval of suspended solid concentration in Lake Taihu based on BP neural net. (2006). Geomatics and Information Science of Wuhan University. 31, (8), 683-686.
Available at: https://ink.library.smu.edu.sg/sis_research/6683

Comments

Removed non-SMU affiliated pubs from InK as requested by faculty after he left SMU (Dec 2021)