Title :
Application of neural networks to fluorescent diagnostics of organic pollution in natural waters
Author :
Orlov, Yuri V. ; Persiantsev, Igor G. ; Rebrik, Sergey P.
Author_Institution :
Dept. of Microelectron., Moscow State Univ., Russia
Abstract :
A neural net has been used to build a sea water express-diagnostics system that does not require an expert´s participation. The network can classify sea water pollution on the basis of its total luminescent spectrum. A typical minimal detectable PSP (pollutant´s spectrum portion) value is 0.2; this value corresponds to a concentration of 0.5-10 p.p.m. for dissolved organic matter (DOM) in water (10 mg/l of organic carbon), a situation that is most difficult for diagnostics. The net is capable of giving adequate answers for spectra corresponding to a mixture of two pollutants or for spectra of unknown substances. It is possible to detect nonstandard situations, as reflected by the simultaneous activity of a number of output neurons. A linear neural net allows one to define the concentration of a known pollutant with a typical accuracy of 0.1 p.p.m. Variations of the DOM spectrum shape and amplitude within reasonable limits do not affect the neural net´s functioning
Keywords :
environmental science computing; geophysics computing; luminescence of liquids and solutions; molecular fluorescence; neural nets; organic compounds; seawater; water pollution detection and control; dissolved organic matter; fluorescent diagnostics; minimum detectable amount; mixture; natural waters; neural networks; nonstandard situations; organic pollution; pollutant concentration; sea water express-diagnostics system; total luminescent spectrum; Active matrix organic light emitting diodes; Fluorescence; Intelligent networks; Marine pollution; Microelectronics; Neural networks; Nuclear physics; Petroleum; Region 8; Water pollution;
Conference_Titel :
Neuroinformatics and Neurocomputers, 1992., RNNS/IEEE Symposium on
Conference_Location :
Rostov-on-Don
Print_ISBN :
0-7803-0809-3
DOI :
10.1109/RNNS.1992.268642