Optimal Field-Scale Groundwater Remediation Using Neural Networks and the Genetic Algorithm

An approach to nonlinear optimization that harnesses the strengths of artificial neural networks and the genetic algorithm to search for more cost-effective remediation strategies within practical time frames is described.

Saved in:
Bibliographic Details
Published in:Environmental science & technology 1995-05, Vol.29 (5), p.1145-1155
Main Authors: Rogers, Leah L, Dowla, Farid U, Johnson, Virginia M
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Environmental monitoring
Exact sciences and technology
Genetic algorithms
Groundwater
Groundwaters
Natural water pollution
Neural networks
Pollution
Water treatment and pollution
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:An approach to nonlinear optimization that harnesses the strengths of artificial neural networks and the genetic algorithm to search for more cost-effective remediation strategies within practical time frames is described.
ISSN:0013-936X
1520-5851
DOI:10.1021/es00005a003