Abstract
The use of biological responses in environmental modelling, also referred to as biomonitoring, mainly involves indicator species or communities those accumulate pollutants in their tissues from the surrounding environment, thus reflect the environmental conditions. Despite the progress made through research activities in detecting biological changes in these organisms at various levels i.e. macromolecular, cellular within individual organisms and in communities, constraints with conventional data analysis methods in exactly assessing an environmental pollution and its real cause led ecologists to experiment with emerging technologies. The recent use of artificial neural networks (ANNs), especially self-organising map (SOM) and evolving SOM techniques to analyse multi dimensional data sets provide a means to analyse community dynamics and is elaborated upon with a case study from northern New Zealand.
Date
2003
Source
WE - 2003: Proceedings of the international conference on water and environment: Planning, development, utilization, conservation, and management (Integrated engineering, scientific, technological, and socio-economic approaches, Dec. 15-18, 2003, Regional Research Laboratory, (Council of Scientific and Industrial Research), Bhopal, M.P. India, Bhopal
Item Type
Conference Contribution
Publisher
Council of Scientific and Industrial Research (CSIR)
Rights Statement
NOTICE: this is the author’s version of a work that was accepted for publication. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in (see Citation). The original publication is available at (see Publisher's Version)
