Chemistry for the Protection of the Environment 3 : Proceedings of the 11th International Conference Held in Cairo, Assuan, and Luxor, Egypt, September 10-17, 1997

Lucjan Pawlowski. Marjorie A. Gonzales. Marzenna R. Dudzinska. William J. Lacy.

ISBN 10: 0306460262 / ISBN 13: 9780306460265

Published by Plenum Press, 1998

About this Item

This book is part of a large purchase from a Public Sector Library and except where mentioned are for the most part LIKE NEW! MOSTLY the ONLY flaws are the blacked out (they insisted) Library stamps which show many of them to be UNUSED! This copy is Very Good (AVERAGE) with Near Fine (NEAR NEW) contents. FEEL FREE TO E-MAIL FOR PHOTOGRAPHS AND FURTHER DETAILS. FROM A DEALER WHO TELLS YOU WHO THEY ARE AND WHAT THEIR TELEPHONE AND ADDRESS CONTACT DETAILS ARE! Size: 4to - over 9¾" - 12".

Seller Inventory # 33333336364

Bibliographic Details

• Title: Chemistry for the Protection of the Environment 3 : Proceedings of the 11th International Conference Held in Cairo, Assuan, and Luxor, Egypt, September 10-17, 1997
• Publisher: Plenum Press
• Publication Date: 1998
• Language: English
• ISBN 10: 0306460262
• ISBN 13: 9780306460265
• Binding: Glossy Pictorial Boards
• Edition: This is the FIRST EDITION
• Condition: Near Fine (NEAR NEW)
• Dust Jacket Condition: No Jacket
• Signed: EX PUBLIC SECTOR LIBRARY BLACK

About this title

Synopsis

The first meeting in this series was organized by Prof. Pawlowski and Dr. Lacy in 1976 at the Marie Curie-Sklodowska University in Lublin, Poland. The conference dealt with various physicochemical methodologies for water and wastewater treatment research projects that were jointly sponsored by US EP A and Poland. The great interest expressed by the participants led the organizers to expand the scope of the second conference, which was also held in Poland in September 1979. The third and enlarged symposium was again successfully held in 1981 in Lublin, Poland. At that time the participating scientists and engineers expressed their desire to broaden the coverage as well as the title of the conference series. The International Committee, ap­ proved the title "Chemistry for the Protection of the Environment" and designated that date of the fourth conference, CPE IV, which was convened in September 1983 at the Paul Sabatier University in Toulouse, France, and was hosted and arranged by Prof. A. Verdier. This conference series included participants from various government agencies, academia, and the private sector, representing industrialized countries as well as emerging nations, both the East and West in an independent, non politica! forum.

Synopsis

The 25 years up to 1999 have seen a tremendous growth in the application of statistical and modelling techniques to ecological problems. This expansion has been accelerated by the increasing availability of software, books and computing power. However, the suitability of some of these approaches to data analysis, in a relatively knowledge-poor discipline such as ecology, can be questioned on grounds of appropriateness and robustness. One reason for these concerns is that many ecological problems are at best poorly defined and most lack algorithmic solutions. Machine learning methods offer the potential for a different approach to these difficult problems. One definition of machine learning is that it is concerned with inducing knowledge from data, where the data could be patterns in a game of chess or patterns in the species composition of natural communities. Unfortunately ecologists have little experience of these relatively recent and novel approaches to understanding data.

This is a problem that is made more complex because there is no simple taxonomy of machine learning methods and there are relatively few examples in the mainstream ecological literature to encourage exploration. This text is aimed at introducing machine learning methods to a readership of professional ecologists. All but one of the chapters have been written by ecologists and biologists who highlight the application of a particular method to a particular class of problem. Examples include the identification of species, optimal mate choice, predicting species distributions and modelling landscape features. A group of experienced machine learning workers, who have become interested in environmental problems, have written a chapter that demonstrates how machine learning methods can be used to discover equations that describe the dynamic behaviour of ecological systems. The final chapter reviews "real learning", offering the potential for greater dialogue between the biological and machine learning communities.