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Remediation Of Abandoned Surface Coal Mining Sites

RRP $120.00

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Christopher Kennedy University of Toronto, Department of Civil Engineering, 35 St. George Street, Toronto, Ontario, Canada M5S IA4 Coal is a valuable resource. It provides a significant amount of the World's energy supply and it is the basis for many industries. However, in areas where coal lies close to the Earth's surface and has been exploited by open cast tech- niques, radical alterations of landscape and significant impacts on the envi- ronment have occurred. This report was prepared to provide guidance to those who are responsible for the prevention of environmental effects from surface mining and for the restoration of the mining areas. Environmental problems of surface coal mining and restoration of the mine sites are discussed in the re- port. Particular attention is given to Eastern Europe, which continues to be a major centre of opencast lignite mining. Reclamation of mined lands for for- estry, agriculture and wildlife is briefly discussed. However, the shear volume of coal removed from many mines in Eastern Europe is so vast, that there is often insufficient overburden material to refill the pits. Consequently, the main focus of this report is on the creation of lakes in these former surface mines. Many problems have to be overcome in creating healthy lakes for recreation or wildlife. Guidelines for treating water quality problems and further devel- opment of lakes are provided. Techniques for dealing with acidic, waters, eutrophication and contamination are discussed.


Determining The Economic Value Of Water

RRP $546.99

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Water provides benefits as a commodity for agriculture, industry, and households, and as a public good such as fisheries habitat, water quality and recreational use. To aid in cost-benefit analysis under conditions where market determined price signals are usually unavailable, economists have developed a range of alternative valuation methods for measuring economic benefits.

This volume provides the most comprehensive exposition to-date of the application of economic valuation methods to proposed water resources investments and policies. It provides a conceptual framework for valuation of both commodity and public good uses of water, addressing non-market valuation techniques appropriate to measuring public benefits - including water quality improvement, recreation, and fish habitat enhancement. The book describes the various measurement methods, illustrates how they are applied in practice, and discusses their strengths, limitations, and appropriate roles.

In this second edition, all chapters have been thoroughly updated, and in particular the coverage of water markets and valuation of ecosystem services from water has been expanded. Robert Young, author of the 2005 edition, has been joined for this new edition by John Loomis, who brings additional expertise on ecosystem services and the environmental economics of water for recreational and other public good uses of water.


Automating The Design Of Data Mining Algorithms

RRP $436.99

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Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from data. We focus on genetic programming in this book because it is the paradigmatic type of machine learning method for automating the generation of programs and because it has the advantage of performing a global search in the space of candidate solutions (data mining algorithms in our case), but in principle other types of search methods for this task could be investigated in the future.



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