Artificial Neural Network Approach for Predicting Cation Exchange Capacity in Soil Based on Physico-Chemical Properties-Reference-Cited by-同舟云学术

Artificial Neural Network Approach for Predicting Cation Exchange Capacity in Soil Based on Physico-Chemical Properties

Published:2009-01 Issue:1 Volume:26 Page:137-146
ISSN:1092-8758
Container-title:Environmental Engineering Science
language:en
Short-container-title:Environmental Engineering Science

Author:

Tang Lin¹,Zeng Guongming²,Nourbakhsh Farshid³,Shen Guoli L.⁴

Affiliation:

1. College of Environmental Science and Engineering, Hunan University, Changsha 410082, China.

2. College of Environmental Science and Engineering, Hunan University, Changsha 410082, China, Phone: +86 7318822754; Fax: +86 7318823701; E-mail: zgming@hnu.cn

3. Department of Soil Science, College of Agriculture, Isfahan University of Technology, Isfahan 84156-83111, Iran.

4. State Key Laboratory for Chemo/Biosensing and Chemometrics, Hunan University, Changsha 410082, China.

Publisher

Mary Ann Liebert Inc

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry

Link

http://www.liebertpub.com/doi/pdf/10.1089/ees.2007.0238

Reference34 articles.

1. Aging, Bioavailability, and Overestimation of Risk from Environmental Pollutants

2. Lead (II) removal from natural soils by enhanced electrokinetic remediation

3. Adsorption and desorption of copper and zinc in the surface layer of acid soils

4. Variable charge characteristics of selected Andisols from the Azores, Portugal

5. Kinetics of Cadmium and Cobalt Desorption from Iron and Manganese Oxides

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