Efficacy of Selected Soft Computing Techniques in Ranking of Sites for Hazardous Industrial Installation

Chapter
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 317)

Abstract

Environmental impact assessment (EIA) is a process of identifying impact and risks that a proposed project (e.g., nuclear power plant installation) may have on the environment. The EIA methods require measurement of specific parameters and variables to estimate the values of impact indicators. However, many parameters and impact indicators in EIA cannot be measured precisely (e.g., lifestyle quality, social acceptance, etc.), and are sometimes very subjective in nature. In order to process this inaccurate and subjective information, we have used soft computing techniques to model the EIA process. In the present study we have implemented two well defined soft computing methods for EIA, namely, Fuzzy Indexing and Artificial Neural Networks (ANNs). The chapter presents a comparative evaluation of these methods with the existing BEES method.

Keywords

Environmental impact assessment Fuzzy indexing Artificial neural networks Linear vector quantization 

Notes

Acknowledgement

We would like to express sincere gratitude to Dr. Mrs. S. S. Tikle, Environmental Science Department, University of Pune, India and other Experts recommended by her for their valuable opinion in assessing Environmental parameters and Reports.

References

  1. 1.
    Das, H.: Food Processing Operation Analysis, pp. 383–394. Asian Books Private Limited, Chennai (2005)Google Scholar
  2. 2.
    KaiNing, Y.U., BingXu, L.V.: Research of the environmental impact assessment methods caused by foundation pit dewatering. In: 2011 International Symposium on Water resource and environmental protection (ISWREP), vol. 4, pp. 2777–2780, May 2011Google Scholar
  3. 3.
    Lohani, B.N., Evans, J.W., Everitt, R.R., Ludwig, H., Richard, A.C., Tu, S.L.: Environmental Impact Assessment for developing countries in Asia, Asian Development Bank (1997)Google Scholar
  4. 4.
    MathWorks Matlab Help, Learning Vector Quantization Networks (2011)Google Scholar
  5. 5.
    Mohamed, M.Y.: Artificial neural network model to assess the impacts of land development on the river flow. The 2nd international conference on water resources and arid environment, King Saud University, Riyadh, Saudi Arabia (2006)Google Scholar
  6. 6.
    Omrani, H., Ion-Boussier, L., Trigano, P.: An approach for environmental impact assessment. In: Proceedings of the 5th International Conference on Computational Intelligence, Man Machine Systems and Cybernetics, Italy (2006) Google Scholar
  7. 7.
    Ross, T.J.: Fuzzy Logic with Engineering Application. McGraw Hill, New Mexico (1995)Google Scholar
  8. 8.
    R.S Envirolink Technologies, TT Energy. Environmental Impact Assessment of H.E Project (2010)Google Scholar
  9. 9.
    R.S Envirolink Technologies, Hydro Power Plant. Environmental Impact Assessment Report (2010)Google Scholar
  10. 10.
    Shepherd, R.B.: Quantifying Environmental Impact Assessments using Fuzzy Logic. Springer, New York (2005)Google Scholar
  11. 11.
    Sivanandam, S.N., Sumathi, S., Deepa, S.N.: Introduction to Neural Networks using Matlab. Tata Mc Graw Hill, Delhi (2006)Google Scholar
  12. 12.
    Smec India. Environmental Impact Assessment and Environmental Management Plan for NAFRA Hydro Electric Power Project (2009)Google Scholar
  13. 13.
    Tayebi, M.H., Tangestani, M.H., Roosta, H. Environment impact assessment using neural network model: a case study of the Jahani, Konarsiah and Kohe Gach salt plugs, SE Shiraz, Iran. In: Wagner, W., Székely, B. (eds.) ISPRS TC VII Symposium—100 Years ISPRS, vol. 35, part 7B. IAPRS, Vienna, Austria, 5–7 July 2010Google Scholar
  14. 14.
    Teresa, M.V, Manuel J.F., Carlos L.G.: Application of fuzzy logic to qualify the environmental impact in abandoned mining sites, Water Air Soil Pollut. 217, 303–315 (2011). doi:  10.1007/s11270-010-0587-6
  15. 15.
    Varshosaz, K.: Application of fuzzy logic in environmental impact assessment modeling of a man-made lake in Western Tehran (Iran). The 2nd international conference on environmental science and technology IPCBEE, vol.6, IACSIT Press, Singapore (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of PuneMaharashtraIndia
  2. 2.Evolutionary Computing and Image Processing GroupCentre for Development of Advanced ComputingPuneIndia
  3. 3.Berkeley Initiative Soft Computing, Special Interest GroupEnvironmental Management SystemBerkeleyUSA
  4. 4.College of EngineeringPuneIndia

Personalised recommendations