Forecasting the ranks of sites suitable for power plant installations
DOI:
https://doi.org/10.24297/ijct.v15i14.3965Keywords:
Prediction, Decision support, Fuzzy Soft Set, Linguistic Fuzzy Soft set, Parameter reduction, Futuristic ranking, Planning toolAbstract
An increase in the number of decision parameters used for ranking of sites for a power plant installation using the soft computing techniques leads to complex formulations that are computationally expensive[41]. Amongst a large number of decision parameters, if some of the parameters do not significantly contribute towards the ranking process, then we need not consider these for decision making. Moreover, it is very tedious to form fuzzy sets for all the 87 decision parameters from several environmental experts, which serve as inputs to certain soft computing techniques used for ranking. The decision parameters comprise of some parameters used to describe air quality, water quality, land suitability, socioeconomic and ecological suitability. We have made an attempt to reduce the number of input decision parameters so that the processing is computationally fast without significantly degrading the accuracy of the end results. We have also attempted to predict futuristic values of some of the relevant parameters to infer site suitability and/or ranking, futuristically (subsequent five years) which can act as a planning tool.Downloads
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References
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[1]Abd-Alsabour, Nadia, and Marcus Randall. "Feature Selection for Classification Using an Ant olony System", 2010 Sixth IEEE International Conference on e-Science Workshops, 2010.
[2]Areerachakul S., Junsawang P., Pomsathit A., Prediction of Dissolved Oxygen using Artificial
Neural Network, Computer communication and Management, pp 524-528, 2011
[3]A.R. Roy, P.K. Maji, A fuzzy soft set theoretic approach to decision making problems, J.Comput. Appl. Math. 203 (2007), pp 412–418
[4]Battelle Columbus Laboratories,
http://www.scopenvironment.org/downloadpubs/scope5/chapter04.html (accessed
October 2012)
[5] Central Pollution Control Board, Government of India, 2012, http://www.cpcb.nic.in/
[6] D. Molodtsov, A soft set theory – first results, Comput. Math. Appl. 37 (4) (1999)19–
31
[7] E. Bonabeau, M. Dorigo, G. Theraulez, Swarm Intelligence: From Natural to Artificial Systems, Oxford University Press, New York, 1999, pp. 73–78
[8]Feng, F.. "Application of level soft sets in decision making based on interval-valued fuzzy soft sets", Computers and Mathematics with Applications, 201009
[9]Grande J. and Suarez M. and Villar J., A Feature Selection method using a Fuzzy
Mutual Information Measure, Innovations in Hybrid Intelligent Systems, pp 56-63,
2007
[10]Goodarzi, Mohammad, Matheus P. Freitas, and Richard Jensen. "Feature Selection and Linear/Nonlinear Regression Methods for the Accurate Prediction of Glycogen Synthase Kinase-3β Inhibitory Activities", Journal of Chemical Information and Modeling, 2009
[11]EIA, Nuclear Power Project Jaitapur, National Environmental Engineering Research Institute, Nagpur, 2010
[12]Jensen R., "Supplementary Developments and Investigations", Computational Intelligence and Feature Selection, 09/09/2008
[13] Jensen R., "Further Advanced FS Methods", Computational Intelligence and Feature Selection, 09/09/2008
[14] Jensen R., "Applications II: Web Content Categorization", Computational Intelligence and
Feature Selection, 09/09/2008
[15] Jensen R., Studies in Computational Intelligence, 2006
[16] Jensen R., Combining rough and fuzzy sets for feature selection- Ph.D. Thesis, 2005,
University of Edinburg
[17] Jensen R., "Performing feature selection with ACO", Studies in Computational Intelligence,
2006
[18] Kalyani Sambhoo, Sanjay Kadam, Ashok Deshpande, Rule based fuzzy indexing for grading
of proposed industrial sites for power plant installation, Int. J.Computer Technology. 10 (7)
(2013)
[19] Kudankulam Nuclear Power Project, Environment Impact Assessment Report, Nuclear Power Corporation Ltd., India, 2011
[20] Marco Dorigo, Mauro Birattari, Thomas Stützle, Ant Colony Optimization –Artificial Ants as a Computational Intelligence Technique, 2006
[21] Matrix, Environment Impact Assessment of Nuclear Power plant in Jaitapur,
[22] Matrix Thermal Power Pvt Ltd, 2010, Khammam, Andhra Pradesh
[23]Narmada Thermal Power Limited, Draft Environmental Impact Assessment Report for
Thermal Power Plant, Bharuch, Gujarat, 2011
[24] NTPC Limited, Badarpur Combined Cycle Power Project, Badarpur, Delhi, 2010
[25] Pandey, J. and Rakesh Kumar and Devotta S., Health risks of NO2, SPM and SO2 in
Delhi (India), Atmospheric Environment, pp 6868–6874, 2005
[26] Patel Energy Limited, Draft Environmental Impact Assessment for Coal Based
Thermal Power Plant, Amreli, Gujarat, 2011
[27] Principal Component Analysis,
https://en.wikipedia.org/wiki/Principal_component_analysis, [Online; Accessed 20
Dec, 2014]
[28] R. Jensen, Q. Shen, Computational Intelligence and Feature Selection Rough and
Fuzzy Approaches, John Wiley and Sons, Inc. Pub, Hoboken, 2008
[29] Ross, T., Fuzzy Logic with Engineering Application, 1995, isbn 0-470-86075-8,
Mc Graw Hill, New Mexico
[30] R.S. Envirolink Technologies, GMR Bajoli Holi Hydro Power Plant, Environmental Impact
Assessment Report, 2010
[31] R.S. Envirolink Technologies, TT Energy, Environmental Impact Assessment of H.E.
Project, 2010
[32]Saikia, L. C., S. M. Borah, and S. Pait. "Detection and classification of power quality
disturbances using wavelet transform, fuzzy logic and neural network", 2010 Annual IEEE
India Conference (INDICON), 2010.
[33] Sangeetha R., B. Kalpana, Enhanced Fuzzy Rough set based Feature selection
strategy using Differential Evolution, International Journal of Computer Science and
Applications, pp 13-20, 2013
[34] Sfetsos A., Vlachogiannis D., Time Series Forecasting of Hourly PM10 using
Localized Linear Models, Journal of Software Engineering, pp 374-383, 2010,
[35] Shepherd R., Quantifying Environmental Impact Assessments using Fuzzy Logic, 2005,
ISBN 978-0-387-28098-1, Springer
[36] Smec India, Environmental Management Plan for NAFRA Hydro Electric Power Project,
Smec India, SEW Nafra Corporation, 2009, Kameng, Arunachal Pradesh
[37]S.N. Sivanandam. "Introduction to Particle Swarm Optimization and Ant Colony
Optimization", Introduction to Genetic Algorithms, 2008
[38] SPIC Electric Power corporation Pvt., Ltd., HW Tuticorin Thermal Power
Project,2010, Tuticorin, Tamilnadu
[39]Sun, Yuanchang, and Jack Xin. "Nonnegative Sparse Blind Source Separation for NMR Spectroscopy by Data Clustering, Model Reduction, and $\ell_1$ Minimization", SIAM Journal on Imaging Sciences, 2012.
[40]Tanli Kuang. "A method to calculate importance weights of fuzzy soft sets with unequal importance weights", 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery, 08/2010
[41]Tao, Zhifu, Huayou Chen, Xia Song, Ligang Zhou, and Jinpei Liu. "Uncertain linguistic
fuzzy soft sets and their applications in group decision making", Applied Soft Computing, 2015.
[42] Venkadesh S., Hoogenboom G., Potter W., McClendon, R., A genetic algorithm to refine input data selection for air temperature prediction using artificial neural networks, Applied soft computing, pp 2253-2260, 2013
[43]Xiuqin M., Sulaiman N., Hongwu Q., Herawan T., Zain, J., A new efficient normal
parameter reduction algorithms of soft sets, Computers and Mathematics with
Applications, Vol 62, pp 588-598, 2011
[44]Zhi Kong. "Changing entries in soft sets", 2010 International Conference On Computer Design and Applications, 06/2010
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Published
2017-01-08
How to Cite
Sambhoo(Salla), D. K., & Kadam, D. S. (2017). Forecasting the ranks of sites suitable for power plant installations. INTERNATIONAL JOURNAL OF COMPUTERS &Amp; TECHNOLOGY, 15(14), 7453–7471. https://doi.org/10.24297/ijct.v15i14.3965
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