Abstract
Exploring biological indicators as tool for evaluation of ecological conditions is one of prime interest for planning process. The focus of this paper is biological indicator based on seed characteristics and defined with the use of fuzzy sets methodology. It is considered application of fuzzy biological indicators in combination with the minimum average weighted deviation method. Finally, Adaptive Neuro-Fuzzy Inference System is utilized for categorization of biological indicators.
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References
Busscher, W., Krueger, E., Novak, J., Kurtener, D.: Comparison of soil amendments to decrease high strength in SE USA Coastal Plain soils using fuzzy decision-making analyses. International Agrophysics 21, 225–231 (2007)
Burrough, P.A.: Fuzzy mathematical methods for soil survey and land evaluation. Journal of Soil Science 40, 477–492 (1989)
Burrough, P.A., MacMillan, R.A., van Deursen, W.: Fuzzy classification methods for determining land suitability from soil profile observations and topography. Journal of Soil Science 43, 193–210 (1992)
Carver, S.: Integrating multi-criteria evaluation with geographical information systems. International Journal of Geographical Information Systems 5, 321–339 (1991)
Carlsson, C., Fuller, R.: Fuzzy multiple criteria decision making: Recent developments. Fuzzy Sets and Systems 78, 139–153 (1996)
Jang, J.S.: ANFIS: Adaptive-Network-based Fuzzy Inference Systems. IEEE Transaction on Systems, Man, and Cybernetics 23, 665–685 (1993)
Joerin, F., Theriault, M., Musy, A.: Using GIS and outranking multicriteria analysis for land-use suitability assessment. International Journal of Geographical Information Science 15, 153–174 (2001)
Krueger-Shvetsova, E., Kurtener, D.: A management fuzzy indicator for precision agriculture. In: Kurtener, D.A., Yakushev, V.P. (eds.) Agrophysical and Ecological Problems of Agriculture in the 21st Century, vol. 4, pp. 31–43. SPBISTRO Press, St. Petersburg (2003)
Krueger-Shvetsova, E., Kurtener, D.: Evaluation of cultivation practices using fuzzy multi-attributive decision-making approach. In: Kurtener, D.A., Yakushev, V.P. (eds.) Agrophysical and Ecological Problems of Agriculture in the 21st Century, vol. 4/2, pp. 44–53. SPBISTRO Press, St. Petersburg (2003)
Kurtener, D., Shvetsova, E.: Multicriteria analysis of agrotechnologies on the basis of theory of decisions in uncertainty conditions (in Russian). In: Methodological and experimental support of adaptive-landscape systems of agriculture, pp. 193–208. AFI Press, St. Petersburg (2007)
Kurtener, D., Arkhipov, M., Petrova, Z., Badenko, V.: Development of conception of system diagnosing ecological conditions in soil. In: Kurtener, D.A., Yakushev, V.P. (eds.) Agrophysical and Ecological Problems of Agriculture in the 21st Century, vol. 2, pp. 74–84. SPBISTRO Press, St. Petersburg (2000)
Kurtener, D., Badenko, V., Cudlip, W.: Development of the methodology of multiple assessment of burned areas in forest regions for the planning of restoration actions. In: Kurtener, D.A., Yakushev, V.P. (eds.) Agrophysical and Ecological Problems of Agriculture in the 21st Century, vol. 2, pp. 54–62. SPBISTRO, St. Petersburg (2000)
Kurtener, D., Badenko, V.: Fuzzy Algorithms to Support Spatial Planning. In: Geertman, S., Stillwell, J. (eds.) Planning Support Systems in Practice, pp. 249–267. Springer Publishers, Berlin (2002)
Kurtener, D., Krueger-Shvetsova, E., Dubitskaia, I.: Quality estimation of data collection. In: UDMS 2004, pp. 9.101–9.109. UDMS Press, Giorggia-Venice (2004)
Kurtener, D., Krueger-Shvetsova, E., Dubitskaia, I.: Field agriculture experimentation: assessment of geo referenced data quality. In: IAMFE/RUSSIA, pp. 120–127. IAMFE Press, St. Petersburg (2004)
Li, D.F.: Fuzzy multi attribute decision-making models and methods with incomplete preference information. Fuzzy Sets and Systems 106, 113–119 (1999)
Mathworks Inc, http://www.mathworks.com/
Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man-Machine Studies 7, 1–13 (1975)
Orchard, R.A.: User’s Guide: FuzzyCLIPS Version 6.04A. National Research Council, Canada (1998)
Sugeno, M.: Industrial applications of fuzzy control. Elsevier Science Pub. Co., Amsterdam (1985)
Torbert, H.A., Krueger, E., Kurtener, D.: Evaluation of tillage systems for grain sorghum and wheat yields and total N uptake in the Texas Blackland Prairie. Sustainable Agriculture (in print, 2008)
Torbert, A., Krueger, E., Kurtener, D.: Evaluation of Long-Term Impacts of Tillage and Cropping Systems in Alabama, USA. In: Modern Agrophysics for High-Tech, pp. 39–41. AFI Press, St. Petersburg (2007)
Xiang, W.N., Gross, M., Fabos, J.G., Macdougall, E.B.: A fuzzy group multi-criteria decision making model and its application to land-use planning. Environment and Planning B 19, 61–84 (1992)
Wang, Y.: On fuzzy multiattribute decision-making models and methods with incomplete preference information. Fuzzy Sets and Systems 151, 285–301 (2005)
Zadeh, L.A.: Outline of a new approach to the analysis of complex systems and decision processes. IEEE Transactions on Systems, Man, and Cybernetics 3, 28–44 (1973)
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Arkhipov, M., Krueger, E., Kurtener, D. (2008). Evaluation of Ecological Conditions Using Bioindicators: Application of Fuzzy Modeling. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69839-5_36
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DOI: https://doi.org/10.1007/978-3-540-69839-5_36
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