Abstract
This paper presents the environmental applications of granular computing. First, the relevance of information granulation in the description of environmental phenomena is discussed. A granular prediction model of time series of a dust storm concentration is described. This example is used to explain the technique of information granulation of an environmental phenomenon. Then the issue of environmental management is discussed. Granular computing helps us establish the pattern recognition technique which is also very helpful in environmental management. In addition, this study presents an approach to extract interpretable rules of natural hazards from available data. Finally, the multi-objective design of a granular hierarchy model is presented to determine the optimal management strategy of air quality. The environmental application experiments show that granular computing comes as a promising vehicle for solving social problems related to protection of the environment.
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Ahmad, M., Mohammad, S.M., Meysam, M.S.: Project risk identification and analysis based on group decision making methodology in a fuzzy environment. International Journal of Management Science and Engineering Management 5(2), 108–118 (2010)
Byun, D.W., Kim, S.T., Cheng, Kim, F., Cuclis, S., Moon, N.: Information infrastructure for air quality modeling and analysis: Application to the Houston-Galveston ozone non-attainment area. J. Environ. Info. 2(2), 38–57 (2003)
Cai, D.L., Chen, W.K.: Knowledge-based air quality management study by fuzzy logic principle. In: Proceedings of the 8th International Conference on Machine Learning and Cybernetics, Baoding, China, pp. 3064–3069 (2009)
Carr, V., Tah, J.: A fuzzy approach to construction project risk assessment and analysis. Advances in Engineering Software 32, 847–857 (2001)
Chapman, C., Ward, S.: Project risk management: processes, techniques and insights, 2nd edn. John Wiley and Sons Ltd, Chichester (2004)
Chen, S.M.: Forecasting enrollments based on fuzzy time series. Fuzzy Sets and Systems 81(3), 311–319 (1996)
Chen, S.M.: Forecasting enrollments based on high-order fuzzy time series. An International Journal Cybernetics and System 33(1), 1–16 (2002)
Chen, S.M., Hsu, C.C.: A new approach for handling forecasting problem using high-order fuzzy time series. Intelligent Automation and Soft Computing 14(1), 29–43 (2008)
Chen, S.M., Huarng, J.R., Lee, C.H.: Handling forecasting problem using fuzzy time series. Fuzzy Sets and Systems 100(2), 217–229 (1998)
Chen, S.M., Hwang, J.R.: Temperature predicting using fuzzy time series. IEEE Transaction on System, Man, and Cybernetics- Part B: Cybernetics 30(2), 263–275 (2000)
Chen, S., Hsu, C.C.: A new method to forecast enrollments using fuzzy time series. International Journal of Applied Science and Engineering 2(3), 234–244 (2004)
Chen, W.K.: An approach to pattern recognition by fuzzy category and neural network simulation. In: Proceedings of the 9th International Conference on Machine Learning and Cybernetic, Cingdao, China, pp. 3042–3048 (2010)
Chen, W.K., Juang, Y.R., Cai, D.L.: Courseware design and assessment methodology by fuzzy theory - A case study of energy saving course. In: Proceedings of the 8th International Conference on Machine Learning and Cybernetic, Baoding, China, pp. 3042–3048 (2009)
Chen, W.K., Sui, G.J., Tang, D.L., Cai, D.L., Wang, J.S.: Study of environmental risk management by multivariable analysis of pattern structure. In: Proceedings of The Fourth International Conference on Management Science and Engineering Management, Chungli, Taiwan, pp. 144–148 (2010)
Choi, H.G., Ahn, J.O., Jeung, H.S., Kim, J.S.: A framework for managing risks on concurrent engineering basis. International Journal of Management Science and Engineering Management 5(1), 44–52 (2010)
Cooper, L.: A research agenda to reduce risk in new product development through knowledge management: a practitioner perspective. Journal of Engineering and Technology Management 20(1-2), 117–140 (2003)
Coppendale, J.: Manage risk in product and process development and avoid unpleasant surprises. Engineering Management Journal 5(1), 35–38 (1995)
Duda, P.O., Hart, P.E., Stork, D.G.: Pattern classification, 2nd edn. Wiley, New York (2001)
Hsu, C.C., Chen, S.M.: A new method for forecasting enrollments based on high-order fuzzy time series. In: Proceeding of the 2003 Jont Conference on AI Fuzzy System and Grey system, Taipei, Taiwan (2003)
Klir, G., Yuan, B.: Fuzzy sets and fuzzy logic: Theory and Applications. Pearson Education Taiwan Ltd, London (2005)
Li, H.L., Huang, G.H., Zou, Y.: An integrated fuzzy-stochastic modeling approach for assessing health-impact risk from air pollution. Stochastic Environmental Research and Risk Assessment 22(6), 789–803 (2008)
Murray, T.J., Pipino, L.L., Gigch, J.P.: A pilot study of fuzzy set. modification of Delphi. Human Systems Management 5, 76–80 (1985)
Patrick, X., et al.: Understanding the key risks in construction projects in China. International Journal of Project Management 25, 601–614 (2007)
Pedrcyz, W., Gomide, F.: Fuzzy systems engineering, pp. 101–135. John Wiley & Sons, USA (2007)
Saaty, T.L.: The analytic hierarchy process: planning, priority setting, resource allocation. McGraw-Hill, New York (1980)
Schuermann, J.: Pattern recognition. Wiley & Sons, Chichester (1996)
Song, Q., Chissom, B.S.: Fuzzy time series and its models. Fuzzy Sets and Systems 54(3), 269–277 (1993)
Song, Q., Chissom, B.S.: Forecasting enrollments with fuzzy time series – Part I. Fuzzy Sets and Systems 54(1), 1–9 (1993)
Song, Q., Chissom, B.S.: Forecasting enrollments with fuzzy time series Part II. Fuzzy Sets and Systems 62(1), 1–8 (1994)
Zadeh, L.A.: Fuzzy sets. Information and Control (8), 338–353 (1965)
Zadeh, L.A.: Fuzzy logic and approximate reasoning. Synthese (30), 407–428 (1975)
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Chen, WK. (2011). Environmental Applications of Granular Computing and Intelligent Systems. In: Pedrycz, W., Chen, SM. (eds) Granular Computing and Intelligent Systems. Intelligent Systems Reference Library, vol 13. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19820-5_14
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DOI: https://doi.org/10.1007/978-3-642-19820-5_14
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