Fuzzy bases

Fuzzy based mapping between local variance v and central weight of the Gaussian mask Wo by using the knowledge base. 

Fig. 8 Performance comparison between the proposed fuzzy based technique and the crisp rule based technique under vtuying zooming conditions at 4 1 compression ratio a flower, b Stefan...

Kleiner, Y, Rajani, B.B. Sadiq, R., 2006. Failure risk management of buried infrastructure using fuzzy-based techniques. Journal of Water Supply Research and Technology, Aqua, 55(2) 81-94. 

Shahriar, A. Sadiq, R. Tesfamariam, S. 2012. Risk analysis for oil gas pipelines A sustainability assessment approach using fuzzy based bow-tie analysis. J. Loss Prevention Process bid. 25, 505-523. 

Chapter 5 is structured as follows. Since there exists no direct cause-and-effect relationship between SCM and a company s revenues the following section gives a concise overview of the relevant literature (Chapter 5.1). In the next step a logistics customer service-revenue curve is derived (Chapter 5.2) which determinants are calculated in the next step by a fuzzy-based q)proach (Chapters 5.3). The relevant results from the developed fuzzy model are presented in a numerical example from the consumer goods industry (Chapter 5.4). Finally, in Chapter 5.5 a discussion based on previous experience is offered. The presentation of the determination of the revenue contribution of SCM ends with a short summary in Chapter 5.6. 

As the derived shape of the logistics customer service-revenue curve is of qualitative nature, a quantification of that relationship is called for. The exact curve progression is determined by surrounding conditions like product, customers, industry or company (Hsin-Hui et aly 2009 112, 121 ). The below introduced fuzzy-based model ascertains the curve progression considering these fEictors. 

Ayag, Z (2005) A fuzzy-based simulation approach to concept evaluation in a NPD environment. In HE Transactions, 37(9), 827-842. 

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