There are several authorities on Fuzzy Logic in Spain. Please, try to find them through Google Scholar (easy), but if you need some help don't hesitate to contact me.
Please note that the phrase Fuzzy Logic has two quite distinct meanings. There is Fuzzy Logic in the strict or narrow sense and there is Fuzzy Logic in the broad sense.
Fuzzy Logic in the narrow sense: a branch of mathematical logic, in particular multi-valued logic, existing since the early decades of the 20th century (especially Lukasiewicz), studying logic systems where the range of truth values is different from {false, true} but not necessarily [0,1], and the axioms may be quite different from the usual ones;
Fuzzy Logic in the broad sense: a branch of applied mathematics, in particular control theory and other technical or applied disciplines, largely based upon Fuzzy Set Theory as popularized by Lofti Zadeh (☨2017) , later worked out by e.g. Fodor, Yager, Sugeno and a lot of other people, not interested in abstract logic but in concrete applications in technical, social and economic disciplines.
So the first question is: which Fuzzy Logic do you mean?
Recommendation: The 8th SOFA Workshop on Software Computing Applications, 13th-15th September 2018
I have contributed twice and been there once (2016). It is a splendid atmosphere and you may come in contact with many outstanding speakers and attendants. Perhaps you want to contribute yourself to the workshop?
Feel free to personally contact Prof. Valentina E. Balas, one of the founding chairs, and ask her if she knows the right expert for you. Tell her that you got her name from me, she will be delighted to help you, I'm sure. But ... she is very busy, so it may take some time before you get a reply.
Adriana qué necesitas exactamente, actualmente emigré a Valencia y tengo tiempo libre para vincularme a proyectos que me apasionen y reten. Por favor escríbeme a mi correo [email protected]
Yesterday, I have been reading diagonally through your paper "The New Fuzzy SWOT". I'm still trying to figure out what your data acquisition model is, i.e. how do you get the data from your respondents, and what type of data are these? Furthermore, I noted that you are still open for any data analysis model which does its job, i.e. give you a way of measuring and ordering the criteria in each of the four cells of a SWOT matrix. I see that you have found most of the relevant FL approaches and one outside this field: Analytical Hierarchy Process. AHP is certainly a good option, but it is a little bit complicated to implement, so you better look for an existing implementation (free software).
Here, I like to propose an alternative data analysis model which is easy to understand and easy to implement e.g. using Excel, so that you may avoid the complications of using heavy-weight tools like Matlab or Mathematica (don't misunderstand me: the tools are of high quality, but they don't solve the problem of choosing the right approach for your problem).
My proposal assumes that you have already found several candidates for the four cells of a SWOT matrix. Then the following steps are:
Use a simple kind of questionnaire asking respondents to scale each candidate SWOT-criterion according to relevance or applicability for the SWOT-category with which it is associated. The scale may be [0,1], or [0,100] or even [-n,+n]. Here for simplicity I will choose the unit interval [0,1] as is usual for a FL approach.
Assuming that you have enough responses per SWOT-criterion, e.g. at least N=20 or so, you have to build a kind of mean (average) relevance or applicability per criterion over all N respondents. The important point is NOT to use the common arithmetic or geometric mean, but to use a mean that is appropriate for fuzzy degrees in [0,1]. Let me know if you are interested to go this way, then I will send you the correct formulae to use (there are three options depending upon the fuzzy addition operation that you want to work with)
That's all! You may directly compare these fuzzy relevance or applicability measures to find out which SWOT-criteria are really interesting from the point of view of your representative sample of users. You may weight the responses if you have the feeling that the respondents have different competences in judging relevance or applicability (the weights should add up to 1). You may even adopt a pass/fail criterion of say 70% to include or exclude criteria in your final SWOT matrix. Or you keep all of them, but order them from high relevance to low relevance while adding the degree of relevance in parentheses, e.g.: "Attend to new client groups (92%)".
Question: what is/are "Expertons"? I never heard of it, but your paper assumes that it is well-known for most readers.
Check out this posts on the Dice and Levenshtein algorithms for some fuzzy matching techniques (http://www.georgestragand.com/di... & http://www.georgestragand.com/le...).