Maybe this will help... Imagine you have two people sitting at a table drinking and you are the waiter/waitress.
One customer says, "I have 13.21435343234 ml of alchohol in my drink." The other says, "My drink is low." Which is more meaningful??? When the first person makes their statement, do you really know what it means? You will need a lot more information to assess what it means such as: how big is their glass, how much ice is in it, was it a mixed drink? The second person has relayed a very useful statement that tells you exactly what is meant, however, you do not know how much it will take to fill the drink. The first example would be a standard estimate such as probability. It seeks to get to the exact number of concern. The second exaple is a fuzzy estimate, and provides a cognitive estimate that has obvious meaning but will need further investigation to work out the details. Standard estimates deal with what is probable. Fuzzy estimates deal with what is possible. does that make sense? On Fri, Aug 7, 2009 at 3:28 AM, William Silvert<cien...@silvert.org> wrote: > Although Zadeh may have had the idea "of the best fit POSSIBLE" in the back > of his mind, that is hardly how I would characterise the motivation for > using fuzzy logic.For me it brings science closer to the way that people, > including scientists, think, and thus can do a better job of approximating > the best possible reasoning. > > Common examples can be found in some of the fuzzy decision tools that aare > widely circulated as demos. For example, if you are buying a house and your > rules include: > > IF the house is close to work AND not too expensive THEN ... > > the usual approach would be to define "close to work" and "too expensive" as > perhaps <10 km and >200.000 €, but a real person would probably settle for a > really great buy 12 km from work or a 220.000 € house within walking > distance. This is easily represented by treating these concepts with fuzzy > memberships. > > Another reason for using fuzzy logic is that it is simple. Literally so. The > first applications of fuzzy logic were in system control, because back in > the days before cheap high-speed processors it was possible to build > economical controllers to replace slow and expensive systems based on > traditional methods with systems of differential equations to be solved. > Unfortunately there are those who feel that any mathematical approach has to > be fancy and sophisticated and involve lots of equations, which is one of > the reasons that fuzzy logic has been slow to be adopted in ecology, but it > is really very simple. > > Bill Silvert > > ----- Original Message ----- From: "Wayne Tyson" <landr...@cox.net> > To: <ECOLOG-L@LISTSERV.UMD.EDU> > Sent: Thursday, August 06, 2009 9:22 PM > Subject: Re: [ECOLOG-L] Fuzzy Logic in Ecology > > > Re: Ecology Logic Fuzzy* > > I was never much good at statistics, to put it mildly (two or three courses > put a real drag on my GPA and my intuition). > > It seems (intuitively) to me that Bayes and Zadaeh both had good ideas that > were aimed at the direction of the best fit POSSIBLE, the former seeming to > be more elegantly conforming to hypotheses, the latter embracing uncertainty > more certainly--maybe. > > I am grateful for those laboring in the fields of numerical research; > without them observers of the interplay of organisms and their environments > might tumble down some warren of fantasy and never to return. Yet, looking > in the looking-glass never hurt anybody. > > On the other hand, it seems that the Sword of Certainty, especially in the > form of irrelevant decimal points and other attempts to reduce complex and > constantly-changing phenomena to quantities that fit neat boxes carved out > for them, hangs threateningly over jiggly and evasive phenomena, threatening > to freeze it all in place for all time. Still, provided analyses don't stray > too far from the actual data manipulated and are not treated as license for > (ironically?) unbridled conjecture amongst self-ordained emperors, those > numbers can open up insights as well as interfere with them. I have no firm > answer for this conundrum. > > What are the Great Questions in ecology? What are the answers? What answers > have actually changed rather than just been re-clothed or bumped off the > mountain in, say, the last century or so? What new questions have been > added? > > WT > > *Sorry, Bill, in a lame attempt to please everybody I didn't fuss with the > subject line (what a wuss, eh?), I was going to ask Eric off-list but the > reply-to-all button didn't have his email address in it, so I just deleted > one of the apparently duplicate list addresses--gad, this is getting > complicated! Back to square one . . . > > > > ----- Original Message ----- From: "William Silvert" <cien...@silvert.org> > To: <ECOLOG-L@LISTSERV.UMD.EDU> > Sent: Thursday, August 06, 2009 8:13 AM > Subject: [ECOLOG-L] Fuzzy Logic in Ecology > > > I missed Wayne's posting since the subject line had nothing to do with fuzzy > logic, and although I know that I will raise a chorus of outrage I am > changing the subject line. > > Quite a few papers on fuzzy logic aplications have been published, many in > Ecological Modelling (including a couple of my own). I also have some > PowerPoint presentations on my website, http://ciencia.silvert.org, and > there are many in related fields such as soil science. I think that one of > my first efforts was in niche theory, obviously the "multi-dimensional > manifold" that Hutchinson defined must have fuzzy boundaries. > > Unfortunately a lot of work in the field seems to consist of lots of > mathematics with little biological content. I like to think in terms of > fuzzy rules like > > IF the weather is warm AND nutrient levels are high THEN there is a serious > risk of bottom anoxia > > (which is similar to a rule composed for aquaculture siting) but many > authors seem more concerned with whether the membership function is > triangular or trapezoidal. > > As with any new field or approach, fuzzy ecology is experiencing growing > pains. There was an international conference on the topic in Kiel many years > ago, perhaps 15, but progress has been slow. > > Bill Silvert > > ----- Original Message ----- From: "Jonathan Nelson" <eco...@phossie.com> > To: <ECOLOG-L@LISTSERV.UMD.EDU> > Sent: Thursday, August 06, 2009 3:00 PM > Subject: Re: [ECOLOG-L] Bayesian analysis in population ecology workshop, > early registration deadline 10 August 2009 > > >> On Wed, Aug 5, 2009 at 7:25 PM, Wayne Tyson <landr...@cox.net> wrote: >>> >>> Do you know if anyone has investigated the possible application of fuzzy >>> logic theory to ecology/population ecology and why or why not? >> >> Re the first part of the question: >> >> Results 1 - 10 of about 12,300 for fuzzy logic ecology. >> http://scholar.google.com/scholar?q=fuzzy%20logic%20ecology&oe=utf-8 >> >> The results include the 2002 overview paper by Regan, Colyvan, Burgman >> (Ecological Applications, 12(2), 2002, pp. 618–628) as the 3rd result, >> available as PDF. I had not seen this before but I'll be reading it >> this evening, as it looks fascinating: >> >> "Abstract. Uncertainty is pervasive in ecology where the difficulties >> of dealing with >> sources of uncertainty are exacerbated by variation in the system >> itself. Attempts at clas- >> sifying uncertainty in ecology have, for the most part, focused >> exclusively on epistemic >> uncertainty. In this paper we classify uncertainty into two main >> categories: epistemic un- >> certainty (uncertainty in determinate facts) and linguistic >> uncertainty (uncertainty in lan- >> guage). We provide a classification of sources of uncertainty under the >> two main categories >> and demonstrate how each impacts on applications in ecology and >> conservation biology. >> In particular, we demonstrate the importance of recognizing the effect >> of linguistic uncer- >> tainty, in addition to epistemic uncertainty, in ecological >> applications. The significance to >> ecology and conservation biology of developing a clear understanding >> of the various types >> of uncertainty, how they arise and how they might best be dealt with >> is highlighted. Finally, >> we discuss the various general strategies for dealing with each type >> of uncertainty and offer >> suggestions for treating compounding uncertainty from a range of sources." >> > > > -------------------------------------------------------------------------------- > > > > No virus found in this incoming message. > Checked by AVG - www.avg.com > Version: 8.5.392 / Virus Database: 270.13.44/2283 - Release Date: 08/05/09 > 05:57:00 > -- Malcolm L. McCallum Associate Professor of Biology Managing Editor, Herpetological Conservation and Biology Texas A&M University-Texarkana Fall Teaching Schedule: Vertebrate Biology - TR 10-11:40 General Ecology - MW 1-2:40pm Forensic Science - W 6-9:40pm
