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==Insieme sfocato <math>\tilde{A}</math> e funzione di appartenenza <math>\mu_{\displaystyle {\tilde {A}}}(x)</math>== | ==Insieme sfocato <math>\tilde{A}</math> e funzione di appartenenza <math>\mu_{\displaystyle {\tilde {A}}}(x)</math>== | ||
Scegliamo - come formalismo - di rappresentare un insieme sfocato con la 'tilde':<math>\tilde{A}</math>. Un insieme fuzzy è un insieme in cui gli elementi hanno un 'grado' di appartenenza (coerente con la logica fuzzy): alcuni possono essere inclusi nell'insieme al 100%, altri in percentuali inferiori. | |||
A rappresentare matematicamente questo grado di appartenenza è la funzione <math>\mu_{\displaystyle {\tilde {A}}}(x)</math> chiamata ''''Funzione di appartenenza'''<nowiki/>'. La funzione <math>\mu_{\displaystyle {\tilde {A}}}(x)</math> è una funzione continua definita nell'intervallo <math>[0;1]</math> dove: | |||
*<math>\mu_ {\tilde {A}}(x) = 1\rightarrow </math> se <math>x</math> è totalmente contenuta in <math>A</math> (questi punti sono chiamati 'nucleus', essi indicano i valori ''plausibili'' del predicato ). | |||
*<math>\mu_ {\tilde {A}}(x) = 0\rightarrow </math> se <math>x</math> non è contenuto in <math>A</math> | |||
*<math>0<\mu_ {\tilde {A}}(x) < 1 \;\rightarrow </math> se <math>x</math> è parzialmente contenuto in <math>A</math> (questi punti sono chiamati 'Support' ed indicano i valori possibili del predicato <u>possible</u> predicate values). | |||
La rappresentazione grafica della funzione <math>\mu_{\displaystyle {\tilde {A}}}(x)</math> può essere variato; da quelli con linee lineari (triangolari, trapezoidali) a quelli a forma di campana o 'S' (sigmoidale) come rappresentato in Figura 1, che racchiude l'intero concetto grafico della funzione di appartenenza.<ref>{{Cite book | |||
| autore = Zhang W | | autore = Zhang W | ||
| autore2 = Yang J | | autore2 = Yang J | ||
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[[File:Fuzzy_crisp.svg|alt=|left|thumb|400px|'''Figure 1:''' Types of graphs for the membership function.]] | [[File:Fuzzy_crisp.svg|alt=|left|thumb|400px|'''Figure 1:''' Types of graphs for the membership function.]] | ||
The '''support set''' of a fuzzy set is defined as the zone in which the degree of membership results <math>0<\mu_ {\tilde {A}}(x) < 1</math>; | The '''support set''' of a fuzzy set is defined as the zone in which the degree of membership results <math>0<\mu_ {\tilde {A}}(x) < 1</math>; on the other hand, the '''core''' is defined as the area in which the degree of belonging assumes value <math>\mu_ {\tilde {A}}(x) = 1</math> | ||
The 'Support set' represents the values of the predicate deemed '''possible''', while the 'core' represents those deemed more '''plausible'''. | The 'Support set' represents the values of the predicate deemed '''possible''', while the 'core' represents those deemed more '''plausible'''. | ||
If <math>{A}</math | If <math>{A}</math> represented a set in the ordinary sense of the term or classical language logic previously described, its membership function could assume only the values <math>1</math> or <math>0</math>, <math>\mu_{\displaystyle {{A}}}(x)= 1 \; \lor \;\mu_{\displaystyle {{A}}}(x)= 0</math> depending on whether the element <math>x</math> belongs to the whole or not, as considered. Figure 2 shows a graphic representation of the crisp (rigidly defined) or fuzzy concept of membership, which clearly recalls Smuts's considerations.<ref name=":0">•SMUTS J.C. 1926, [[wikipedia:Holism_and_Evolution|<!--139-->Holism and Evolution]], London: Macmillan.</ref> | ||
Let us go back to the specific case of our Mary Poppins, in which we see a discrepancy between the assertions of the dentist and the neurologist and we look for a comparison between classical logic and fuzzy logic: | Let us go back to the specific case of our Mary Poppins, in which we see a discrepancy between the assertions of the dentist and the neurologist and we look for a comparison between classical logic and fuzzy logic: | ||
[[File:Fuzzy1.jpg|thumb|400x400px|'''<!--141-->Figure 2:''' <!--142-->Representation of the comparison between a classical and fuzzy ensemble.]] | [[File:Fuzzy1.jpg|thumb|400x400px|'''<!--141-->Figure 2:''' <!--142-->Representation of the comparison between a classical and fuzzy ensemble.]] | ||
'''Figure 2:''' Let us imagine the Science Universe <math>U</math | '''Figure 2:''' Let us imagine the Science Universe <math>U</math> in which there are two parallel worlds or contexts, <math>{A}</math> and <math>\tilde{A}</math>. | ||
<math>{A}=</math> In the scientific context, the so-called ‘crisp’, and we have converted into ''the logic'' of ''Classic Language'', in which the physician has an absolute scientific background information <math>KB</math> | <math>{A}=</math> In the scientific context, the so-called ‘crisp’, and we have converted into ''the logic'' of ''Classic Language'', in which the physician has an absolute scientific background information <math>KB</math> with a clear dividing line that we have named <math>KB_c</math>. | ||
<math>\tilde{A}=</math> In another scientific context called ‘fuzzy logic’, and in which there is a union between the subset <math>{A}</math | <math>\tilde{A}=</math> In another scientific context called ‘fuzzy logic’, and in which there is a union between the subset <math>{A}</math> in <math>\tilde{A}</math> that we can go so far as to say: union between <math>KB_c</math>. | ||
We will remarkably notice the following deductions: | We will remarkably notice the following deductions: |
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