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I have been trying to understand the difference between two types of fuzzy logic, i.e., Type I and Type II. I have seen lot of tutorials on the internet, but they are using complicated graphs and equations to explain the difference and I am unable to understand. I am trying to learn the difference in order to implement type II fuzzy logic with Semantic Web technology to help increase the number of relevant search results. Please help me understand the difference by giving simple examples.

Joshua Taylor
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sana
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  • This question does not appear to be about programming within the scope defined in the help center. – Ali May 08 '14 at 10:11
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    Note that the [tag:fuzzy] has the wiki entry "Do not use". I've removed it from the question. Please don't use it in the future. – Joshua Taylor May 08 '14 at 15:32
  • I am sorry. I did not get your point. What do you mean by "Note that the fuzzy has the wiki entry 'Do not use'"... What is it's impact ? @JoshuaTaylor – sana May 08 '14 at 18:16
  • The question was tagged with [tag:fuzzy]. When you type in a tag for a question, the summary for the tag is displayed, and that usually includes some guidelines for when you should use it. The [tag:fuzzy] tag's summary says (emphasis added): "**Do not use**-ambiguous: See fuzzy-search, fuzzy-logic, or image-processing for more appropriate tags." The tag shouldn't be used. – Joshua Taylor May 08 '14 at 18:47
  • @JoshuaTaylor Ok thank you. But my question is still there. I am unable to understand the difference. :( – sana May 08 '14 at 19:39
  • You mean the difference between the fuzzy logic types, or the difference between using the tag and not using the tag? – Joshua Taylor May 08 '14 at 20:28
  • Can you explain any more about what you've encountered so far, and what's been unclear about it. E.g., what in http://en.wikipedia.org/wiki/Type-2_fuzzy_sets_and_systems is problematic? In Type 1 systems, the only fuzziness is membership. E.g., "Tom is rather tall." The phrase "is rather tall" corresponds to stronger membership in "tall". But if tallness can be fuzzy, why must "Tom is rather tall" be absolute? Type II systems allow you to say ""Tom is rather tall" is not very certain." adding uncertainty to the fuzzy claim. – Joshua Taylor May 08 '14 at 20:41
  • So far, I have come to know that type II fuzzy logic can describe the intervals between membership grades. What is another point of difference except this ? – sana May 09 '14 at 01:09

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The main difference between them is that the type-2 fuzzy set itself is fuzzy, with a new dimension called the footprint of uncertainty, which characterizes type-2 fuzzy logic.

The rule structure of both types are the same, except for the antecedent and consequent are of the respective types.

You may refer to link

Shivanshu Bagga
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