First Course on Fuzzy Theory and Applications (Advances in Intelligent and Soft Computing 27)
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Fuzzy logic offers computationally-oriented systems of concepts and methods, to formalize types of reasoning which are ordinarily approximate only, and not exact. In principle, this allows us to give a definite, precise answer to the question, "To what extent is something the case? Via a series of switches, this kind of reasoning can be built into electronic devices. That was already happening before fuzzy logic was invented, but using fuzzy logic in modelling has become an important aid in design, which creates many new technical possibilities.
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Fuzzy reasoning i. It looks like fuzzy logic will eventually be applied in almost every aspect of life, even if people are not aware of it, and in that sense fuzzy logic is an astonishingly successful invention. Originally lot of research on fuzzy logic was done by Japanese pioneers inventing new machinery, electronic equipment and appliances see also Fuzzy control system.
Since that time, the movement has spread worldwide; nearly every country nowadays has its own fuzzy systems association, although some are larger and more developed than others. In some cases, the local body is a branch of an international one. In other cases, the fuzzy systems program falls under artificial intelligence or soft computing. Lotfi A. Zadeh estimated around that there were more than 50, fuzzy logic—related, patented inventions.
He listed 28 journals at that time dealing with fuzzy reasoning, and 21 journal titles on soft computing. His searches found close to , publications with the word "fuzzy" in their titles, but perhaps there are even , When he died on 11 September at age 96, Professor Zadeh had received more than 50 engineering and academic awards, in recognition of his work. The technique of fuzzy concept lattices is increasingly used in programming for the formatting, relating and analysis of fuzzy data sets. According to the computer scientist Andrei Popescu at Middlesex University London ,  a concept can be operationally defined to consist of:.
Once the context is defined, we can specify relationships of sets of objects with sets of attributes which they do, or do not share. Whether an object belongs to a concept, and whether an object does, or does not have an attribute, can often be a matter of degree. Thus, for example, "many attributes are fuzzy rather than crisp". This is the basic idea of a "fuzzy concept lattice", which can also be graphed; different fuzzy concept lattices can be connected to each other as well for example, in " fuzzy conceptual clustering " techniques used to group data, originally invented by Enrique H.
Fuzzy concept lattices are a useful programming tool for the exploratory analysis of big data , for example in cases where sets of linked behavioural responses are broadly similar, but can nevertheless vary in important ways, within certain limits. It can help to find out what the structure and dimensions are, of a behaviour that occurs with an important but limited amount of variation in a large population.
Coding with fuzzy lattices can be useful, for instance, in the psephological analysis of big data about voter behaviour, where researchers want to explore the characteristics and associations involved in "somewhat vague" opinions; gradations in voter attitudes; and variability in voter behaviour or personal characteristics within a set of parameters. Very large quantities of data can now be explored using computers with fuzzy logic programming  and open-source architectures such as Apache Hadoop , Apache Spark , and MongoDB.
One author claimed in that it is now possible to obtain, link and analyze " data points" for each voter in a population, using Oracle systems a "data point" is a number linked to one or more categories, which represents a characteristic. It also becomes possible to identify and measure gradations in personal characteristics which, in aggregate, have very large effects. Some researchers argue that this kind of big data analysis has severe limitations, and that the analytical results can only be regarded as indicative, and not as definitive.
In a video interview published by The Guardian in March , whistleblower Christopher Wylie called Cambridge Analytica a "full-service propaganda machine" rather than a bona fide data science company. Its own site revealed with "case studies" that it has been active in political campaigns in numerous different countries, influencing attitudes and opinions.
The company itself was founded on using Facebook data". According to Christopher Wylie 's testimony, the company also harvested the data of each user's network of friends, leveraging the original data set. It then converted, combined and migrated its results into new data sets, which can in principle survive in some format, even if the original data sources are destroyed. It created and applied algorithms using data to which - critics argue - it could not have been entitled.
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This was denied by Cambridge Analytica , which stated on its website that it legitimately "uses data to change audience behavior" among customers and voters who choose to view and provide information. If advertisers can do that, why not a data company? Where should the line be drawn?
Legally, it remained a "fuzzy" area. The tricky legal issue then became, what kind of data Cambridge Analytica or any similar company is actually allowed to have and keep. Federal Trade Commission inquiry, to establish whether Facebook violated the terms of a consent decree governing its handing of user data data which was allegedly transferred to Cambridge Analytica without Facebook's and user's knowledge.
Facebook] that I have never seen in the fifteen years that I have covered it. Zuckerberg claimed that he "did not really know". Lujan's figure was based on ProPublica research, which in fact suggested that Facebook may even have 52, data points for many Facebook users. He justified himself saying that:. What we have learnt now In July , Facebook and Instagram barred access from Crimson Hexagon , a company that advises corporations and governments using one trillion scraped social media posts, which it mined and processed with artificial intelligence and image analysis.
It remained "fuzzy" what was more important to Zuckerberg: making money from user's information, or real corporate integrity in the use of personal information. Thus, "the good" was itself a fuzzy concept, because it was a matter of degree "more good than bad". He had to sell stuff, to keep the business growing. If people did not like Facebook, then they simply should not join it, or opt out, they have the choice. Many critics however feel that people really are in no position to make an informed choice, because they have no idea of how exactly their information will or might be used by third parties contracting with Facebook; because the company legally owns the information that users provide online, they have no control over that either, except to restrict themselves in what they write online the same applies to many other online services.
After the New York Times broke the news on 17 March , that copies of the Facebook data set scraped by Cambridge Analytica could still be downloaded from the Internet, Facebook was severely criticized by government representatives. On 2 May , it was reported that the Cambridge Analytica company was shutting down and was starting bankruptcy proceedings, after losing clients and facing escalating legal costs.
A traditional objection to big data is, that it cannot cope with rapid change: events move faster that the statistics can keep up with. Yet the technology now exists for corporations like Amazon , Google and Microsoft to pump cloud-based data streams from app-users straight into big data analytics programmes, in real time. Obviously this achievement has become highly topical in military technology, but military uses can also have spin-offs for medical applications.
There have been many academic controversies about the meaning, relevance and utility of fuzzy concepts. If it weren't called fuzzy logic , there probably wouldn't be articles on it on the front page of the New York Times. So let us say it has a certain publicity value. Of course, many people don't like that publicity value, and when they see it in the New York Times , it doesn't sit well with them.
However, the impact of the invention of fuzzy reasoning went far beyond names and labels. When Zadeh gave his acceptance speech in Japan for the Honda Foundation prize, which he received for inventing fuzzy theory, he stated that "The concept of a fuzzy set has had an upsetting effect on the established order. Such quasi-conceptual constructions cannot be recognized as concepts by logic.
The law of the excluded middle is really just another form of the requirement that the concept should have a sharp boundary. Similarly, Rudolf E.
We do talk about fuzzy things but they are not scientific concepts". The suggestion is that a concept, to qualify as a concept, must always be clear and precise, without any fuzziness. A vague notion would be at best a prologue to formulating a concept. There is no general agreement among philosophers and scientists about how the notion of a " concept " and in particular, a scientific concept , should be defined. Edward E.https://volunteerparks.org/wp-content/fiqisim/151.php
First Course on Fuzzy Theory and Applications (Advances in Intelligent and Soft Computing 27)
The subsequent ISO definition is very similar. Under the ISO terminology standard of the International Standards Organization first published in October , and reviewed in , a concept is defined as a unit of thought or an idea constituted through abstraction on the basis of properties common to a set of objects. Thus, for example, the same concept can have different names in different languages. Both verbs and nouns can express concepts. A concept can also be thought of as "a way of looking at the world". Reasoning with fuzzy concepts is often viewed as a kind of "logical corruption" or scientific perversion because, it is claimed, fuzzy reasoning rarely reaches a definite "yes" or a definite "no".
A clear, precise and logically rigorous conceptualization is no longer a necessary prerequisite, for carrying out a procedure, a project, or an inquiry, since "somewhat vague ideas" can always be accommodated, formalized and programmed with the aid of fuzzy expressions. The purist idea is, that either a rule applies, or it does not apply. When a rule is said to apply only "to some extent", then in truth the rule does not apply.
Thus, a compromise with vagueness or indefiniteness is, on this view, effectively a compromise with error - an error of conceptualization, an error in the inferential system, or an error in physically carrying out a task. The computer scientist William Kahan argued in that "the danger of fuzzy theory is that it will encourage the sort of imprecise thinking that has brought us so much trouble.