{"id":6112,"date":"2018-01-19T09:59:22","date_gmt":"2018-01-19T09:59:22","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=6112"},"modified":"2025-07-25T21:05:00","modified_gmt":"2025-07-25T15:35:00","slug":"fuzzy-logic-systems","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/fuzzy-logic-systems\/","title":{"rendered":"What is Fuzzy Logic Systems in AI &#8211; Architecture, Application"},"content":{"rendered":"<div>\n<div class=\"\">\n<p>In this Fuzzy Logic Tutorial, we will learn What is\u00a0Fuzzy Logic Systems in Artificial Intelligence. Moreover, we will discuss the Application and Architecture of Fuzzy Logic in AI. Along with this, we will learn why Fuzzy logic is used and what are its pros and cons.<\/p>\n<p>So, let&#8217;s start our journey of Fuzzy Logic System in AI.<\/p>\n<\/div>\n<div class=\"\">\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Introduction to Fuzzy Logic in AI<\/h3>\n<\/div>\n<div class=\"\">\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">a. What is Fuzzy Logic System?<\/h4>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Generally, it\u2019s a method of reasoning. Although, resembles human reasoning. Also, it has an approach to decision making in humans. As they involve all intermediate possibilities between digital values YES and NO.<\/div>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Fuzzy Logic System\u00a0<span class=\"passivevoice\">was invented by<\/span> Lotfi Zadeh. Also, he observed, unlike other computers, it includes a range of possibilities between YES and NO, in a human decision.<\/div>\n<\/div>\n<div class=\"\">\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">b.\u00a0Implementation of Fuzzy Logic System<\/h4>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><span class=\"adverb\">Basically<\/span>,\u00a0it can <span class=\"passivevoice\">be implemented<\/span> in systems with various sizes and capabilities. That should be range from mall micro-controllers to large. Also, it can be implemented in hardware, software, or a combination of both in artificial intelligence.<\/div>\n<\/div>\n<div class=\"\">\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Why Fuzzy Logic?<\/h3>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Generally, we use\u00a0fuzzy logic system for the practical as well as commercial purposes.<\/div>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">We can use it to consumer products and control machines.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Although, not give accurate reasoning, but acceptable reasoning.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Also, this logic helps to deal with the uncertainty in engineering.<\/li>\n<\/ul>\n<\/div>\n<h3>Fuzzy Logic Systems Architecture<\/h3>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><span class=\"adverb\">Basically<\/span>, four parts <span class=\"passivevoice\">are shown<\/span> in the architecture of fuzzy logic system-<\/div>\n<\/div>\n<div class=\"\"><\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>a. Fuzzification Module<\/strong><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">We use this module to transform the system inputs. As tha is is crisp number. Also, helps in splitting the input signal into various five steps.<\/div>\n<\/div>\n<\/div>\n<div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>LP &#8211;\u00a0<\/strong>x is Large Positive.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>MP-\u00a0\u00a0<\/strong>x is Medium Positive.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>S &#8211;\u00a0<\/strong>x is Small.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>MN &#8211;\u00a0<\/strong>x is Medium Negative.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>LN &#8211;\u00a0<\/strong>x is Large Negative<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>b. Knowledge Base<\/strong><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">In this, we have to store it in IF-THEN rules that <span class=\"passivevoice\">was provided by<\/span> experts.<\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>c. Inference Engine<\/strong><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Generally, it helps in simulating the human reasoning process. That is by making fuzzy inference on the inputs and IF-THEN rules.<\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>d. Defuzzification Module<\/strong><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">In this module, we have to transform fuzzy set into a crisp value. That set <span class=\"passivevoice\">was obtained by<\/span> an inference engine.<\/div>\n<\/div>\n<div class=\"\"><\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Although, the membership functions always work on a same concept i.e fuzzy sets of variables.<\/div>\n<\/div>\n<\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">\n<div id=\"attachment_6131\" style=\"width: 640px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-6131\" class=\"wp-image-6131 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image.jpg\" alt=\"Fuzzy Logic Systems in Artificial Intelligence\" width=\"630\" height=\"341\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image.jpg 630w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image-150x81.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image-300x162.jpg 300w\" sizes=\"auto, (max-width: 630px) 100vw, 630px\" \/><\/a><p id=\"caption-attachment-6131\" class=\"wp-caption-text\">AI Fuzzy Logic &#8211; Defuzzification Module<\/p><\/div>\n<\/div>\n<div>\n<div class=\"\">\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Membership Function<\/h3>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">As this function allows you to quantify linguistic term. Also, represent a fuzzy set <span class=\"adverb\">graphically<\/span>. Although, MF for a fuzzy set A on the universe of discourse. That X <span class=\"passivevoice\">is defined<\/span> as \u03bcA:X \u2192 [0,1].<\/div>\n<\/div>\n<div class=\"\">\n<div><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">In this function, between a value of 0 and 1, each element of X <span class=\"passivevoice\">is mapped<\/span>. We can define it as the degree of membership. Also, it quantifies the degree of membership of the element. That is in X to the fuzzy set A.<\/div>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>x-axis<\/strong>&#8211; It represents the universe of discourse.<\/li>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>y-axis<\/strong> &#8211; It represents the degrees of membership in the [0, 1] interval.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">We can apply different membership functions to fuzzify a numerical value. Also, we use simple functions as complex. As they do not add more precision in the output.<\/div>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">We can define all membership functions for LP, MP, S, MN, and LN. That <span class=\"passivevoice\">is shown<\/span> as below \u2212<\/div>\n<\/div>\n<\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">\n<div id=\"attachment_6132\" style=\"width: 644px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image-2.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-6132\" class=\"wp-image-6132 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image-2.jpg\" alt=\"Fuzzy Logic Systems in Artificial Intelligence\" width=\"634\" height=\"329\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image-2.jpg 634w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image-2-150x78.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/image-2-300x156.jpg 300w\" sizes=\"auto, (max-width: 634px) 100vw, 634px\" \/><\/a><p id=\"caption-attachment-6132\" class=\"wp-caption-text\">Fuzzy Logic System &#8211; Membership Function<\/p><\/div>\n<\/div>\n<div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">There is some common triangular membership function as compared to other functions. Such as singleton, Gaussian. And trapezoidal.<\/div>\n<\/div>\n<div class=\"\">\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Fuzzy Logic Applications<\/h3>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">There are some areas of fuzzy logic system. These are-<\/div>\n<\/div>\n<div class=\"\">\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">a. Automotive Systems<\/h4>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Automatic Gearboxes<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Four-Wheel Steering<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Vehicle environment control<\/li>\n<\/ul>\n<h4>b. Consumer Electronic Goods<\/h4>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Hi-Fi Systems<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Photocopiers<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Still and Video Cameras<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Television<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">c. Domestic Goods<\/h4>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Microwave Ovens<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Refrigerators<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Toasters<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Vacuum Cleaners<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Washing Machines<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">d. Environment Control<\/h4>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Air Conditioners\/Dryers\/Heaters<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Humidifiers<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Advantages of Fuzzy Logic Systems<\/h3>\n<\/div>\n<div class=\"\">\n<ul>\n<li>Generally, in this system, we can take imprecise, distorted, noisy input information.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Also, these logics are easy to construct and understand.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Basically, it\u2019s solution to complex problems. Such as medicine.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Also, we can relate math in concept within fuzzy logic. Also, these concepts are very simple.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Due to the flexibility of fuzzy logic, we can add and delete rules in FLS system.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Disadvantages of Fuzzy Logic Systems<\/h3>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Till no designing approach to this fuzzy logic.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><span class=\"adverb\">Basically<\/span>, if logics are simple, then one can understand it.<\/li>\n<\/ul>\n<\/div>\n<div class=\"\">\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Also, suitable for problems which do not have high accuracy.<\/li>\n<\/ul>\n<p>So, this was all about\u00a0Fuzzy Logic systems in AI. Hope you like our explanation.<\/p>\n<\/div>\n<div class=\"\">\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Conclusion<\/h3>\n<\/div>\n<div class=\"\">\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Fuzzy logic helps AI make decisions when the answer isn\u2019t just \u201cyes\u201d or \u201cno.\u201d In real life, things are often in-between. For example, a room might be \u201ca little hot\u201d or \u201cslightly cold.\u201d Fuzzy logic lets AI understand these gray areas and act smartly\u2014like adjusting a fan speed to medium.<\/div>\n<div><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">This system is used in many smart devices. Washing machines use fuzzy logic to decide how long to wash based on dirt level. Cameras use it to focus better. Air conditioners use it to give comfort instead of just turning on or off. It\u2019s all about making machines act more like humans in unclear situations.<\/div>\n<div><\/div>\n<div class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Fuzzy logic is also used in medical tools, car controls, and even robots. It helps AI handle real-world problems where data is not always perfect. Instead of waiting for exact numbers, fuzzy logic lets machines make the best decision based on \u201chow much\u201d or \u201chow likely.\u201d It adds flexibility and realism to AI systems.<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>In this Fuzzy Logic Tutorial, we will learn What is\u00a0Fuzzy Logic Systems in Artificial Intelligence. Moreover, we will discuss the Application and Architecture of Fuzzy Logic in AI. Along with this, we will learn&#46;&#46;&#46;<\/p>\n","protected":false},"author":7,"featured_media":42246,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[1140,5010,5011,5012,15721],"class_list":["post-6112","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","tag-artificial-intelligence-fuzzy-logic-systems","tag-fuzzy-logic","tag-fuzzy-logic-and-application-in-a-i","tag-fuzzy-logic-in-a-i","tag-what-is-fuzzy-logic"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What is Fuzzy Logic Systems in AI - Architecture, Application - DataFlair<\/title>\n<meta name=\"description\" content=\"Learn What is Fuzzy Logic in AI, Architecture of Fuzzy Logic Systems, Applications of Fuzzy Logic in AI, Pros and cons of Fuzzy Logic\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/fuzzy-logic-systems\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What is Fuzzy Logic Systems in AI - Architecture, Application - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Learn What is Fuzzy Logic in AI, Architecture of Fuzzy Logic Systems, Applications of Fuzzy Logic in AI, Pros and cons of Fuzzy Logic\" \/>\n<meta property=\"og:url\" content=\"https:\/\/data-flair.training\/blogs\/fuzzy-logic-systems\/\" \/>\n<meta property=\"og:site_name\" content=\"DataFlair\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/DataFlairWS\/\" \/>\n<meta property=\"article:published_time\" content=\"2018-01-19T09:59:22+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-07-25T15:35:00+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Fuzzy-Logic-Systems-in-AI-01.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"628\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"DataFlair Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:site\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"DataFlair Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"5 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"What is Fuzzy Logic Systems in AI - Architecture, Application - DataFlair","description":"Learn What is Fuzzy Logic in AI, Architecture of Fuzzy Logic Systems, Applications of Fuzzy Logic in AI, Pros and cons of Fuzzy Logic","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/data-flair.training\/blogs\/fuzzy-logic-systems\/","og_locale":"en_US","og_type":"article","og_title":"What is Fuzzy Logic Systems in AI - Architecture, Application - DataFlair","og_description":"Learn What is Fuzzy Logic in AI, Architecture of Fuzzy Logic Systems, Applications of Fuzzy Logic in AI, Pros and cons of Fuzzy Logic","og_url":"https:\/\/data-flair.training\/blogs\/fuzzy-logic-systems\/","og_site_name":"DataFlair","article_publisher":"https:\/\/www.facebook.com\/DataFlairWS\/","article_published_time":"2018-01-19T09:59:22+00:00","article_modified_time":"2025-07-25T15:35:00+00:00","og_image":[{"width":1200,"height":628,"url":"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/01\/Fuzzy-Logic-Systems-in-AI-01.jpg","type":"image\/jpeg"}],"author":"DataFlair Team","twitter_card":"summary_large_image","twitter_creator":"@DataFlairWS","twitter_site":"@DataFlairWS","twitter_misc":{"Written by":"DataFlair Team","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"Article","@id":"https:\/\/data-flair.training\/blogs\/fuzzy-logic-systems\/#article","isPartOf":{"@id":"https:\/\/data-flair.training\/blogs\/fuzzy-logic-systems\/"},"author":{"name":"DataFlair Team","@id":"https:\/\/data-flair.training\/blogs\/#\/schema\/person\/beb0cab24b7aa54423a3b50e669a9dcd"},"headline":"What is Fuzzy Logic Systems in AI &#8211; 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