fuzzy-logic | 易学教程

Multikey Multivalue Non Deterministic python dictionary

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问题 There is already a multi key dict in python and also a multivalued dict. I needed a python dictionary which is both: example: # probabilistically fetch any one of baloon, toy or car d['red','blue','green']== "baloon" or "car" or "toy" Probability of d['red']==d['green'] is high and Probability of d['red']!=d['red'] is low but possible the single output value should be probabilistically determined (fuzzy) based on a rule from keys eg:in above case rule could be if keys have both "red" and

PHP - Finding number of matching words between two pieces of text?

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I want to find number of similar words between two texts Example $str1=the cat is on the roof $str2=the mouse is on the roof the,is,on,the,roof words are similar in $str1 and $str2 So output will be in number 5 OR In percentage 86% I am try similar_text() function but this function not work as which i want. Easy, explode them and then use array_diff: $totalWords = count($array_1); $array_1 = explode(" ", $str1); $array_2 = explode(" ", $str2); $differenceCount = count(array_diff($array_1, $array_2)); $differentPercent = $differenceCount / ($totalWords / 100); @Edit: Edited code above to

Fuzzy Logic Implementation In Android

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How to add jfuzzy lite library in android? Anybody who feels problem in implementing Fuzzy Library in Android can easily view my project in Git address which i mentioned here: https://github.com/susylPearl/RNA For successfully completion of the project follow below steps: Download Fuzzylite library from www.fuzzylite.com/downloads After then import it in your project as it is jar file. Then make assets folder and inside it create file with .fcl extension and copy .fcl code for your project, you can view mine here: https://github.com/susylPearl/RNA/blob/RNA/app/src/main/assets/tipper.fcl After

Find Match of two data frames and rewrite the answer as data frame

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i have two data frames which are cleaned and merged as a single csv file , the data frames are like this **Source Master** chang chun petrochemical CHANG CHUN GROUP chang chun plastics CHURCH AND DWIGHT CO INC church dwight CITRIX SYSTEMS ASIA PACIFIC P L citrix systems pacific CNH INDUSTRIAL N.V now from these , i have to consider the first name and check with each name of master names and find a match that is relevant and print the output as another data frame. the above data frames are few , but i am working with 20k values as such. My output must look like this **Source Master Result**

What is fuzzy logic?

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I'm working with a couple of AI algorithms at school and I find people use the words Fuzzy Logic to explain any situation that they can solve with a couple of cases. When I go back to the books I just read about how instead of a state going from On to Off it's a diagonal line and something can be in both states but in different "levels". I've read the wikipedia entry and a couple of tutorials and even programmed stuff that "uses fuzzy logic" (an edge detector and a 1-wheel self-controlled robot) and still I find it very confusing going from Theory to Code... for you, in the less complicated

Find Match of two data frames and rewrite the answer as data frame

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问题 i have two data frames which are cleaned and merged as a single csv file , the data frames are like this **Source Master** chang chun petrochemical CHANG CHUN GROUP chang chun plastics CHURCH AND DWIGHT CO INC church dwight CITRIX SYSTEMS ASIA PACIFIC P L citrix systems pacific CNH INDUSTRIAL N.V now from these , i have to consider the first name and check with each name of master names and find a match that is relevant and print the output as another data frame. the above data frames are few

Joining two datasets using fuzzy logic

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问题 I’m trying to do a fuzzy logic join in R between two datasets: first data set has the name of a location and a column called config second data set has the name of a location and two additional attributes that need to be summarized before they are joined to the first data set. I would like to use the name column to join between the two data sets. However the name column may have additional or leading characters in either data set or have one word contained inside of a larger word. So for