fuzzy-logic

Using fuzzy logic toolbox on Octave

由 我怕爱的太早我们不能终老 提交于 2019-12-11 15:49:03
问题 I've install Octave and the fuzzy logic toolkit to work with Fuzzy Inference Systems. pkg install fuzzy-logic-toolkit-0.4.5.tar.gz For information about changes from previous versions of the fuzzy-logic-toolkit package, run 'news fuzzy-logic-toolkit'. >> pkg list Package Name | Version | Installation directory ---------------------+---------+----------------------- fuzzy-logic-toolkit | 0.4.5 | /home/bgarcial/octave/fuzzy-logic-toolkit-0.4.5 But ... How to can I use the toolkit? I type pkg

Using fuzzylite in Visual Studio 2010

由 随声附和 提交于 2019-12-11 09:43:49
问题 Has anyone done this before ? I am not able to get it to work. Following are my steps: Download the windows package from link I can run qfuzzylite (gui-tool) without any problem. Now I want to use the fuzzylite lib in my Visual Studio + Qt Integration Project. In the CMake GUI I give fuzzylite source folder as the input folder and select Visual Studio 2010 as the compiler. I am able to generate the Visual Studio fuzzylite solution in CMake without any errors. Then, I tried to build the Visual

Fuzzy Logic / matching on Company Name (leads)

由 六月ゝ 毕业季﹏ 提交于 2019-12-11 06:48:12
问题 I have looked at conventional methods of using De-Duping tools however because I work for an organisation which is multi alliance the de-duping tool looks at the entire database, when I actually need to look at segments of the database, so I have decided to try and create my own de-duping tool. So far I have created the following apex . The apex currently looks at the company name on the lead and if there is an exact match with another company name in the database it provide the user the

Fuzzy logic on big datasets using Python

由 烈酒焚心 提交于 2019-12-06 07:14:08
问题 My team has been stuck with running a fuzzy logic algorithm on a two large datasets. The first (subset) is about 180K rows contains names, addresses, and emails for the people that we need to match in the second (superset). The superset contains 2.5M records. Both have the same structure and the data has been cleaned already, i.e. addresses parsed, names normalized, etc. ContactID int, FullName varchar(150), Address varchar(100), Email varchar(100) The goal is to match values in a row of

elasticsearch fuzzy matching max_expansions & min_similarity

由 懵懂的女人 提交于 2019-12-05 10:39:54
问题 I'm using fuzzy matching in my project mainly to find misspellings and different spellings of the same names. I need to exactly understand how the fuzzy matching of elastic search works and how it uses the 2 parameters mentioned in the title. As I understand the min_similarity is a percent by which the queried string matches the string in the database. I couldn't find an exact description of how this value is calculated. The max_expansions as I understand is the Levenshtein distance by which

F# and Fuzzy Logic

由 人盡茶涼 提交于 2019-12-04 18:48:08
问题 I know it might sound strange but I would like to know one thing in this new world where Microsoft Visual F# is getting into. There are many application of this language, I am going to learn, regarding parsing, functional programming, structured programming... But what about artificial intelligence? Are there any applications for Fuzzy Logic? Is F# a good language to be used for Fuzzy Logic applications? At university we are studying Prolog and similar languages. Prolog is able to create

Fuzzy logic in java

由 元气小坏坏 提交于 2019-12-04 12:21:15
I have been given a new project module which involves fuzzy logic. It is to determine different Hydrometeors using fuzzy logic method.I have very little idea about what fuzzy logic is. So I would like to have some advice from people who have already done projects using fuzzy logic in Java (like what are the basic programming strategies I can adopt). I have come across a fuzzy logc API . People who have used it please comment on how useful it is. Fuzzy logic is an abstract concept that is completely independant of programming lanuages. The basic idea is that instead of boolean logic where any

elasticsearch fuzzy matching max_expansions & min_similarity

由 泪湿孤枕 提交于 2019-12-03 22:57:40
I'm using fuzzy matching in my project mainly to find misspellings and different spellings of the same names. I need to exactly understand how the fuzzy matching of elastic search works and how it uses the 2 parameters mentioned in the title. As I understand the min_similarity is a percent by which the queried string matches the string in the database. I couldn't find an exact description of how this value is calculated. The max_expansions as I understand is the Levenshtein distance by which a search should be executed. If this actually was Levenshtein distance it would have been the ideal

SQL Fuzzy Join - MSSQL

由 梦想的初衷 提交于 2019-12-03 20:57:25
I have two sets of data. Existing customers and potential customers. My main objective is to figure out if any of the potential customers are already existing customers. However, the naming conventions of customers across data sets are inconsistent. EXISTING CUSTOMERS Customer / ID Ed's Barbershop / 1002 GroceryTown / 1003 Candy Place / 1004 Handy Man / 1005 POTENTIAL CUSTOMERS Customer Eds Barbershop Grocery Town Candy Place Handee Man Beauty Salon The Apple Farm Igloo Ice Cream Ride-a-Long Bikes I would like to write some type of select statement like below to reach my objective: SELECT a

F# and Fuzzy Logic

由 泪湿孤枕 提交于 2019-12-03 12:55:15
I know it might sound strange but I would like to know one thing in this new world where Microsoft Visual F# is getting into. There are many application of this language, I am going to learn, regarding parsing, functional programming, structured programming... But what about artificial intelligence? Are there any applications for Fuzzy Logic? Is F# a good language to be used for Fuzzy Logic applications? At university we are studying Prolog and similar languages. Prolog is able to create complex query in a very plain and short expresisons (by taking advantage of predicates and facts). Is F#
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