Questions tagged [fuzzy-logic]
Fuzzy logic is a variant of boolean logic, where the values are real numbers between 0 and 1 (inclusive), rather than only the integer numbers 0 and 1. Use this tag for questions that involve this real-valued logic.
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Algorithm Suggestion for Diverging Data (Severity/Intensity Analysis)
I have four datasets for four different accidents; each dataset has the same parameters. Some of the key parameters are changing their values from a "standard value". The more they change ...
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Improving Fuzzy Logic Control System Results
I am new to using skfuzzy and the use of fuzzy logic for classification, but the results I am getting are both good and bad for some conditions. I am aware of the overarching impact the ...
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Today's practicality of Neuro-Fuzzy Systems
I am questioning today's practicality of Neuro-Fuzzy Systems (NFS), which build upon Fuzzy logic, linguistic rules, ANFIS and "standard" reinforcement learning (see this paper for a nice ...
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Job Description Sentence Context Model
Working on a capstone.
Usecase: Optimizing for job descriptions.
Someone has a line on their LinkedIn (or CV) outlining their experience. This description may closely align and have a few synonyms for ...
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Does this property in product fuzzy logic have a name and any consequences?
In product fuzzy logic, the $AND$ operator of two variables $x_0$ and $x_1$ is the product $x_0x_1$.
Using the $NOT(x)$ as $1-x$, expressions for the other three minterms are easily obtained.
$$\...
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Why has statistics-based AI become more popular than other forms of AI?
What is the fundamental reason that statistics-based AI (e.g., ML and Neural Net) has become more popular than other forms of AI, e.g., Fuzzy Logic and rules-based AI (e.g., Prolog)?
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In this example of fuzzy c-means, what is the difference between "sigma" and "center" for the clusters?
In this example, what exactly do "Cluster" and "Sigma" mean? (They chose random coordinates for the three centroids of the groups)
Centers: Cluster centers, returned as a ...
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What approach would work well for predicting earthquake intensity based on historical data?
My problem: I own warning system where I collect data from institutions and send them over through various ways to users. I would like to hear your advice on what approach I can use for solving my ...
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How to calculate probability from fuzzy membership grade?
Suppose we have the fuzzy membership grade for a person $x$ with a set $S = \text{set of tall people}$ be $0.9$, i.e. $\mu_S(x)=0.9$.
Does this mean that the probability of person $x$ being tall is $0....
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Can someone explain and help to understand this fuzzy diagram?
Could someone help me to understand in detail each step of this fuzzy diagram, because I am lost?
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What is the difference between fuzzy neural networks and adaptive neuro fuzzy inference systems?
I have, like you see, just a general question about the combination of fuzziness and neural networks. I understood it as follows
Fuzzy neural networks as a hybrid system: the neural network helps me ...
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How do we determine the membership functions and values for this problem?
The goal of our project is to identify the quality of a grain and we have two values, A and B.
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How can I formulate a fuzzy inference system to approximate the tangent function?
Consider the function $f(x)=\tan(2x)$. How can I determine a fuzzy system that approximates $f(x)$? How to choose membership functions and how to determine fuzzy rules? Any help would be appreciated.
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How can I prove that all the a-cuts of any fuzzy set A defined on $R^n$ are convex?
How can I prove that all the a-cuts of any fuzzy set A defined on $R^n$
are convex if and only if
$$\mu_A(\lambda r + (1-\lambda)s) \geq min \{\mu_A(r), \mu_A(s)\}$$
such that $r, s \in R^n$, $\...
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The membership function of Consequents (Outputs) in Fuzzy classifier
The
problem in Iris data is to classify three species of iris (setosa, versicolor and virginica) by
four-dimensional attribute vectors consisting of
sepal length (x1)
sepal width (x2)
petal length (...
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What is the relationship between fuzzy logic and objective bayesian probability?
I understand fuzzy logic is a variant of formal logic where, instead of just 0 or 1, a given sentence may have a truth value in the [0..1] interval. Also, I understand that logical probability (...
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What is the role of the 'fuzzifier' w in Fuzzy Clustering?
According to my lecture, Fuzzy c-Means tries to minimize the following objective function:
$$J(X,B,U)=\sum_{i=1}^c\sum_{j=1}^n u_{ij}^w \, d^2(\vec{\beta_i},\vec{x_j})$$
where $X$ are the data ...
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Is fuzzy logic connected to neural networks?
Fuzzy logic is typically used in control theory and engineering applications, but is it connected fundamentally to classification systems?
Once I have a trained neural network (multiple inputs, one ...
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Choice of fuzzification function
I'm a relative newbie to fuzzie logic systems but I have some knowledge in mathematics. I have the following problem:
I want to fuzzify certain values. Some are in the range [-$\inf$,$\inf$] and some ...
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Why did fuzzy logic fall out of fashion?
Fuzzy logic seemed like an active area of research in machine learning and data mining back when I was in grad school (early 2000s). Fuzzy inference systems, fuzzy c-means, fuzzy versions of the ...
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Defining formula for fuzzy equation
I'm learning fuzzy logic and more or less understand the basic concept, but i'm having a hard time understanding how to apply it to a method. I tried browsing online for explanation on how to use it, ...
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Fuzzy confusion matrix for fuzzy classifier
Let us suppose I have a NxN matrix and I want to classify in M classes each entry of the matrix using a fuzzy classifier. The ...
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Tuning the b parameter, ANFIS
In order for the generalized bell membership function to retain its defined shape and domain, two restrictions must be placed on the b parameter: 1) b must be positive and 2) b must be an integer. ...
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Are there real applications of fuzzy logic?
This question covers in detail, what fuzzy logic is and how it relates to other math fields, such as boolean algebra and sets theory.
This question is also very related, but the answers are focused ...
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How do we decide which membership function to use?
In classical set theory, there are two options for an element. It is either a member of a set or not. But in fuzzy set theory, there are membership functions to define the "rate" of an ...
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How to determine the probability of an "existence" question
I am having a go at creating a program that does math like a human. By inventing statements, assigning probabilities to statements (to come back and think more deeply about later). But I'm stuck at ...
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How can fuzzy logic be used in creating AI?
Fuzzy logic is the logic where every statement can have any real truth value between 0 and 1.
How can fuzzy logic be used in creating AI? Is it useful for certain decision problems involving multiple ...
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What is fuzzy logic?
I'm new to A.I. and I'd like to know in simple words, what is the fuzzy logic concept? How does it help, and when is it used?
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