Models for route choice behavior in the presence of information using concepts from fuzzy set theory and approximate reasoning

1993 ◽  
Vol 20 (2) ◽  
pp. 129-155 ◽  
Author(s):  
Tsippy Lotan ◽  
Haris N. Koutsopoulos
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Choice Behavior ◽  
Route Choice ◽  
Approximate Reasoning ◽  
Route Choice Behavior

HEDGE ALGEBRAS, LINGUISTIC-VALUE LOGIC AND THEIR APPLICATION TO FUZZY REASONING

1999 ◽  
Vol 07 (04) ◽  
pp. 347-361 ◽  
Author(s):  
CAT HO NGUYEN ◽  
DINH KHANG TRAN ◽  
HUYNH VAN NAM ◽  
HAI CHAU NGUYEN
Keyword(s):  
Fuzzy Control ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Fuzzy Model ◽  
Fuzzy Reasoning ◽  
Approximate Reasoning ◽  
Linguistic Terms ◽  
Natural Languages ◽  
The Given

People use natural languages to think, to reason, to deduce conclusions, and to make decisions. Fuzzy set theory introduced by L. A. Zadeh has been intensively developed and founded a computational foundation for modeling human reasoning processs. The contribution of this theory both in the theoretical and the applied aspects is well recognized. However, the traditional fuzzy set theory cannot handle linguistic terms directly. In our approach, we have constructed algebraic structures to model linguistic domains, and developed a method of linguistic reasoning, which directly manipulates linguistic terms, In particular, our approach can be applied to fuzzy control problems. In many applications of expert systems or fuzzy control, there exist numerous fuzzy reasoning methods. Intuitively, the effectiveness of each method depends on how well this method satisfies the following criterion: the similarity degree between the conclusion (the output) of the method and the consequence of an if-then sentence (in the given fuzzy model) should be the "same" as that between the input of the method and the antecedent of this if-then sentence. To formalize this idea, we introduce a "measure function" to measure the similarity between linguistic terms in a domain of any linguistic variable and to build approximate reasoning methods. The resulting comparison between our method and some other methods shows that our method is simple and more effective.

scholarly journals A Theory of Approximate Reasoning with Type-2 Fuzzy Set

2021 ◽  
Vol 27 (1) ◽  
pp. 9-28
Author(s):  
Sudin Mandal ◽  
Injamam Ul Karim ◽  
Swapan Raha
Keyword(s):  
Fuzzy Logic ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Residuated Lattice ◽  
Approximate Reasoning ◽  
Truth Values ◽  
Logic Structure

In this paper, an attempt is made to study approximate reasoning based on a Type-2 fuzzy set theory. In the process, we have examined the underlying fuzzy logic structure on which the reasoning is formulated. We have seen that the partial/incomplete/imprecise truth-values of elements of a type-2 fuzzy set under consideration forms a lattice. We propose two new lattice operations which ultimately help us to define a residual and thereby making the structure of truth- values a residuated lattice. We have focused upon two typical rules of inference used mostly in ordinary approximate reasoning methodology based on Type-1 fuzzy set theory. Our proposal is illustrated with typical artificial examples.

AN ANALYSIS OF TRUCKS' ROUTE CHOICE BEHAVIOR CONSIDERING VEHICLE TYPE AND TRIP LENGTH

2018 ◽  
Vol 74 (5) ◽  
pp. I_657-I_666
Author(s):  
Hideki OKA ◽  
Makoto CHIKARAISHI ◽  
Jun TANABE ◽  
Daisuke FUKUDA ◽  
Takashi OGUCHI
Keyword(s):  
Choice Behavior ◽  
Route Choice ◽  
Trip Length ◽  
Vehicle Type ◽  
Route Choice Behavior
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