Book ChapterDOI
Interpretation and execution of fuzzy programs
C.L. Chang
- pp 191-218
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TLDR
In this paper, a fuzzy program is defined through a flowchart where each arc is associated with a fuzzy relation (called a fuzzy branching condition) and a fuzzy assignment and the execution of the fuzzyprogram is equivalent to searching a solution path in the tree, i.e., tree searching.Abstract:
In this paper, a fuzzy program is defined through a flowchart where each arc is associated with a fuzzy relation (called a fuzzy branching condition) and a fuzzy assignment. Input, program and output variables occurring in a fuzzy program represent fuzzy subsets. A fuzzy program is interpreted as implicitly defining a tree; and the execution of the fuzzy program is equivalent to searching a solution path in the tree, i.e., tree searching. Examples of fuzzy programs and their executions are given.read more
Citations
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Journal ArticleDOI
PRUF—a meaning representation language for natural languages
TL;DR: In addition to serving as a foundation for approximate reasoning, PRUF may be employed as a language for the representation of imprecise knowledge and as a means of precisiation of fuzzy propositions expressed in a natural language.
Book ChapterDOI
Fuzzy Mathematical Programming
TL;DR: Fuzzy linear programming belongs to goal programming in the sense that implicitly or explicitly aspiration levels have to be defined at which the membership functions of the fuzzy sets reach their maximum or minimum.
BookDOI
User Interface Management Systems
TL;DR: In this paper, the authors proposed a DEVICE-DEVICE DEVC DEVICE DEVICE (Device-Device-Device Discrete Controller) for autonomous driving systems and demonstrated its performance.
Journal ArticleDOI
Applications of fuzzy set theory to mathematical programming
TL;DR: This paper surveys major models and theories in this area of fuzzy set theory and offers some indication on future developments which can be expected.
Book ChapterDOI
Local and fuzzy logics
Richard Bellman,Lotfi A. Zadeh +1 more
TL;DR: Fuzzy logic differs from conventional logical systems in that it aims at providing a model for approximate rather than precise reasoning as mentioned in this paper, and it can be seen as a form of probabilistic reasoning.
References
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Journal ArticleDOI
Outline of a New Approach to the Analysis of Complex Systems and Decision Processes
TL;DR: By relying on the use of linguistic variables and fuzzy algorithms, the approach provides an approximate and yet effective means of describing the behavior of systems which are too complex or too ill-defined to admit of precise mathematical analysis.
Journal ArticleDOI
The structure of ill structured problems
TL;DR: Reviews of the state of the professional practice in Requirements Engineering stress that the RE process is both complex and hard to describe, and suggest there is a significant difference between competent and "approved" practice.
Book ChapterDOI
Hedges: A Study In Meaning Criteria And The Logic Of Fuzzy Concepts
TL;DR: Students of language, especially psychologists and linguistic philosophers, have long been attuned to the fact that natural language concepts have vague boundaries and fuzzy edges and that, consequently, natural language sentences will very often be neither true, nor false, nor nonsensical.
Journal ArticleDOI
Quantitative fuzzy semantics
TL;DR: In this paper, the authors define a language, L, as a fuzzy relation from a set of terms, T = x, to a universe of discourse, U = y, and define a fuzzy set, M(x), in U whose membership function is given by @m"M" ("x")(y) =@m"L(x,y).
Journal ArticleDOI
On the Execution of Fuzzy Programs Using Finite-State Machines
TL;DR: An abstract model for the execution of fuzzy programs using finite-state machines is described and it is shown that the performance function λ of a fuzzy machine M can be effectively constructed so that the program searching cost of an elementary fuzzy program, a number of elementary fuzzy programs, or a regular fuzzy program is minimized.