Volume 11 - Volume 11
Non Homogeneous Rough Finite State Automaton
Abstract
Objective: The study of finite state automaton is an essential tool in machine learning and artificial
intelligence. The class of rough finite state automaton captures the uncertainty using the rough
transition map. The need to generalize this concept arises to adhere the dynamical behaviour of the
system. Hence this paper focuses on defining non-homogeneous rough finite state automaton.
Methodology: With the aid of Rough finite state automata we define the concept of non-homogeneous rough finite state automata. Findings: Non homogeneous Rough Finite State Automata (NRFSA) is defined by a tuple The dynamical behaviour of any system can be expressed in terms of an information system at time t. This leads us to define non-homogeneous rough finite state automaton. For each time ‘t’ we generate lower approximation rough finite state automaton and the defined concepts are elaborated with suitable examples. The ordered pair, and the upper approximation rough finite state automaton is called as the non-homogeneous rough finite state automaton. Conclusion: Over all our study reveals the characterization of the system which changes its behaviour dynamically over a time ‘t’. Novelty: The novelty of the proposed article is that it clearly immense the system behaviour over a time ‘t’. Using this concept the possible and the definite transitions in the system can be calculated in any given time ‘t’.
Paper Details
PaperID: 1700
Author's Name: B. Praba and R. Saranya
Volume: Volume 11
Issues: Volume 11
Keywords: Information System, Rough Set, Automata, Language Generated by an Automaton.
Year: 2021
Month: April
Pages: 629-641