Fuzzy Reinforcement Learning using Neural Network: An Application to Medical Diagnosis and Business Intelligence

Poli Venkata Subba Reddy

Fuzzy Reinforcement Learning using Neural Network: An Application to Medical Diagnosis and Business Intelligence

Poli Venkata Subba Reddy * §

Contact

§ Sri Venkateswara University, Tirupati

Fuzzy Reinforcement Learning using Neural Network: An Application to Medical Diagnosis and Business Intelligence

Article Fingerprint

ReserarchID

CSTA2HU4

Fuzzy Reinforcement Learning using Neural Network: An Application to Medical Diagnosis and Business Intelligence Banner

Key Research Insights

Synthesized scholarly intelligence & interactive research assistant

This converted HTML version may contain rendering inconsistencies. Please refer to the PDF for the authoritative version, or click here to provide feedback.

Abstract

The information available to the system is incomplete in many applications, particularly in Decision Support Systems. The fuzzy logic deals incomplete information with belief rather than likelihood (probability). Sometimes the decision has to be taken with fuzzy information. In this paper, fuzzy machine learning is studied for decision support systems. The fuzzy Decision set is defined with two-fold fuzzy set. The fuzzy inference is studied with fuzzy neural network for fuzzy Decision sets. Business application is given as application.

References

13 Cites in Article

Reference Format

B Buchanan,E Shortliffe (1984). Rule-Based Expert System: The MYCIN Experiments of the Stanford Heuristic Programming Project, Readings.
E Mamdani,S Assilian (1975). An experiment in linguistic synthesis with a fuzzy logic controller.
Witold Pedrycz,Fernando Gomide (1998). An Introduction to Fuzzy Sets.
Ping Ren (1990). Generalized fuzzy set s and Representation of Incomplete Knowledge.
N Rescher (1969). Many-Valued Logic.
Glenn Shafer (1976). A Mathematical Theory of Evidence.
Poli Venkata,Subba Reddy,M Babu (1992). Some Methods of Reasoning for Conditional Propositions.
P Venkata Subba,Reddy (1993). Some Methods of Fuzzy Conditional Inference for Application to Fuzzy Control Systems.
Poli Venkata,Subba Reddy (2013). Generalized fuzzy logic for Incomplete Information.
L Zadeh (1975). CALCULUS OF FUZZY RESTRICTIONS.
L Zadeh (1965). Fuzzy sets.
Lotfi Zadeh (2006). Generalized theory of uncertainty (GTU)—principal concepts and ideas.
Lotfi Zadeh (1994). Fuzzy logic, neural networks, and soft computing.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Poli Venkata Subba Reddy. 2021. "Fuzzy Reinforcement Learning using Neural Network: An Application to Medical Diagnosis and Business Intelligence". Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 21 (GJCST Volume 21 Issue D2).

More Citation Formats

Select Citation Style:

Download Citation

GJCST Volume 21 Issue D2

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Not Found

Classification

GJCST-D Classification F.1.1

Submission ReceivedJune 11, 2021
Peer Review Double Blind
Handling Editor
Accepted July 1, 2021
Published July 15, 2021

Version of record

v1.2

Issue date

September 1, 2021

Language

English

Order Article Reprint

Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Views: 1.4K

Total Downloads: 91

All Trends