A new approach for tuning interval type-2 fuzzy knowledge bases using genetic algorithms

Shukla, Praveen Kumar; Tripathi, Surya Prakash

doi:10.1186/2195-5468-2-4

Cited by 21 publications

(12 citation statements)

References 65 publications

(45 reference statements)

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“…This is called the interpretability-accuracy trade-off [6,8,14]. Few of the knowledge base systems are also developed in advanced fuzzy methods, like interval type-2 fuzzy sets [7,13].…”

Section: Related Workmentioning

confidence: 99%

Social Perception Grading of Hospitals using Fuzzy Knowledge Base Systems

Karn

Darbari

Shukla³

2017

Fifth International Conference on Advances in Computing, Communication and Information Technology - CCIT 2017

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Abstract.Proper health is an important parameter to ensure the socioeconomic development of the country. Hospitals are playing vital role to improve the health standards in the life and serves the society very effectively. The assessment of quality and ease of medical facilities provided by the hospitals is an important research line. The higher quality of medical care improves the patient satisfaction leading to social perception enhancement. In this paper, we are investigating a new Expert System to assess the quality of medical care of any hospital depending on few parameters. The system is developed using fuzzy knowledge based systems and implemented in Guaje. The system would be generating the grades of different hospitals as per the quality care provided by them.

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“…This is called the interpretability-accuracy trade-off [6,8,14]. Few of the knowledge base systems are also developed in advanced fuzzy methods, like interval type-2 fuzzy sets [7,13].…”

Section: Related Workmentioning

confidence: 99%

Social Perception Grading of Hospitals using Fuzzy Knowledge Base Systems

Karn

Darbari

Shukla³

2017

Fifth International Conference on Advances in Computing, Communication and Information Technology - CCIT 2017

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“…It is worth to mention that there are many papers that focus on reviewing methods that concentrate on interpretability and interpretability-accuracy trade-off (see e.g. [1,30,86,87]). For example, in [30] authors are focused on splitting types of methods in the context of interpretability into following quadrants of interpretability: (a) complexity at the rule base level (it refers to i.e.…”

Section: Introductionmentioning

confidence: 99%

“…In the area of those research is worth to list methods focused on: (a) Definition and implemention of new criteria of interpretability of fuzzy rules (see e.g. [1,30,86,87]). (b) Appropriate aggregation of those criteria (see e.g.…”

Section: Introductionmentioning

confidence: 99%

A New Interpretability Criteria for Neuro-Fuzzy Systems for Nonlinear Classification

Łapa

Cpałka

Galushkin

2015

Artificial Intelligence and Soft Computing

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Abstract. In this paper a new approach for construction of neuro-fuzzy systems for nonlinear classification is introduced. In particular, we concentrate on the flexible neuro-fuzzy systems which allow us to extend notation of rules with weights of fuzzy sets. The proposed approach uses possibilities of hybrid evolutionary algorithm and interpretability criteria of expert knowledge. These criteria include not only complexity of the system, but also semantics of the rules. The approach presented in our paper was tested on typical nonlinear classification simulation problems.

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“…4]. Fuzzy techniques are basically the extended version of binary logic and support the concept of multi-valued logic [5]. Fuzzy logic is also used to implement Knowledge Based System or FRBS in which the form of knowledge representation is if then rules [6,7,8].…”

Section: Introductionmentioning

confidence: 99%

Interpretability and Accuracy Analysis of Fuzzy Rule Based System Designed for Abalone

Chandra*,

Agarwal,

Shukla

2020

IJRTE

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 Abstract: Fuzzy Rule Based Systems are playing vital role in the implementation of human decision making. The development of interpretable Fuzzy Rule Based Systems with improved accuracy is a crucial research aspect in fuzzy based systems. Mamdani type fuzzy rule based systems are used to implement the proposed model. In this manuscript a FRBS is implemented with Guaje Open-Access Java based software. The interpretability and accuracy assessments are recorded on the different experiments with various rule generation methods, like Fuzzy decision tree and Wang Mendel method. The results are found satisfactory and a trade-off is handled between interpretability and accuracy. The major concern of the experimentation is number and type of fuzzy partitions. K-means and Hierarchical Fuzzy Partitions are used in the experiments with three and five number of fuzzy partitions.

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A new approach for tuning interval type-2 fuzzy knowledge bases using genetic algorithms

Cited by 21 publications

References 65 publications

Social Perception Grading of Hospitals using Fuzzy Knowledge Base Systems

Social Perception Grading of Hospitals using Fuzzy Knowledge Base Systems

A New Interpretability Criteria for Neuro-Fuzzy Systems for Nonlinear Classification

Interpretability and Accuracy Analysis of Fuzzy Rule Based System Designed for Abalone

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