English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In time diagnosis of diabetes significantly reduces damages and inconveniences of this disease in society. It may be said that one of the most important problems of diagnosis methods of this disease, particularly in early phases, is not to pay attention to proper features in order to diagnose the disease and as a result weakness in disease diagnosis. This research endeavors to introduce a new method for accurate diagnosis of this disease through usage of a combination of artificial intelligent methods such as fuzzy systems for immediate and accurate decision making, Evolutionary Algorithms (ACO) for choosing best rules in fuzzy systems, and artificial neural networks for modeling, structure identification, and parameter identification. The proposed system relying on features of database in the form of combination and interaction succeeded in reaching an accuracy of 95.852% which in comparison to current methods on the one hand and to artificial methods in foresaid references on the other hand, has a proper and very faster performance than other intelligent methods and you can see its accuracy and excellence as an intelligent system.

journal of mathematics and computer science

Introduction Of A Method To Diabetes Diagnosis According To Optimum Rules In Fuzzy Systems Based On Combination Of Data Mining Algorithm (d-t), Evolutionary Algorithms (aco) And Artificial Neural Networks (nn)