Determination of Diagnostic Factors for Different Domains Using FDMML Techniques

Authors

  • R. Suguna Research Scholar, Sri Sarada College for Women (Autonomous), Salem-16.
  • R. Uma Rani Principal Sri Sarada College for Women (Autonomous), Salem-16.

Keywords:

Diagnostics analytics, correlations, machine learning, autism, rainfall, child abuse

Abstract

There are numerous factors that contribute to each problem in research criteria. Diagnose problems using diagnostic analytics to find causes and solutions. DA supports finding solutions and advancing science for the benefit of future generations. In this paper, there are three kinds of data have selected, which are essential and solutions needed in the future. Autism is one of the medical data which is increasing every year in India. Rainfall data is an agricultural data, which is a main need for earth. Child abusing is the social relevant data, which should be considered earnestly in our India. Diagnostic analytics can be attained through some of statistical techniques such as correlation, hypothesis testing and regression techniques. The three types of data's proposed factors are analysed using historical research and computational intelligence methodologies. Effective fuzzy rules are generated for the diagnosed factors.

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Diagnosing factors for different domains

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Published

17.05.2023

How to Cite

Suguna, R. ., & Rani, R. U. . (2023). Determination of Diagnostic Factors for Different Domains Using FDMML Techniques. International Journal of Intelligent Systems and Applications in Engineering, 11(6s), 107–113. Retrieved from https://www.ijisae.org/index.php/IJISAE/article/view/2833

Issue

Vol. 11 No. 6s (2023)

Section

Research Article

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