Rheumatoid Arthritis (Ra) Using Hybrid Artificial Bee Colony (Hyarbc) of Fuzzy Cognitive Map (Fcm) (Hyarbc-Fcm) With Gene Datasets

Authors

  • Dr.R. Rajeswari Assistant Professor, Dr.N.G.P Arts and Science College, Coimbatore, Tamil Nadu, India. Author
  • Dr.M. Subhashini Associate Professor, St.Peter’s Institute of Hig.Edu. & Research, Chennai, Tamil Nadu, India. Author
  • Padma Priya R.S. Assistant Professor, Dr.N.G.P Arts and Science College, Coimbatore, Tamil Nadu, India Author

DOI:

https://doi.org/10.61841/n1grwf75

Keywords:

Mobile Computing, Pervasive Computing, Urban Development, Virtual Reality, Mobile Crowd Sourcing Technologies.

Abstract

Rheumatoid arthritis (RA) is a severe autoimmune syndrome that damages both the joints and muscles of the body and can lead to disruption of joints and their function. Initial prediction of RA is very significant for avoiding the progression of the disease. Single Nucleotide Polymorphism (SNP) techniques utilize RA biomarkers to show the importance of the outputs. The major target of this study is to build a prediction of Hybrid Artificial Bee Colony (HYARBC) of Fuzzy Cognitive Map (FCM) (HYARBC-FCM) technique that identifies the crucial part of RA taking the medical experts knowledge into consideration and further experience with the help of HYARBC and FCM methods to easily predict the RA for the purpose of gene profiles. This work uses the type named decision support, which is built for the diagnostic process of RA with gene expression using HYARBC and the soft computational method of FCM. The FCM type is constructed by the HYARBC technique. There is a possibility of stabilizing the predetermined FCM topology and determining weights as per the stated topology. The changes carried out in the HYARBC algorithm have two significant aspects. Initially, the local search is guided efficiently by the data from the global optimal outputs and its gradient as a step-by-step process. The global optimal output provides maximum efficiency of the ABC algorithm by losing its diversity. Following that, with the inspiration of genetic algorithms, the resource nectar is converted into an innovative matrix with the process of selection. The nectar resource is converted into an innovative adjacency matrix with 3 processes, namely selection, crossover, and mutation, that produce diversity of individuals and utilization of prior adjacency matrices for enhancing the broad search capability of the ABC technique. It is possible to elaborate on the general correlation between the significant concepts that identify the system’s behavior dynamically. Meanwhile, RA issues can be avoided by passing through modern phases, and the risk of building persistent and erosive arthritis for these victims would be minimized. 

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Published

31.07.2020

How to Cite

R. , R., M. , S., & R.S. , P. P. (2020). Rheumatoid Arthritis (Ra) Using Hybrid Artificial Bee Colony (Hyarbc) of Fuzzy Cognitive Map (Fcm) (Hyarbc-Fcm) With Gene Datasets. International Journal of Psychosocial Rehabilitation, 24(5), 1730-1741. https://doi.org/10.61841/n1grwf75