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DOI: http://dx.doi.org/10.22266/ijies2017.0430.08

Multi Agent Based Diabetes Diagnosing and Classification with the Aid of Hybrid Firefly-Neural Network

Author(s):

Kiran Tangod1*, Gururaj Kulkarni2


Affiliations:

1Gogte Institute of Technology, Belagavi, Karnataka, India
2Jain College of Engineering, Belagavi, Karnataka, India







Abstract:

A multi agent distributed data mining system for diagnosing diabetes and classification is proposed. Here we are introducing four agents namely user agent, connection agent, updation agent, and security agent. In which each agent performs their own task under the coordination of the connection agent. The user agent collects the user symptoms in order to predict the patient status also the knowledge based of the system. Updation agent is responsible for prescribing drugs for the patient. For secure communication, the proposed technique introduces one security agent between connection agent and updation agent. Here the user symptoms are encrypted by means of advanced encryption standard (AES). Finally, updation agent is classifying the user symptoms and then evaluates the diabetes level with the help of hybrid firefly based neural network algorithm. The performance of the proposed system will acquire with the classification accuracy. The proposed method will be implemented in JAVA platform.


Keywords:

Multi agent diabetes, Advanced encryption standard, Artificial neural network and firefly optimization.


Full Text:




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