Recognition efficiency enhancement of control chart pattern using ensemble MLP neural network

https://doi.org/10.53730/ijhs.v6nS3.6851

Authors

  • Sapna Kadakadiyavar Associate professor, Department of Electronics and Communication Engineering, Sambhram institute of technology, M.S.Palya, Bangalore-560097
  • Achyutha Prasad N. Professor, Department of Computer Science and Engineering, East West Institute of Technology, Bengaluru, Karnataka, India
  • Piyush Kumar Pareek Professor(CSE) and Head(IPR CELL), Dept. of Computer Science & Engineering,Nitte Meenakshi Institute of Technology, Yelahanka, Bengaluru-560064, Karnataka, India
  • Vani V. Professor, Department of Computer Science and Engineering, Nitte Meenakshi Institute of Technology, Bangalore, Karnataka, India
  • Rekha V. S. Assistant Professor, Department of Computer Science and Engineering Dayananda Sagar Academy of Technology and Management, Bengaluru
  • Nirmala G. Assistant Professor, Department of Computer Science and Engineering, Sri Siddhartha Institute of Technology, Tumakuru

Keywords:

control chart patter, pattern recognition, artificial neural network, ensemble

Abstract

chart pattern for six different fundamental patterns have been proposed. The multilayer perceptron based neural network has applied as an entity to form the ensemble. The loss of generalization property of an individual neural network has been fulfilled by providing the diversity in the training data for the individual entity of ensemble. The outcome of individual recognizer has combined over their decision value to include the outcome knowledge of each and every entity instead of majority voting of decision. The proposed method has been verified over a large set of data experimentally and observed that there is significant improvement with proposed ensemble approach in compare to individual recognizer.

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Published

01-05-2022

How to Cite

Kadakadiyavar, S., Prasad, A. N., Pareek, P. K., Vani, V., Rekha, V. S., & Nirmala, G. (2022). Recognition efficiency enhancement of control chart pattern using ensemble MLP neural network. International Journal of Health Sciences, 6(S3), 4295–4306. https://doi.org/10.53730/ijhs.v6nS3.6851

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