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Kalman Filtering Based Fuzzy C-Means Clustering and Artificial Neural Network for Classification of Microarray Data

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Applications of Robotics in Industry Using Advanced Mechanisms (ARIAM 2019)

Part of the book series: Learning and Analytics in Intelligent Systems ((LAIS,volume 5))

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Abstract

Genomic Signal Processing is used for processing, investigation and usage of genomic signals for achieving biological knowledge for systems-based applications. The important objective of study of genomics is to determine the group of gene for categorizing the disease, so the molecular based diagnosis can be mostly used. The proposed method is an efficient method to enhance the genomic signal processing. Here the proposed Kalman filter is used as a preprocessing part and used to remove the noise available in the microarray data and also helps in smoothening the data for signal processing. The fuzzy c-means clustering has been used here for clustering the microarray data after removal of noise. The artificial neural network is used here to classify microarray data to identify the affected and non-affected genes which are available in the microarray data. In the proposed method, the results are verified in terms of Davies-Bouldin Index, Dunn’s Index, Silhouette Width, precision, recall, and F-score. As per the result obtained by this proposed method, we found that it is one of the efficient methods in genomic signal processing of micro array data set.

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Author information

Authors and Affiliations

  1. Department of Electronics and Tele Communication Engineering, Veer Surendra Sai University of Technology, Burla, Odisha, India

    Purnendu Mishra & Nilamani Bhoi

Authors
  1. Purnendu Mishra
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  2. Nilamani Bhoi
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Corresponding author

Correspondence to Purnendu Mishra .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Sri Sivani College of Engineering, Srikakulam, Andhra Pradesh, India

    Janmenjoy Nayak

  2. Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina E. Balas

  3. Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  4. Department of Production Engineering, Indira Gandhi Institute of Technology, Sarang, Odisha, India

    Bibhuti Bhusan Choudhury

  5. Department of Computer Science and Engineering, Gandhi Institute for Technology, Hyderabad, Telangana, India

    S. Krishna Mohan Rao

  6. Department of Computer Application, Veer Surendra Sai University of Technology, Burla, Odisha, India

    Bighnaraj Naik

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Mishra, P., Bhoi, N. (2020). Kalman Filtering Based Fuzzy C-Means Clustering and Artificial Neural Network for Classification of Microarray Data. In: Nayak, J., Balas, V., Favorskaya, M., Choudhury, B., Rao, S., Naik, B. (eds) Applications of Robotics in Industry Using Advanced Mechanisms. ARIAM 2019. Learning and Analytics in Intelligent Systems, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-030-30271-9_28

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