Swati Vipsita

Employment

• International Institute of Information Technology Bhubaneswar Assistant Professor
  2012 - Present

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (30)

• Jaya Optimized Extreme Learning Machine for Breast Cancer Data Classification
  Smart Innovation, Systems and Technologies 2021 DOI: 10.1007/978-981-15-6202-0_47
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• Analysis of high-dimensional genomic data using MapReduce based probabilistic neural network
  Computer Methods and Programs in Biomedicine 2020 DOI: 10.1016/j.cmpb.2020.105625
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• Triclustering of gene expression microarray data using coarse grained and dynamic deme based parallel genetic approach
  Evolutionary Intelligence 2020 DOI: 10.1007/s12065-019-00330-6
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• A new optimal gene selection approach for cancer classification using enhanced Jaya-based forest optimization algorithm
  Neural Computing and Applications 2020 DOI: 10.1007/s00521-019-04355-x
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• Chaotic emperor penguin optimised extreme learning machine for microarray cancer classification
  IET Systems Biology 2020 DOI: 10.1049/iet-syb.2019.0028
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• A memetic algorithm using emperor penguin and social engineering optimization for medical data classification
  Applied Soft Computing 2019 DOI: 10.1016/j.asoc.2019.105773
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• Ensemble Neighborhood Search (ENS) for biclustering of gene expression microarray data and single cell RNA sequencing data
  Journal of King Saud University - Computer and Information Sciences 2019 DOI: 10.1016/j.jksuci.2019.11.011
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• Analysis of high-dimensional biomedical data using an evolutionary multi-objective emperor penguin optimizer
  Swarm and Evolutionary Computation 2019 DOI: 10.1016/j.swevo.2019.04.010
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• Cancer Classification using improved Extreme Learning Machine
  2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) 2019 DOI: 10.1109/cibcb.2019.8791238
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• Analysis of high-dimensional genomic data employing a novel bio-inspired algorithm
  Applied Soft Computing 2019 DOI: 10.1016/j.asoc.2019.01.007
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