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            <name>Title</name>
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                <text>Faculty Publications</text>
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    <name>Article</name>
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          <name>Creator</name>
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              <text>Swain, Kaliprasanna; Tak, Tan Kuan; Upreti, Kamal; Kshirsagar, Pravin R.; Krishnan, Sivaneasan Bala; Poonia, Ramesh Chandra; Mohapatra, Sumant Kumar; Nayak, Sumya Ranjan</text>
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          <name>Title</name>
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              <text>PERFORMANCE EVALUATION OF IPE AND IE-AFFECTED PATIENTS USING A MODIFIED PSO AND ANFIS</text>
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          <name>Date</name>
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              <text>01-01-2025</text>
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          <name>Source</name>
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              <text>Journal of Mechanics of Continua and Mathematical Sciences;Volume;20;Issue;6;pp.65-89</text>
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          <name>Identifier</name>
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              <text>&lt;a href="https://doi.org/10.26782/jmcms.2025.06.00005" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.26782/jmcms.2025.06.00005&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105008696027?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105008696027?origin=resultslist&lt;/a&gt;</text>
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              <text>Swain K., Department of ETC, Trident Academy of Technology, Bhubaneswar, India; Tak T.K., Singapore Institute of Technology, Singapore; Upreti K., CHRIST University, Delhi NCR, Ghaziabad, India; Kshirsagar P.R., J. D. College of Engineering &amp;amp; Management, Maharashtra, Nagpur, India; Krishnan S.B., Singapore Institute of Technology, Singapore; Poonia R.C., CHRIST University, Delhi NCR, Ghaziabad, India; Mohapatra S.K., Department of ETC, TAT, Odisha, Bhubaneswar, 24, India; Nayak S.R., School of Computer Engineering, KIIT University, Bhubaneswar, India</text>
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              <text>Epilepsy, a complex neurological disorder, is particularly challenging to diagnose and manage when driven by genetic factors. This study focuses on the analysis of Idiopathic Partial Epilepsy (IPE) and Idiopathic Epilepsy (IE) in both children and women, using a novel approach combining Modified Particle Swarm Optimization (MPSO) with a 9-rule Adaptive Neuro-Fuzzy Inference System (ANFIS). Four feature extraction techniquesDiscrete Wavelet Transform (DWT), Shearlet Transform (SLT), Contourlet Transform (CLT), and Stockwell Transform (SWT)are employed to process electroencephalogram (EEG) signals. The performance of the proposed MPSO-ANFIS model is evaluated and compared with existing methods. Results indicate that the SWT-ANFIS-MPSO method achieves superior classification accuracy for both IE and IPE patients, highlighting its potential to improve epilepsy diagnosis and treatment strategies.  2025, Institute of Mechanics of Continua and Mathematical Sciences. All rights reserved.</text>
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          <name>Subject</name>
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              <text>ANFIS; Idiopathic Epilepsy (IE); Idiopathic Partial Epilepsy (IPE); Modified Particle Swarm Optimization (MPSO)</text>
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          <name>Publisher</name>
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              <text>Institute of Mechanics of Continua and Mathematical Sciences</text>
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              <text>ISSN: 9738975;</text>
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              <text>All Open Access; Gold Open Access</text>
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