Fuzzy Numbers Unraveling the Intricacies of Neural Network Functionality

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Abstract This research delves into the synergy between fuzzy numbers and neural networks, presenting a novel perspective on interpreting neural network functionality. Fuzzy numbers offer a flexible framework to capture uncertainties and imprecisions, enriching the interpretability of neural network outputs. By integrating fuzzy number theory into the analysis, our study seeks to enhance the transparency and reliability of neural network models, contributing to a more nuanced understanding of their inner
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Fuzzy Numbers Unraveling the Intricacies of Neural Network Functionality | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Fuzzy Numbers Unraveling the Intricacies of Neural Network Functionality Vehbi Ramaj, Rame Elezaj, Elvir Čajić This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3876947/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This research delves into the synergy between fuzzy numbers and neural networks, presenting a novel perspective on interpreting neural network functionality. Fuzzy numbers offer a flexible framework to capture uncertainties and imprecisions, enriching the interpretability of neural network outputs. By integrating fuzzy number theory into the analysis, our study seeks to enhance the transparency and reliability of neural network models, contributing to a more nuanced understanding of their inner Fuzzy Numbers Neural Networks Interpretability Uncertainty Modeling Computational Intelligence Figures Figure 1 Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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