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  • Published Subscription Original Research

    Study of an Improved Quantum Particle Swarm Optimization-Based Framework for Neural Network Optimization in Modelling of Polymer Data

    Abstract: The accurate forecasting of polymer viscosity at various physicochemical conditions has been quite critical due to the nonlinear interactions and interrelations between the variables. This paper suggests a better hybrid modelling framework, which involves the use of Artificial Neural Networks (ANN) and more advanced versions of Quantum Particle Swarm Optimization (QPSO) to better predict polymer viscosity. The input parameters taken are, namely, log (shear rate), polymer concentration, NaCl concentration, Ca …

    Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 282–297 Read article

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