Hybrid Optimization Framework

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• Published Subscription Original Research 3 Jul 2026

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

  By Kakali Das, Amrita Mitra, Sagardeep Ghosh, Suchismita Maiti, Soumyabrata Saha, Pushpita Roy, Anubrata Mondal, Pijush Dutta

  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 Read article →