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Nanotechnology

Intelligent Solution Predicted Bayesian Regularization Networks for Nano-Liquid Applications

Strategic Insights

— 1 min read

Researchers at Saveetha University in Tamil Nadu, India, have developed a novel approach to evaluate the performance of gyrotactic and oxytactic microbes in hybrid nanofluids using a deep neural network. The network, built using the Bayesian regularization technique, was trained on a dataset created with the RKF-45th command and was able to predict the rate of heat transmission in hybrid nanofluids with high accuracy. The study's findings have significant implications for wastewater treatment, thermal performance optimization, and environmental monitoring.

Key Takeaways:

  • The research aims to evaluate the performance of gyrotactic and oxytactic microbes in hybrid nanofluids using a deep neural network.
  • The network was built using the Bayesian regularization technique and was trained on a dataset created with the RKF-45th command.
  • The study found that the rate of heat transmission in hybrid nanofluids increases as the volume friction of nanoparticles increases.
  • The model can be used to optimize thermal performance in energy systems such as solar collectors and heat exchangers.
  • The predictive capabilities of the model can be used in commercial cooling operations and environmental monitoring.
  • The study's findings have significant implications for wastewater treatment as microorganisms can increase the fluid's bioactivity and efficacy in removing pollutants.

Statistics:

  • The input dataset for the network was created using the RKF-45th command.
  • Three independent instances were created to study how the various parameters changed on the proposed model.
  • A variety of statistical indicators were employed to evaluate the network's accuracy and precision.
  • The rate of heat transmission in hybrid nanofluids increases as the volume friction of nanoparticles increases.

Sources:

  • "Intelligent Solution Predicted Bayesian Regularization Networks for Chemical Reactive Flow of Hybrid Nanoliquid With Applications of Bioconvection and Solar Radiation" (Journal of Radiation Research and Applied Sciences, 2025;18(3)).
  • (Elsevier, Radarweg 29, 1043 Nx Amsterdam, Netherlands).
  • NewsRx. Findings from Saveetha University Provides New Data about Nano-Liquids (Intelligent Solution Predicted Bayesian Regularization Networks for Chemical Reactive Flow of Hybrid Nanoliquid With Applications of Bioconvection and Solar Radiation). Nanotechnology Weekly. September 1, 2025; p 241.

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