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Hybrid AI-Based Soil Moisture Prediction and Advisory System

Author

Listed:
  • Sahel T. Sande
  • Ruturaj R. Mane
  • Sanika C. Joshi

Abstract

In the present study, a laboratory-scale swirl-stabilized dump combustor was used to investigate the dynamic characteristics. The dynamics of the flame was studied for progressively decreasing equivalence ratios till blowout occurred. The equivalence ratio was varied by decreasing the fuel flow rate at a given air flow rate. The combustion dynamics was represented in terms of time series data of pressure fluctuations, measured with a microphone, and fluctuations of intensity of flame emissions (CH* chemiluminescence), measured with a photomultiplier tube. The dynamics was characterized by means of power spectrum analysis and short time Fourier transform. The statistical moments are calculated based on fluctuation which gives the clear picture flame dynamics.

Suggested Citation

  • Sahel T. Sande & Ruturaj R. Mane & Sanika C. Joshi, 2026. "Hybrid AI-Based Soil Moisture Prediction and Advisory System," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 13(3), pages 485-491, June.
    • Handle: RePEc:etm:ijsrst:v13:y2026:i3:id:1624
    DOI: 10.32628/IJSRST26133159
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