Machine learning approach for analysis and prediction of cloud particle size and shape distribution
US10168448B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 30, 2013 |
| Grant date | Jan 1, 2019 |
| Priority date | — |
| Expiry date | Sep 30, 2035 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01W1/10
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
Techniques for analysis and prediction of cloud particle distribution and solar radiation are provided. In one aspect, a method for analyzing cloud particle characteristics includes the steps of: (a) collecting meteorological data; (b) calculating solar radiation values using a radiative transfer model based on the meteorological data and blended guess functions of a cloud particle distribution (c) optimizing the cloud particle distribution by optimizing the weight coefficients used for the blended guess functions of the cloud particle distribution based on the solar radiation values calculated in step (b) and measured solar radiation values; (d) training a machine-learning process using the meteorological data collected in step (a) and the cloud particle distribution optimized in step (c) as training samples; and (e) predicting future solar radiation values using forecasted meteorological data and the machine-learning process trained in step (d).
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.