World-First Study Uses First Nations Calendars for Solar Power Forecasting
NORTHERN TERRITORY, AUSTRALIA, JUL 11 – The AI model Conv-Ensemble improves solar forecasting accuracy by 14.6% and reduces error by 26.2% by incorporating First Nations ecological seasonal data.
8 Articles
8 Articles
AI, First Nations data boost solar forecasts by 14.6% in Australia
Australian researchers improved solar generation forecasts by 14.6% by integrating advanced AI methods with First Nations seasonal knowledge, offering new potential for more accurate renewable energy planning.From pv magazine Australia Researchers at Charles Darwin University (CDU) in Australia's Northern Territory have developed FNS-Metrics, a solar forecasting system that uses seasonal information from First Nations calendars. The team fed thi…
First Nations wisdom improves AI solar power prediction model by 14.6%
Researchers have combining advanced AI techniques with First Nations seasonal data and discovered a 14.6% more accurate way to predict solar power generation, with potential to improve renewable energy planning.Researchers at the Charles Darwin University (CDU) in the Northern Territory (NT) have developed a solar power forecasting system called FNS-Metrics, using seasonal information from First Nations calenders, the data of which was fed into …
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