A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

Artificial intelligence-driven algorithms can be used to better forecast models for natural disasters, saving lives and protecting property by rapidly analyzing massive data sets and identifying ...

AI fixes earnings forecasting when it expands coverage, standardizes signal extraction, and quantifies uncertainty. AI breaks forecasting when it creates false precision, synchronized expectations, ...

Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...

As climate extremes intensify across Africa, the need for accurate and timely weather prediction has become increasingly ...

This study was led by Professor Qi Zhong and Professor Xiuping Yao from the China Meteorological Administration Training Center, and Assistant Engineer Zhicha Zhang from the Zhejiang Meteorological ...

Researchers in China have applied a machine learning technology based on temporal convolutional networks in PV power forecasting for the first time. The new model reportedly outperforms similar models ...

One of the unwritten axioms of data scientists specializing in machine learning methodologies is that they all try their hand at predicting the stock market. Some of the best attempts have turned a ...