Chandigarh, February 7
In the backdrop of global warming and climatic changes, a recent study has projected that the monthly mean precipitation in the Jhelum basin is expected to increase by 20-25 per cent towards the end of the 21st century, while the monthly mean temperature may go up 2-3°C.
Investigation of the future projections revealed an average increase of 17-25 per cent in the mean annual precipitation. The mean seasonal temperature of the projected period was found to be increasing for all the four seasons in most parts of the basin.
Using future prediction models, the study examined the spatio-temporal variations of precipitation and temperature for the 2011-2100 period in the Jhelum basin that lies across the mountainous regions of Kashmir and adjoining parts of north-east Pakistan. It has a total catchment area of 33,342 sq km and forms part of the Indus basin, which is among the largest basins in the world.
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Risk.net
Quants unveil new technique for controlling extrapolation by neural networks
According to a popular internet meme, there are two types of people in this world: those who can extrapolate from incomplete data.
Neural networks will probably struggle with that one. As quants race to deploy neural networks in finance, they are running into a common problem. Neural networks require huge datasets to train, but they do not always extrapolate well when faced with new situations.
“Neural networks can fit the data very well within the region of training, but can produce completely unpredictable and uncontrolled results outside of that,” says Michael Konikov, head of quantitative development at Numerix.