Computer-based weather forecast: New algorithm outperforms mainframe computer systems

February 13, 2020

The exponential growth in computer processing power seen over the past 60 years may soon come to a halt. Complex systems such as those used in weather forecast, for example, require high computing capacities, but the costs for running supercomputers to process large quantities of data can become a limiting factor. Researchers at Johannes Gutenberg University Mainz (JGU) in Germany and Università della Svizzera italiana (USI) in Lugano in Switzerland have recently unveiled an algorithm that can solve complex problems with remarkable facility - even on a personal computer.

Exponential growth in IT will reach its limit

In the past, we have seen a constant rate of acceleration in information processing power as predicted by Moore's Law, but it now looks as if this exponential rate of growth is limited. New developments rely on artificial intelligence and machine learning, but the related processes are largely not well-known and understood. "Many machine learning methods, such as the very popular deep learning, are very successful, but work like a black box, which means that we don't know exactly what is going on. We wanted to understand how artificial intelligence works and gain a better understanding of the connections involved," said Professor Susanne Gerber, a specialist in bioinformatics at Mainz University. Together with Professor Illia Horenko, a computer expert at Università della Svizzera italiana and a Mercator Fellow of Freie Universität Berlin, she has developed a technique for carrying out incredibly complex calculations at low cost and with high reliability. Gerber and Horenko, along with their co-authors, have summarized their concept in an article entitled "Low-cost scalable discretization, prediction, and feature selection for complex systems" recently published in Science Advances. "This method enables us to carry out tasks on a standard PC that previously would have required a supercomputer," emphasized Horenko. In addition to weather forecasts, the research see numerous possible applications such as in solving classification problems in bioinformatics, image analysis, and medical diagnostics.

Breaking down complex systems into individual components

The paper presented is the result of many years of work on the development of this new approach. According to Gerber and Horenko, the process is based on the Lego principle, according to which complex systems are broken down into discrete states or patterns. With only a few patterns or components, i.e., three or four dozen, large volumes of data can be analyzed and their future behavior can be predicted. "For example, using the SPA algorithm we could make a data-based forecast of surface temperatures in Europe for the day ahead and have a prediction error of only 0.75 degrees Celsius," said Gerber. It all works on an ordinary PC and has an error rate that is 40 percent better than the computer systems usually used by weather services, whilst also being much cheaper.

SPA or Scalable Probabilistic Approximation is a mathematically-based concept. The method could be useful in various situations that require large volumes of data to be processed automatically, such as in biology, for example, when a large number of cells need to be classified and grouped. "What is particularly useful about the result is that we can then get an understanding of what characteristics were used to sort the cells," added Gerber. Another potential area of application is neuroscience. Automated analysis of EEG signals could form the basis for assessments of cerebral status. It could even be used in breast cancer diagnosis, as mammography images could be analyzed to predict the results of a possible biopsy.

"The SPA algorithm can be applied in a number of fields, from the Lorenz model to the molecular dynamics of amino acids in water," concluded Horenko. "The process is easier and cheaper and the results are also better compared to those produced by the current state-of-the-art supercomputers."
The collaboration between the groups in Mainz and Lugano was carried out under the aegis of the newly-created Research Center Emergent Algorithmic Intelligence, which was established in April 2019 at JGU and is funded by the Carl Zeiss Foundation.

Johannes Gutenberg Universitaet Mainz

Related Algorithm Articles from Brightsurf:

CCNY & partners in quantum algorithm breakthrough
Researchers led by City College of New York physicist Pouyan Ghaemi report the development of a quantum algorithm with the potential to study a class of many-electron quantums system using quantum computers.

Machine learning algorithm could provide Soldiers feedback
A new machine learning algorithm, developed with Army funding, can isolate patterns in brain signals that relate to a specific behavior and then decode it, potentially providing Soldiers with behavioral-based feedback.

New algorithm predicts likelihood of acute kidney injury
In a recent study, a new algorithm outperformed the standard method for predicting which hospitalized patients will develop acute kidney injury.

New algorithm could unleash the power of quantum computers
A new algorithm that fast forwards simulations could bring greater use ability to current and near-term quantum computers, opening the way for applications to run past strict time limits that hamper many quantum calculations.

QUT algorithm could quash Twitter abuse of women
Online abuse targeting women, including threats of harm or sexual violence, has proliferated across all social media platforms but QUT researchers have developed a sophisticated statistical model to identify misogynistic content and help drum it out of the Twittersphere.

New learning algorithm should significantly expand the possible applications of AI
The e-prop learning method developed at Graz University of Technology forms the basis for drastically more energy-efficient hardware implementations of Artificial Intelligence.

Algorithm predicts risk for PTSD after traumatic injury
With high precision, a new algorithm predicts which patients treated for traumatic injuries in the emergency department will later develop posttraumatic stress disorder.

New algorithm uses artificial intelligence to help manage type 1 diabetes
Researchers and physicians at Oregon Health & Science University have designed a method to help people with type 1 diabetes better manage their glucose levels.

A new algorithm predicts the difficulty in fighting fire
The tool completes previous studies with new variables and could improve the ability to respond to forest fires.

New algorithm predicts optimal materials among all possible compounds
Skoltech researchers have offered a solution to the problem of searching for materials with required properties among all possible combinations of chemical elements.

Read More: Algorithm News and Algorithm Current Events is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to