New Clustering Method Simplifies Analysis of Large Data Sets
Researchers from HSE University and the Institute of Control Sciences of the Russian Academy of Sciences have proposed a new method of data analysis: tunnel clustering. It allows for the rapid identification of groups of similar objects and requires fewer computational resources than traditional methods. Depending on the data configuration, the algorithm can operate dozens of times faster than its counterparts. Thestudy was published in the journal Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia.
Scientists Assess the Effectiveness of Forest Fires Suppression in the Russian Regions
April officially marked the beginning of the peak forest fire season across Russia, and preventative measures have recently been discussed at the Ministry of the Russian Federation for Civil Defence, Emergencies and Elimination of Consequences of Natural Disasters (also known as The Ministry of Emergency Situations, MChS) and at a meeting in which the President of the Russian Federation participated. Regions have already started taking measures to prevent forest fires, and a team of researchers from the Faculty of Economic Sciences of HSE University has proposed a mathematical model by which the effectiveness of these measures can be evaluated. Using this algorithm, they compared Russian regions in terms of the success of their firefighting activities. Details of the work have been published in the collection ‘Dynamics of Disasters: Impact, Risk, Resilience, and Solutions’.