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Technologies of war: actively developing software capable of predicting the outcome of war – Industry news – Technologies and Business – Financenet – TVNET

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In order for the MCOSM model to work and make a prediction, it is necessary to know 30 different values, such as the readiness level of each party involved, ammunition, mobility, logistics, decision making and others. It is also necessary to objectively assess the situation and unknown factors, as well as the possibility of error.

In May 1940, the French army experienced a collapse, although before World War II the French army was considered one of the strongest in Europe. Also, the Russian army was considered to be very dangerous, especially after the reforms started in 2008.

Carneckis, who previously served in the US Army, was adamant about the decision-making capabilities of the Russian military. This proved to be an accurate prediction, as many military analysts point out that Russia’s biggest mistake in the first phase of the war was to launch an attack on a wide front line from several directions.

Other forecasting models also exist. One category is deterministic models, which means that given the same data, it is possible to get virtually the same prediction. The second category is probabilistic models. For example, one can model how likely it is that a sniper will hit his target, given that the target is 600 meters away, is reclining, the target is wearing body armor and moving, but the sniper is tired and ill-prepared.

These types of probabilities are represented by percentages, for example, indicating the probability that the sniper will miss, injure, or kill the target.

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