Canberra:
A series of complex mathematical formulas which were used to find the wreckage of Air France Flight 447 in 2011 could be used to solve the mystery of the missing Malaysia Airlines flight MH370, Australian academics said on Tuesday.
It took two years but statisticians eventually found the Air France flight at the bottom of the Atlantic Ocean using the complex formulas, Xinhua reported.
Professor Michael McCarthy of the University of Melbourne said that optimal searching and Bayesian statistics were two maths formulas that can help the search effort of the missing Malaysian jet, which is concentrated across a vast area of the Indian Ocean off the west coast of Australia.
This technique was developed in World War II to hunt for submarines also maps the probability of the presence of a target.
Bayesian methods can be used to boost small data sets with expert opinion in order to get the most out of the data.
Associate Professor Adrian Barnett of the University of Queensland said while the probabilities will be broad, statistics can still offer some insight.
"The Bayesian estimates in this case would be a map of probabilities which would be used to guide the experts on where to look," Barnett said.
When authorities searching for the missing Air France Flight plugged in to the Bayesian inference statistical technique, a set of probabilities were produced for the whole search area.
The statistics allowed for one crucial variation: That the black boxes may have failed to activate their locator beacons.
With just such a possibility taken into account, the search was guided back to the start-point by the simple overlapping concentration of probabilities and the plane was eventually located.
Malaysia Airlines flight MH370 vanished mysteriously about an hour after taking off for Beijing from Kuala Lumpur shortly after midnight March 8.
The Boeing 777-200ER was scheduled to land in Beijing the same morning. The 227 passengers on board included five Indians, 154 Chinese and 38 Malaysians.
It took two years but statisticians eventually found the Air France flight at the bottom of the Atlantic Ocean using the complex formulas, Xinhua reported.
Professor Michael McCarthy of the University of Melbourne said that optimal searching and Bayesian statistics were two maths formulas that can help the search effort of the missing Malaysian jet, which is concentrated across a vast area of the Indian Ocean off the west coast of Australia.
This technique was developed in World War II to hunt for submarines also maps the probability of the presence of a target.
Bayesian methods can be used to boost small data sets with expert opinion in order to get the most out of the data.
Associate Professor Adrian Barnett of the University of Queensland said while the probabilities will be broad, statistics can still offer some insight.
"The Bayesian estimates in this case would be a map of probabilities which would be used to guide the experts on where to look," Barnett said.
When authorities searching for the missing Air France Flight plugged in to the Bayesian inference statistical technique, a set of probabilities were produced for the whole search area.
The statistics allowed for one crucial variation: That the black boxes may have failed to activate their locator beacons.
With just such a possibility taken into account, the search was guided back to the start-point by the simple overlapping concentration of probabilities and the plane was eventually located.
Malaysia Airlines flight MH370 vanished mysteriously about an hour after taking off for Beijing from Kuala Lumpur shortly after midnight March 8.
The Boeing 777-200ER was scheduled to land in Beijing the same morning. The 227 passengers on board included five Indians, 154 Chinese and 38 Malaysians.
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