How a math equation could solve the Malaysia Airline mystery
The Malaysia Airlines mystery has dragged into its sixth day, with authorities no closer to locating the plane.
But one expert believes that a mathematical equation could be the key to unlocking one of aviation's biggest mysteries, The Malaysian Insider reported.
Scientists believe rescuers should turn to an 18th century equation called Bayes' Theorem, one that has actually found a plane in the past.
The theorem allows investigators to organise data in a way that helps target a location and discount unlikely scenarios.
“It’s a very short, simple equation that says you can start out with hypothesis about something - and it doesn’t matter how good the hypothesis is,” said Sharon Bertsch McGrayne, an author who has gone to explain the theory in simple language in her book The Theory That Would Not Die.
The formula would allow authorities to work on hypotheses that change as new information comes to hand, and thus increase the probability of finding the plane.
The theory was used to help find the plane involved in the Air France incident. In that case, experts searched two years to find the black box of Air France flight 447 in the Atlantic Ocean.
According to Al Jazeera, after applying Bayes' Theorem, they found the black box in five days despite it being 12,000 feet under water.
The Bayes' Theorem "“allows the organisation of available data with associated uncertainties and computation of the PDF (probability distribution function) for target location given these data," according to chief scientist Lawrence D. Stone from consultancy firm Metron.
The theorem, devices in the 1740s, also helped locate German U-boats during world war two, and is also being used as part of Google's "driverless car" project.
Stone believes it is "highly unlikely" that search and rescue efforts are applying Bayes' Theorem.
However, he said the current search may have discarded the theorem as"it then got upset when their prior calculations were incorrect," tatistician Professor Bradley Efron of Stanford University said.
