Submission Title

Searching For a Lost Plane

Location

Jereld R. Nicholson Library

Subject Area

Mathematics

Description

Malaysia plane MH370 disappeared en route from Kuala Lumpur to Beijing on 8, March 2014. Besides considering the factors such as air piracy, weather, electromagnetic wave, and kinds of bugs of the airplane, in order to find the wreckage efficiently the growing concern is to confirm a limited area where the airplane probably fell, and then to find an optimum way to find the plane. It’s essential to build such a model involving both of the two layers mentioned above that can cover all the searching area by using the most efficient way.

The first layer is to confirm the limited area. We use the Poisson Probability Distribution, the Drag equation, and the Proper Orthogonal Decomposition Theorem to assume the direction of the airplane and the sea area where it probably fell. All assumptions are based on the actual situation.

The second model will basically rely on the Bayesian principles. In this case, the model would be advantageous as it will rely on contingency as an important role in the search for lost objects in the sea or on land. As matter of fact, any information that is provided to the search team would be put into good use as it will be used in developing the probabilities. It is also good in that it's flexible and would be good enough to sustain the ongoing search even with new information or facts obtained regarding the flight of the plane and/or the initial findings of the debris. This helps in rounding down to a lesser geographical search region and, by extension, increases the probability of getting the plane.

Rights

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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May 15th, 9:30 AM May 15th, 10:45 AM

Searching For a Lost Plane

Jereld R. Nicholson Library

Malaysia plane MH370 disappeared en route from Kuala Lumpur to Beijing on 8, March 2014. Besides considering the factors such as air piracy, weather, electromagnetic wave, and kinds of bugs of the airplane, in order to find the wreckage efficiently the growing concern is to confirm a limited area where the airplane probably fell, and then to find an optimum way to find the plane. It’s essential to build such a model involving both of the two layers mentioned above that can cover all the searching area by using the most efficient way.

The first layer is to confirm the limited area. We use the Poisson Probability Distribution, the Drag equation, and the Proper Orthogonal Decomposition Theorem to assume the direction of the airplane and the sea area where it probably fell. All assumptions are based on the actual situation.

The second model will basically rely on the Bayesian principles. In this case, the model would be advantageous as it will rely on contingency as an important role in the search for lost objects in the sea or on land. As matter of fact, any information that is provided to the search team would be put into good use as it will be used in developing the probabilities. It is also good in that it's flexible and would be good enough to sustain the ongoing search even with new information or facts obtained regarding the flight of the plane and/or the initial findings of the debris. This helps in rounding down to a lesser geographical search region and, by extension, increases the probability of getting the plane.

 

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