ANALYZING FLIGHT DATA USING PREDICTIVE MODELS

摘要

Various embodiments for analyzing flight data using predictive models are described herein. In various embodiments, a quadratic least squares model is applied to a matrix of time-series flight parameter data for a flight, thereby deriving a mathematical signature for each flight parameter of each flight in a set of data including a plurality of sensor readings corresponding to time-series flight parameters of a plurality of flights. The derived mathematical signatures are aggregated into a dataset. A similarity between each pair of flights within the plurality of flights is measured by calculating a distance metric between the mathematical signatures of each pair of flights within the dataset, and the measured similarities are combined with the dataset. A machine-learning algorithm is applied to the dataset, thereby identifying, without predefined thresholds, clusters of outliers within the dataset by using a unified distance matrix.

主权项

1. A device, comprising:
at least one processor; at least one memory device; wherein the at least one memory device stores a program to cause the at least one processor to: derive, using a quadratic least squares model applied to a matrix of time-series flight parameter data for a flight, a mathematical signature for each flight parameter of each flight in a set of data including a plurality of sensor readings corresponding to time-series flight parameters of a plurality of flights; aggregate the derived mathematical signatures into a dataset; measure a similarity between each pair of flights within the plurality of flights by calculating a distance metric between the mathematical signatures of each pair of flights within the dataset; combine the measured similarities with the dataset; apply a machine-learning algorithm to the dataset; and identify, without predefined thresholds, clusters of outliers within the dataset by using a unified distance matrix.