ANALYZING FLIGHT DATA USING PREDICTIVE MODELS

Patent №

US 10,248,742

Granted

2019-04-02

Filed 2015

Owner

UNIVERSITY OF NORTH DAKOTA

Lab

AI components

4

ml · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

14651784

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.

Machine learningKnowledge representationPlanningAI hardwareG08G 5/70G01C 23/00G06F 17/10G06F 30/20G06N 20/00G06Q 10/04G06Q 10/10G06Q 50/40+1 more

AI classification

Planning1.00
Machine learning1.00
Knowledge representation0.99
AI hardware0.94
Vision0.33
Natural language0.04
Evolutionary computation0.00
Speech0.00

Ownership

UNIVERSITY OF NORTH DAKOTA

assignment · 333150691

Assignors

DESELL, TRAVIS, HIGGINS, JAMES, CLACHAR, SOPHINE, DESELL, TRAVIS, HIGGINS, JAMES, CLACHAR, SOPHINE

On an employer assignment, the assignors are typically the inventors.

© 2026 NYSGPT2525 LLC