Modeling of Aircraft Takeoff Weight Using Gaussian Processes
نویسندگان
چکیده
منابع مشابه
Statistical Modeling of Aircraft Takeoff Weight
The Takeoff Weight (TOW) of an aircraft is an important aspect of aircraft performance, and impacts a large number of characteristics, ranging from the trajectory to the fuel burn of the flight. Due to its dependence on factors such as the passenger and cargo load factors as well as operating strategies, the TOW of a particular flight is generally not available to entities outside of the operat...
متن کاملModelling the dispersion of aircraft trajectories using Gaussian processes
This work investigates the application of Gaussian processes to capturing the probability distribution of a set of aircraft trajectories from historical measurement data. To achieve this, all data are assumed to be generated from a probabilistic model that takes the shape of a Gaussian process. The approach to Gaussian process modelling used here is based on a linear expansion of trajectory dat...
متن کاملModeling Text through Gaussian Processes
This paper proposes a continous space text model based on Gaussian processes. Introducing latent coordinates of words over which the Gaussian process is defined, we can encode word correlations directly and lead to a model that performs better than mixture models. Our model would serve as a foundation of more complex text models and also as a statistical visualization of texts.
متن کاملThe Rate of Entropy for Gaussian Processes
In this paper, we show that in order to obtain the Tsallis entropy rate for stochastic processes, we can use the limit of conditional entropy, as it was done for the case of Shannon and Renyi entropy rates. Using that we can obtain Tsallis entropy rate for stationary Gaussian processes. Finally, we derive the relation between Renyi, Shannon and Tsallis entropy rates for stationary Gaussian proc...
متن کاملBayesian Modeling with Gaussian Processes using the GPstuff Toolbox
Gaussian processes (GP) are powerful tools for probabilistic modeling purposes. They can be used to define prior distributions over latent functions in hierarchical Bayesian models. The prior over functions is defined implicitly by the mean and covariance function, which determine the smoothness and variability of the function. The inference can then be conducted directly in the function space ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Air Transportation
سال: 2018
ISSN: 2380-9450
DOI: 10.2514/1.d0099