Flight trajectory prediction enabled by time-frequency wavelet transform
Accurate flight trajectory prediction is a crucial and challenging task in air traffic control,
especially for maneuver operations. Modern data-driven methods are typically formulated as …
especially for maneuver operations. Modern data-driven methods are typically formulated as …
Short term load forecasting using wavelet transform combined with Holt–Winters and weighted nearest neighbor models
G Sudheer, A Suseelatha - International Journal of Electrical Power & …, 2015 - Elsevier
Short term load forecasting (STLF) is an integral part of power system operations as it is
essential for ensuring supply of electrical energy with minimum expenses. This paper …
essential for ensuring supply of electrical energy with minimum expenses. This paper …
A multi-scale relevance vector regression approach for daily urban water demand forecasting
Water is one of the most important resources for economic and social developments. Daily
water demand forecasting is an effective measure for scheduling urban water facilities. This …
water demand forecasting is an effective measure for scheduling urban water facilities. This …
[图书][B] Wavelet analysis: basic concepts and applications
Wavelet Analysis: Basic Concepts and Applications provides a basic and self-contained
introduction to the ideas underpinning wavelet theory and its diverse applications. This book …
introduction to the ideas underpinning wavelet theory and its diverse applications. This book …
DERN: Deep ensemble learning model for short-and long-term prediction of baltic dry index
The Baltic Dry Index (BDI) is a commonly utilized indicator of global shipping and trade
activity. It influences stakeholders' and ship-owners' decisions respecting investments …
activity. It influences stakeholders' and ship-owners' decisions respecting investments …
Multiple seasonal STL decomposition with discrete-interval moving seasonalities
The decomposition of a time series into components is an exceptionally useful tool for
understanding the behaviour of the series. The decomposition makes it possible to …
understanding the behaviour of the series. The decomposition makes it possible to …
Drought prediction using a wavelet based approach to model the temporal consequences of different types of droughts
Droughts are expected to propagate from one type to another–meteorological to agricultural
to hydrological to socio-economic. However, they do not possess a universal …
to hydrological to socio-economic. However, they do not possess a universal …
A short-term load forecasting model with a modified particle swarm optimization algorithm and least squares support vector machine based on the denoising method …
D Niu, S Dai - Energies, 2017 - mdpi.com
As an important part of power system planning and the basis of economic operation of
power systems, the main work of power load forecasting is to predict the time distribution …
power systems, the main work of power load forecasting is to predict the time distribution …
A hybridization of teaching–learning-based optimization and differential evolution for chaotic time series prediction
L Wang, F Zou, X Hei, D Yang, D Chen, Q Jiang… - Neural computing and …, 2014 - Springer
Chaotic time series prediction problems have some very interesting properties and their
prediction has received increasing interest in the recent years. Prediction of chaotic time …
prediction has received increasing interest in the recent years. Prediction of chaotic time …
Epicasting: an ensemble wavelet neural network for forecasting epidemics
Infectious diseases remain among the top contributors to human illness and death
worldwide, among which many diseases produce epidemic waves of infection. The lack of …
worldwide, among which many diseases produce epidemic waves of infection. The lack of …