rakshitha123/IEEE_CIS_Comp

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rakshitha123/IEEE_CIS_Comp

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TSForecasting

This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.

WeeklyForecasting

This repository contains the experiments related with a new baseline model that can be used in forecasting weekly time series. This model uses the forecasts of 4 sub-models: TBATS, Theta, Dynamic Harmonic Regression ARIMA and a global Recurrent Neural Network (RNN), and optimally combine them using lasso regression.

SETAR_Trees

This repository contains the experiments related to a new and accurate tree-based global forecasting algorithm named, SETAR-Tree.

Localised_Ensembles

This repository contains the experiments of our paper titled, "Ensembles of Localised Models for Time Series Forecasting" which is online available at: https://doi.org/10.1016/j.knosys.2021.107518. In this work, we study how ensembleing techniques can be used to solve the localisation issues of global forecasting models.

TemperatureForecasting

This repository contains the experiments of our recent study related to the optimisation of Air Conditioning (AC) systems which is published at the IEEE Access.

setartree

BlastGame

SAODE

SAODE Related Experiments