Short-Term Renewable Energy Forecasting in Greece Using Prophet Decomposition and Tree-Based Ensembles

Vartholomaios, Argyrios; Karlos, Stamatis; Kouloumpris, Eleftherios; Tsoumakas, Grigorios

doi:10.1007/978-3-030-87101-7_22

Cited by 9 publications

(5 citation statements)

References 15 publications

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“…Prophet involves open-source time-series forecasting and outperforms other modelling methods, such as autoregressive integrated moving average (ARIMA), when dealing with multiple seasonal effects. 16 It is based on a univariate generalised additive model (GAM) and involves a curve-fitting task with time as the regressor. The model contains a trend, seasonality and an external variation component.…”

Section: Discussionmentioning

confidence: 99%

Risk of Pseudomonas aeruginosa antimicrobial resistance using time series analysis of antibiotic usage

Papacostas,

Grant,

Hall

2024

Pharmacy Practice and Res

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BackgroundAntimicrobial resistance is emerging as one of the most potentially disastrous threats of the 21st century. Pseudomonas aeruginosa (P. aeruginosa) is a leading resistant pathogen and is clinically significant due to its limited available treatment using antibiotics. Rising resistance of P. aeruginosa is of increasing concern and it is currently listed as one of the top three critically resistant pathogens by the World Health Organization. It is currently known that resistance in P. aeruginosa is significantly linked with the consumption of all antibiotics, making usage surveillance of particular concern.AimThe aim of the current study was to model current and future antibiotic usage using available prescription data for antipseudomonal antibiotics.MethodA time‐series analysis was performed on Pharmaceutical Benefits Scheme/Repatriation Pharmaceutical Benefits Scheme data from January 2000–June 2020 using Facebook Prophet time‐series methods in Python 3.9.14 to analyse and forecast trends to 2025. Ethical approval was not required for this research article as it used publicly available data and did not involve human subjects.ResultsThe usage of antipseudomonal antibiotics decreased by 14.3% from 2014 to 2020 (95% confidence interval [CI] −30.4% to 2.3%) and is projected to further decrease by 11.7% by 2025 (95% CI −30.6% to 7.3%).ConclusionThe current study showed a decline in the use of certain antipseudomonal antibiotics in Australia since 2015 and projects that their use will continue to decline. This is likely due to an increased judicious use of these antibiotics.

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Section: Discussionmentioning

confidence: 99%

Risk of Pseudomonas aeruginosa antimicrobial resistance using time series analysis of antibiotic usage

Papacostas,

Grant,

Hall

2024

Pharmacy Practice and Res

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“…Although it assumes a time-series forecasting methodology, which is relatively new, Prophet is often mainly used in the environmental field in order to make reliable predictions [50,51].…”

Section: Working Mechanismmentioning

confidence: 99%

Reverse Logistics of Packaging Waste under the Conditions of a Sustainable Circular Economy at the Level of the European Union States

Scrioșteanu,

Criveanu

2023

Sustainability

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The efficient use of natural resources and the quality of the environment are the main priorities of sustainable development. The purpose of this paper is to demonstrate the role of reverse logistics in the context of sustainable development, starting from the premise that it combines environmental and economic objectives and aims to minimize the wastage of resources through the reuse of products and packaging. In the current context, the circular economy must be approached by considering the methods of waste collection and reuse, with reverse logistics playing an essential role in creating environmental, economic, and social benefits. The growing population obviously determines the increase in the consumption of resources, which inevitably leads to the increasing generation of packaging and packaging waste. This study aimed to highlight the evolution of recycling rates at the level of the EU member states, starting from the stability objectives of the European Commission for the years 2025–2030. Starting from the Eurostat database, for the 27 member states of the European Union, regarding the recovery rate, recycle rate, and waste generation kg_per_capita related to the period of 2009–2020, we extrapolated the trends of the recycling rate of packaging for the period of 2021–2030 with the help of the Prophet model. Using the Prophet forecasting program, we identified states from the European Union that will meet the stability targets set by the European Commission for the years 2025 to 2030, considering the need to develop a circular economy.

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“…The Prophet modelling approach is an additive forecasting approach based on the Bayesian curve fitting procedure. This technique can incorporate any types of non-linear trend and multiple seasonality such as hourly, daily, weekly, monthly and yearly with holiday effects [59]. The model has four main components such as trend, seasonality, holiday and error term, as seen in equation [59]:…”

Section: Prophet Modelling Approachmentioning

confidence: 99%

Forecasting of Solar and Wind Resources for Power Generation

Islam,

Hassan,

Rasul

et al. 2023

Energies

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Solar and wind are now the fastest-growing power generation resources, being ecologically benign and economical. Solar and wind forecasts are significantly noteworthy for their accurate evaluation of renewable power generation and, eventually, their ability to provide profit to the power generation industry, power grid system and local customers. The present study has proposed a Prophet-model-based method to predict solar and wind resources in the Doomadgee area of Far North Queensland (FNQ), Australia. A SARIMA modelling approach is also implemented and compared with Prophet. The Prophet model produces comparatively less errors than SARIMA such as a root mean squared error (RMSE) of 0.284 and a mean absolute error (MAE) of 0.394 for solar, as well as a MAE of 0.427 and a RMSE of 0.527 for wind. So, it can be concluded that the Prophet model is efficient in terms of its better prediction and better fitting in comparison to SARIMA. In addition, the present study depicts how the selected region can meet energy demands using their local renewable resources, something that can potentially replace the present dirty and costly diesel power generation of the region.

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Short-Term Renewable Energy Forecasting in Greece Using Prophet Decomposition and Tree-Based Ensembles

Cited by 9 publications

References 15 publications

Risk of Pseudomonas aeruginosa antimicrobial resistance using time series analysis of antibiotic usage

Risk of Pseudomonas aeruginosa antimicrobial resistance using time series analysis of antibiotic usage

Reverse Logistics of Packaging Waste under the Conditions of a Sustainable Circular Economy at the Level of the European Union States

Forecasting of Solar and Wind Resources for Power Generation

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