Hybrid forecasting system considering the influence of seasonal factors under energy sustainable development goals

Li, Guomin; Pan, Zhiya; Qi, Zihan; Wang, Hui; Wang, Tao; Zhao, Yunpeng; Zhang, Yagang; Li, Gengyin; Wang, Pengfei

doi:10.1016/j.measurement.2023.112607

Cited by 9 publications

(3 citation statements)

References 56 publications

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“…The use of the Seasonal ARIMA model for forecasting the volume of emissions is justified by the need to consider the seasonal needs in energy resources, the shortage of which can significantly affect the adoption of anti-crisis decisions in the energy sector. Seasonal models are an effective means of forecasting, particularly in alternative energy research (Li et al, 2023). The dataset was formed to consider current trends in the energy sector, including implementing technologies to reduce greenhouse gas emissions.…”

Section: Discussionmentioning

confidence: 99%

Managing the EU energy crisis and greenhouse gas emissions: Seasonal ARIMA forecast

Kuzior

Vakulenko

Kolosok

et al. 2023

Problems and Perspectives in Management

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Changes in the logistics of energy resources and their potential shortage are causing a review of the EU energy policy. The energy sector significantly affects the progress toward achieving climate policy goals due to significt greenhouse gas emissions. The REPowerEU plan, implemented in the EU27 to overcome the energy crisis, requires new forecasts of greenhouse gas emissions due to a change in European energy policy. This paper aims to examine the consequences of the management of the energy crisis caused by Russia’s invasion of Ukraine on EU climate policy. This study focuses on forecasting greenhouse gas emissions in the EU until 2030 and uses the Seasonal ARIMA model based on quarterly time series in the EU27. Depending on energy management and changes in energy policy to overcome the energy crisis, a positive or negative scenario for greenhouse gas emissions may occur. An important parameter that should be considered when determining the scenario of the EU energy development according to climate policy was defined by correlation analysis.According to the negative scenario and under the influence of the effects of the Russian invasion of Ukraine, the value of greenhouse gas emissions in the EU at the beginning of 2030 will be 0.752911 tons per capita. The positive scenario shows greenhouse gas emissions can be reduced to 0.235225 tons per capita.The study results proved two extreme scenarios of greenhouse gas emissions, depending on how to overcome the energy crisis. AcknowledgmentThe authors appreciate the copyright holder: © European Union, 1995–2022, as well as the source of the extracted data, which is the European Commission website, Eurostat http://ec.europa.eu/eurostat (accessed on 16 October 2022). This study was funded by the European Union (the project No. 101048079 – EU4SmartED – ERASMUS-JMO-2021-HEI-TCH-RSCH); by the Ministry of Education and Science of Ukraine (projects No. 0122U000788, 0122U000769, 0121U109553, 0120U102001, 0122U000777).This research was funded by Faculty of Organization and Management of the Silesian University of Technology (grant number: 13/990/BK_23/0178).

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Section: Discussionmentioning

confidence: 99%

Managing the EU energy crisis and greenhouse gas emissions: Seasonal ARIMA forecast

Kuzior

Vakulenko

Kolosok

et al. 2023

Problems and Perspectives in Management

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“…The BP neural network algorithm based on particle swarm optimization algorithm is no exception. By initializing the above particle swarm, the purpose of initializing these two network parameters is further achieved [24]. (2) Secondly, for each particle, the forward propagation of BP neural network is carried out normally, and the fitness function is finally calculated.…”

Section: Research On Seamless Positioning Algorithm Based On Bp Neura...mentioning

confidence: 99%

Research on indoor and outdoor positioning switching algorithm based on improved PSO-BP

Zhao,

Wang,

Miao

et al. 2024

Meas. Sci. Technol.

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Aiming at the problems of poor positioning accuracy in the indoor and outdoor junction areas and the loss of positioning signals and discontinuous positioning results during the transition from the indoor area to the outdoor area, this paper proposes a machine learning method to solve the positioning problem in the indoor and outdoor junction areas and the switching problem of positioning methods. An indoor and outdoor positioning switching algorithm based on PSO-BP(Particle Swarm Optimization-Back Propagation, PSO-BP) and BP(Back Propagation, BP) neural network is designed. Through this algorithm, the position of the positioning tag can be judged independently and the coordinates of the positioning tag in the indoor and outdoor junction area can be predicted independently. The experimental results show that the accuracy of positioning area judgment based on PSO-BP neural network can reach 99.91%. The indoor and outdoor boundary area coordinates obtained by BP neural network prediction method are lower than the root mean square error of UWB(Ultra Wide Band, UWB) indoor positioning method and BDS(Beidou Navigation Satellite System, BDS)positioning method. The algorithm model proposed in this paper effectively improves the positioning problem of the indoor and outdoor junction area and the positioning problem of the transition from the indoor area to the outdoor area, improves the positioning accuracy and positioning stability of the indoor and outdoor junction area, reduces the positioning cost, and has strong practicability.

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“…Romania was selected due to its portrayal of some of the poorest results within the EU. Additionally, given the complexity of the topic and the extensive array of indicators involved, the authors opted to focus solely on specific goals rather than discussing all of them collectively within a single article [30,31,62].…”

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confidence: 99%

Forecasting Sustainable Development Indicators in Romania: A Study in the European Context

Ciucu (Durnoi),

Ioanăș,

Iordan

et al. 2024

Sustainability

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Sustainable development is a very important and highly debated concept worldwide, with almost all states around the globe recognizing the importance of supporting a balancing of economic, social and ecological plans to create a more prosperous and equitable world. The purpose of the current study is to identify the current context of the progress achieved by the EU member states regarding the 17 sustainable development objectives. Following the implemented research, it was found that Romania is one of the countries with the lowest performance, so an attempt was made to make a short-term forecast in the case of this country in order to determine its future course. In this sense, the Holt–Winters trend methods were used, which are based on historical data to predict future values. According to the analysis carried out, the predicted values are mainly encouraging, but it is necessary for the competent authorities to become more involved because, in many aspects, Romania is at the bottom of the European Union (EU) ranking regarding the analyzed indicators.

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Hybrid forecasting system considering the influence of seasonal factors under energy sustainable development goals

Cited by 9 publications

References 56 publications

Managing the EU energy crisis and greenhouse gas emissions: Seasonal ARIMA forecast

Managing the EU energy crisis and greenhouse gas emissions: Seasonal ARIMA forecast

Research on indoor and outdoor positioning switching algorithm based on improved PSO-BP

Forecasting Sustainable Development Indicators in Romania: A Study in the European Context

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