A hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data

A hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data

For decades, time series forecasting had many applications in various industries such as weather, financial, healthcare, business, retail, and energy consumption forecasting. An accurate prediction in these applications is a very important and also difficult task because of high sampling rates leadi...

Full description

Bibliographic Details
Main Author:	Serdar Arslan
Format:	Article
Language:	English
Published:	PeerJ Inc. 2022-06-01
Series:	PeerJ Computer Science
Subjects:	Time series forecasting LSTM Prophet Hybrid model Seasonality
Online Access:	https://peerj.com/articles/cs-1001.pdf

Similar Items

Forecasting the Monkeypox Outbreak Using ARIMA, Prophet, NeuralProphet, and LSTM Models in the United States
by: Bowen Long, et al.
Published: (2023-01-01)

AIR QUALITY INDEX FORECASTING USING HYBRID NEURAL NETWORK MODEL WITH LSTM ON AQI SEQUENCES
by: Shirshendu Roy, et al.
Published: (2020-12-01)

Time series forecasting of stock market using ARIMA, LSTM and FB prophet
by: Sunki Asha, et al.
Published: (2024-01-01)

Forecasting of Electric Load Using a Hybrid LSTM-Neural Prophet Model
by: Md Jamal Ahmed Shohan, et al.
Published: (2022-03-01)

Time-Series Forecasting of Seasonal Data Using Machine Learning Methods
by: Vadim Kramar, et al.
Published: (2023-05-01)

Cluster-based LSTM models to improve Dengue cases forecast
by: Juan Vicente Bogado Machuca, et al.
Published: (2023-05-01)

Improving demand forecasting with LSTM by taking into account the seasonality of data
by: Hossein Abbasimehr, et al.
Published: (2020-03-01)

Comparing Prophet and Deep Learning to ARIMA in Forecasting Wholesale Food Prices
by: Lorenzo Menculini, et al.
Published: (2021-09-01)

A CNN–BiLSTM Architecture for Macroeconomic Time Series Forecasting
by: Alessio Staffini
Published: (2023-06-01)

Domain Fusion CNN-LSTM for Short-Term Power Consumption Forecasting
by: Xiaorui Shao, et al.
Published: (2020-01-01)

Forecasting cauliflower prices in Nepal: a comparative analysis using seasonal time series and nonlinear models
by: Anisha Giri, et al.
Published: (2024-12-01)

Time Series Analysis and Forecasting of Air Pollutants Based on Prophet Forecasting Model in Jiangsu Province, China
by: Ahmad Hasnain, et al.
Published: (2022-07-01)

Comparative analysis of stock price ARIMA and LSTM forecasting methods
by: Aivaras Bielskis, et al.
Published: (2022-12-01)

An Advanced CNN-LSTM Model for Cryptocurrency Forecasting
by: Ioannis E. Livieris, et al.
Published: (2021-01-01)

Short term electricity load forecasting using hybrid prophet-LSTM model optimized by BPNN
by: Tasarruf Bashir, et al.
Published: (2022-11-01)

Typhoon Intensity Forecasting Based on LSTM Using the Rolling Forecast Method
by: Shijin Yuan, et al.
Published: (2021-03-01)

Big data analytics for relative humidity time series forecasting based on the LSTM network and ELM
by: Kurnianingsih Kurnianingsih, et al.
Published: (2023-11-01)

Aggregating Prophet and Seasonal Trend Decomposition for Time Series Forecasting of Italian Electricity Spot Prices
by: Stefano Frizzo Stefenon, et al.
Published: (2023-01-01)

Web Traffic Time Series Forecasting Using LSTM Neural Networks with Distributed Asynchronous Training
by: Roberto Casado-Vara, et al.
Published: (2021-02-01)

A Bayesian Optimization-Based LSTM Model for Wind Power Forecasting in the Adama District, Ethiopia
by: Ejigu Tefera Habtemariam, et al.
Published: (2023-02-01)

A New Approach for the 10.7-cm Solar Radio Flux Forecasting: Based on Empirical Mode Decomposition and LSTM
by: Junqi Luo, et al.
Published: (2021-06-01)

Hybrid Method for Short-Term Time Series Forecasting Based on EEMD
by: Yujun Yang, et al.
Published: (2020-01-01)

Dynamically-biased fixed-point LSTM for time series processing in AIoT edge device
by: Hu, Jinhai, et al.
Published: (2024)

A Comparison of ARIMAX, VAR and LSTM on Multivariate Short-Term Traffic Volume Forecasting
by: Bhanuka Dissanayake, et al.
Published: (2021-01-01)

Combining Forecasts of Time Series with Complex Seasonality Using LSTM-Based Meta-Learning
by: Grzegorz Dudek
Published: (2023-07-01)

A case study of NeuralProphet and nonlinear evaluation for high accuracy prediction in short-term forecasting in PV solar plant
by: Ricardo Manuel Arias Velásquez
Published: (2022-09-01)

Application of the Hybrid Forecasting Models to Road Traffic Accidents in Algeria
by: Fatih Chellai
Published: (2022-06-01)

Robust LSTM With Tuned-PSO and Bifold-Attention Mechanism for Analyzing Multivariate Time-Series
by: Andri Pranolo, et al.
Published: (2022-01-01)

Traffic Forecasting of Back Servers Based on ARIMA-LSTM-CF Hybrid Model
by: Erzhuang Yao, et al.
Published: (2023-04-01)

Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators
by: Deniz Can Yıldırım, et al.
Published: (2021-01-01)

Adaptive Forecasting in Energy Consumption: A Bibliometric Analysis and Review
by: Manuel Jaramillo, et al.
Published: (2024-01-01)

Electric vehicle charging load prediction based on variational mode decomposition and Prophet-LSTM
by: Nuo Cheng, et al.
Published: (2023-11-01)

hLSTM-Aging: A Hybrid LSTM Model for Software Aging Forecast
by: Felipe Battisti, et al.
Published: (2022-06-01)

The Discharge Forecasting of Multiple Monitoring Station for Humber River by Hybrid LSTM Models
by: Yue Zhang, et al.
Published: (2022-06-01)

Forecasting Particulate Matter Emissions Using Time Series Models
by: S. Suresh, M. R. Sindhumol, M. Ramadurai, D. Kalvinithi and M. Sangeetha
Published: (2023-03-01)

Clustering and Deep-Learning for Energy Consumption Forecast in Smart Buildings
by: Desiree Arias-Requejo, et al.
Published: (2023-01-01)

EMDFormer model for time series forecasting
by: Ana Lazcano de Rojas, et al.
Published: (2024-03-01)

Spatiotemporal prediction of O3 concentration based on the KNN-Prophet-LSTM model
by: Biao Zhang, et al.
Published: (2022-11-01)

Energy Time Series Forecasting Based on Empirical Mode Decomposition and FRBF-AR Model
by: Wenquan Xu, et al.
Published: (2019-01-01)

Evolutionary Hybrid System for Energy Consumption Forecasting for Smart Meters
by: Diogo M. F. Izidio, et al.
Published: (2021-03-01)