Web Traffic Time Series Forecasting Using LSTM Neural Networks with Distributed Asynchronous Training

Web Traffic Time Series Forecasting Using LSTM Neural Networks with Distributed Asynchronous Training

Evaluating web traffic on a web server is highly critical for web service providers since, without a proper demand forecast, customers could have lengthy waiting times and abandon that website. However, this is a challenging task since it requires making reliable predictions based on the arbitrary n...

Full description

Bibliographic Details
Main Authors:	Roberto Casado-Vara, Angel Martin del Rey, Daniel Pérez-Palau, Luis de-la-Fuente-Valentín, Juan M. Corchado
Format:	Article
Language:	English
Published:	MDPI AG 2021-02-01
Series:	Mathematics
Subjects:	web traffic forecast time series forecast LSTM parameter averaging Downpour strategy pattern extraction
Online Access:	https://www.mdpi.com/2227-7390/9/4/421

Similar Items

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

Analyses of the convection character and forecast difficulty of autumn typhoon inverted trough heavy downpour
by: Aifen FAN, et al.
Published: (2022-06-01)

Forecasting the Traffic Flow by Using ARIMA and LSTM Models: Case of Muhima Junction
by: Vienna N. Katambire, et al.
Published: (2023-11-01)

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

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)

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

Forecasting Spatially-Distributed Urban Traffic Volumes via Multi-Target LSTM-Based Neural Network Regressor
by: Alessandro Crivellari, et al.
Published: (2020-12-01)

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

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

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

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

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

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 hybrid forecasting model using LSTM and Prophet for energy consumption with decomposition of time series data
by: Serdar Arslan
Published: (2022-06-01)

Dynamic Learning Framework for Smooth-Aided Machine-Learning-Based Backbone Traffic Forecasts
by: Mohamed Khalafalla Hassan, et al.
Published: (2022-05-01)

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

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

Traffic Flow Forecast Through Time Series Analysis Based on Deep Learning
by: Jianhu Zheng, et al.
Published: (2020-01-01)

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)

A Hybrid CNN-LSTM Model for Traffic Accident Frequency Forecasting During the Tourist Season
by: Sinan Uğuz, et al.
Published: (2022-01-01)

Day-Ahead Nonparametric Probabilistic Forecasting of Photovoltaic Power Generation Based on the LSTM-QRA Ensemble Model
by: Fei Mei, et al.
Published: (2020-01-01)

Forecasting Nonlinear Systems with LSTM: Analysis and Comparison with EKF
by: Juan Pedro Llerena Caña, et al.
Published: (2021-03-01)

Short-Term Net Load Forecasting with Singular Spectrum Analysis and LSTM Neural Networks
by: Akylas Stratigakos, et al.
Published: (2021-07-01)

Using the LSTM Network to Forecast the Demand for Electricity in Poland
by: Anna Manowska
Published: (2020-11-01)

LogLS: Research on System Log Anomaly Detection Method Based on Dual LSTM
by: Yiyong Chen, et al.
Published: (2022-02-01)

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

Multi-Behavior with Bottleneck Features LSTM for Load Forecasting in Building Energy Management System
by: Van Bui, et al.
Published: (2021-04-01)

Electrical Load Forecast by Means of LSTM: The Impact of Data Quality
by: Alfredo Nespoli, et al.
Published: (2021-02-01)

Time-series Models Forecasting Performance in the Baltic Stock Market
by: Žana Grigaliūnienė
Published: (2013-05-01)

Determining the Future Demand: Studies for Air Traffic Forecasting Remove
by: Phyoe, Su Myat, et al.
Published: (2016)

FORECASTING AIR TRAFFIC VOLUMES USING SMOOTHING TECHNIQUES
by: Emrah Önder, et al.
Published: (2014-01-01)

Comparing Inflation Forecasting Models in Iran: New Evidences from ARDL-D-LSTM Model
by: Hamed Azizi Ganzagh, et al.
Published: (2022-12-01)

Spectral temporal graph neural network for multivariate agricultural price forecasting
by: Cevher Özden, et al.
Published: (2023-07-01)

A Combined Model Incorporating Improved SSA and LSTM Algorithms for Short-Term Load Forecasting
by: Mingchong Han, et al.
Published: (2022-06-01)

Short-Term Photovoltaic Power Forecasting Using an LSTM Neural Network and Synthetic Weather Forecast
by: Mohammad Safayet Hossain, et al.
Published: (2020-01-01)

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)

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

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

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