Comprehensive Analysis of Time Series Forecasting Using Neural Networks

by   Manie Tadayon, et al.

Time series forecasting has gained lots of attention recently; this is because many real-world phenomena can be modeled as time series. The massive volume of data and recent advancements in the processing power of the computers enable researchers to develop more sophisticated machine learning algorithms such as neural networks to forecast the time series data. In this paper, we propose various neural network architectures to forecast the time series data using the dynamic measurements; moreover, we introduce various architectures on how to combine static and dynamic measurements for forecasting. We also investigate the importance of performing techniques such as anomaly detection and clustering on forecasting accuracy. Our results indicate that clustering can improve the overall prediction time as well as improve the forecasting performance of the neural network. Furthermore, we show that feature-based clustering can outperform the distance-based clustering in terms of speed and efficiency. Finally, our results indicate that adding more predictors to forecast the target variable will not necessarily improve the forecasting accuracy.


page 1

page 2

page 3

page 4


Sales forecasting using WaveNet within the framework of the Kaggle competition

We took part in the Corporacion Favorita Grocery Sales Forecasting compe...

Adjusting for Autocorrelated Errors in Neural Networks for Time Series Regression and Forecasting

In many cases, it is difficult to generate highly accurate models for ti...

Smart Data Representations: Impact on the Accuracy of Deep Neural Networks

Deep Neural Networks are able to solve many complex tasks with less engi...

Process Model Forecasting Using Time Series Analysis of Event Sequence Data

Process analytics is an umbrella of data-driven techniques which include...

Improved Sales Forecasting using Trend and Seasonality Decomposition with LightGBM

Retail sales forecasting presents a significant challenge for large reta...

Time Series Forecasting Models Copy the Past: How to Mitigate

Time series forecasting is at the core of important application domains ...

Please sign up or login with your details

Forgot password? Click here to reset