Add to ORKGDuring recent decades, several studies have been conducted in the field of weather forecasting providing various promising forecasting models. Nevertheless, the accuracy of the predictions still remains a challenge. In this paper a new forecasting approach is proposed: it implements a deep neural network based on a powerful feature extraction. The model is capable of deducing the irregular structure, non-linear trends and significant representations as features learnt from the data. It is a 6-layered deep architecture with 4 hidden units of Restricted Boltzmann Machine (RBM). The extracts from the last hidden layer are pre-processed, to support the accuracy achieved by the forecaster. The forecaster is a 2-layer ANN model with 35 hidden uni...
Deep learning based forecasting methods have become the methods of choice in many applications of ti...
The success of deep learning techniques over the last decades has opened up a new avenue of research...
Making deductions and expectations about climate has been a challenge all through mankind's history....
During recent decades, several studies have been conducted in the field of weather forecasting provi...
Nature brings time series data everyday and everywhere, for example, weather data, physiological sig...
In recent years, deep learning techniques have outperformed traditional models in many machine learn...
Weather forecasting is a challenging time series forecasting problem because of its dynamic, continu...
It is well-known that numerical weather prediction (NWP) models require considerable computer power ...
Time series forecasting has recently emerged as a crucial study area with a wide spectrum of real-wo...
Weather and climate prediction is dominated by high dimensionality, interactions on many different s...
A time series is a sequence of time-ordered data, and it is generally used to describe how a phenome...
AbstractTime series prediction appear in many real-world problems, e.g., financial market, signal pr...
Time series forecasting is regarded amongst the top 10 challenges in data mining. Lately, deep learn...
AbstractWeather forecasting has become an important field of research in the last few decades. In mo...
This paper will be covering AI techniques in the prediction of climate change data over the course o...
Deep learning based forecasting methods have become the methods of choice in many applications of ti...
The success of deep learning techniques over the last decades has opened up a new avenue of research...
Making deductions and expectations about climate has been a challenge all through mankind's history....
During recent decades, several studies have been conducted in the field of weather forecasting provi...
Nature brings time series data everyday and everywhere, for example, weather data, physiological sig...
In recent years, deep learning techniques have outperformed traditional models in many machine learn...
Weather forecasting is a challenging time series forecasting problem because of its dynamic, continu...
It is well-known that numerical weather prediction (NWP) models require considerable computer power ...
Time series forecasting has recently emerged as a crucial study area with a wide spectrum of real-wo...
Weather and climate prediction is dominated by high dimensionality, interactions on many different s...
A time series is a sequence of time-ordered data, and it is generally used to describe how a phenome...
AbstractTime series prediction appear in many real-world problems, e.g., financial market, signal pr...
Time series forecasting is regarded amongst the top 10 challenges in data mining. Lately, deep learn...
AbstractWeather forecasting has become an important field of research in the last few decades. In mo...
This paper will be covering AI techniques in the prediction of climate change data over the course o...
Deep learning based forecasting methods have become the methods of choice in many applications of ti...
The success of deep learning techniques over the last decades has opened up a new avenue of research...
Making deductions and expectations about climate has been a challenge all through mankind's history....