Forecasting time series by using deep neural networks

Forecasting and time series analysis plays a crucial role in many applications such as complex networks, demand forecasting, financial predictions, patient response to prescribed drugs, etc. In general, time series data behaves as a highly nonlinear process because of its stochastic nature; for inst...

• Huvudupphovsman: Vega Arellano, Oscar Andrés (author)
• Materialtyp: bachelorThesis
• Språk: eng
• Publicerad: 2021
• Ämnen: Predicción de series de tiempo; Redes neuronales profundas (DNNs); Perceptron multicapa (MLP); Memoria de largo plazo (LSTM); Redes neuronales convolucionales (CNN); Ventana deslizante; Time series forecasting; Deep Neural Networks (DNNs); Multilayer Perceptron (MLP); Long Short-Term Memory (LSTM); Convolutional Neural Network (CNN); Sliding window
• Länkar: http://repositorio.yachaytech.edu.ec/handle/123456789/430