Museum contents are vulnerable to bad ambience conditions and human vandalization.
Preserving the contents of museums is a duty towards humanity. In this paper, we develop …

In this work, we introduce a new modeling and inferential tool for dynamical processing of
time series. The approach is called recurrent dictionary learning (RDL). The proposed model …

Foreign exchange (Forex) rate forecasting is presently pursued by many researchers as it
plays an important role in financial technology and business. The challenge of Forex …

As a developing country, Indonesia is affected by fluctuations in foreign exchange rates,
especially the US Dollar. Determination of foreign exchange rates must be profitable so a …

In a different area of a field of the real life, problem of accurate forecasting has acquired
great importance that present the interesting serve which led to the best ways to achieve a …

This work proposes a new approach for dynamical modeling; we call it sequential transform
learning. This is loosely based on the transform (analysis dictionary) learning formulation …

Buku ini merupakan kasus keempat dari seri implementasi jaringan syaraf tiruan
Backpropagation menggunakan PYTHON GUI. Buku ini merupakan versi bahasa Indonesia …

The global foreign currency exchange market is among the top financial markets worldwide.
Predicting forex rates is a concern because of forex rates volatility. We explore the use of …

In this study, we develop a predictive model using two Machine Learning (ML) techniques:
Artificial Neural Network (ANN) and Deep Learning (DL) architecture called Long Short …

Buku ini merupakan kasus keempat dari seri implementasi jaringan syaraf tiruan
Backpropagation menggunakan PYTHON GUI. Buku ini menyajikan penjelasan praktis …