When the classical H∞ algorithm (HIF) is applied to estimate state of charge (SOC) a lithium battery, influence historical data usually ignored, resulting in an increase estimation error. In order improve accuracy SOC estimation, this paper proposes extended exponential weighted moving average (EE-HIF) view data. By designing Gaussian function, distribution at different times can effectively re...

The production of palm kernel is a significant product for the company and plays crucial role. Nevertheless, stability not always consistent, quality can be detrimental to company. As consumer demands change over time, companies must anticipate every fluctuation in production. Hence it vital figure long run with settlement prepare utilizing information mining within past. Triple Exponential Smo...

With advancements in machine-learning techniques, stock-price movements can ostensibly be forecasted using time-series data. In this study, several different types of long short-term memory (LSTM) are used to predict the closing prices Japanese stocks five days into future. Also, four features [i.e., simple moving average (SMA), linear weighted (WMA), exponential WMA (EMA), and Savitzky–Golay (...

Today, neuroscientists are interested in discovering human brain functions through brain networks. In this regard, the evaluation of dynamic changes in functional connectivity of the brain regions by using functional magnetic resonance imaging data has attracted their attention. In this paper, we focus on two model-based approaches, called the exponential weighted moving average model and the d...

Recently, deep neural networks have demonstrated comparable and even better performance than board-certified ophthalmologists in well-annotated datasets. However, the diversity of retinal imaging devices poses a significant challenge: domain shift, which leads to degradation when applying learning models trained on one new testing domains. In this paper, we propose adaptation framework comprisi...