Lithium-Ion batteries require step-ahead information to apply contingency plans prevent them from operating beyond their safe operation thresholds in grid storage and electric vehicle applications. Recently, machine learning techniques have been increasingly applied forecast one such battery metric, State-of-Charge % ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://w...

This paper proposes an electricity demand and price forecast model of the smart city large datasets using a single comprehensive Long Short-Term Memory (LSTM) based on sequence-to-sequence network. Real market data from Australian Energy Market Operator (AEMO) is used to validate effectiveness proposed model. Several simulations with different configurations are executed actual produce reliable...

The power unit on board the ship generates periodic low-frequency vibration that affects normal operation of equipment board, and adaptive feedforward control algorithm can effectively suppress such harmful noise. But needs to obtain identification model secondary channels, frequency domain least squares method based linear Extended auto-regressive (ARX) is difficult with nonlinear characterist...

Denitrification and arginine fermentation are major parts of the anaerobic metabolism of Pseudomonas aeruginosa, which is important for biofilm formation and infection. The two-component regulatory system NarX-NarL is part of the underlying network and is required for denitrifying growth. All target promoters identified so far are activated by NarL. In this study the effect of NarL on arginine ...

The complexity of helicopter flight dynamics makes modeling and helicopter system identification a very difficult task. Most of the traditional techniques require a model structure to be defined a priori and in case of helicopter dynamics, this is difficult due to its complexity and the interplay between various subsystems. To overcome this difficulty, non-parametric approaches are commonly ado...

In order to meet the new stringent environmental regulations, it is necessary to investigate the adaptive and optimal control strategies for the biological wastewater treatment processes. Nitrogen removal is one of the essential concerns in wastewater treatment. Nitrogen removal is a nonlinear, dynamic, and time variant complex process as complicated activities of microbial metabolism are invol...

A new unified modelling framework based on the superposition of additive submodels, functional components, and wavelet decompositions is proposed for nonlinear system identification. A nonlinear model, which is often represented using a multivariate nonlinear function, is initially decomposed into a number of functional components via the well known analysis of variance (ANOVA) expression, whic...