Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …

A critical review of the existing Internal Combustion Engine (ICE) modeling, optimization,
diagnosis, and control challenges and the promising state-of-the-art Machine Learning (ML) …

Breast cancer is a top dangerous killer for women. An accurate early diagnosis of breast
cancer is the primary step for treatment. A novel breast cancer detection model called …

Efficient control of automotive engine idle speed is crucial for achieving better fuel economy
and smoother engine running. This paper presents a comparison between proportional …

In this paper, an extreme learning machine (ELM)-based adaptive output feedback
command filtered control method is investigated for nonlinear nonaffine pure-feedback …

This paper presents an original model reference adaptive fractional-order proportional
integral derivative (MRAC-FOPID) controller for the stabilization of the idle speed system in …

For series hybrid electric vehicles, due to the limitation of engine operating characteristics,
speed regulation is usually performed using discrete operating points. This leads to the …

Much recently, based on the discrete-time nonlinear output regulation (NOR) theory, a
neural network (NN) method combined with feedforward friction compensation was …

Combustion engine speed control faces significant uncertainties in parameters like mass
equivalent coefficient and efficiency. To address these challenges, this research develops …

Profiting from the great progress of information technology, a huge number of multi-label
samples are available in our daily life. As a result, multi-label classification has aroused …