The exhaust gas temperature (EGT) baseline of an aeroengine is key to accurately analyzing engine health, formulating maintenance decisions and ensuring flight safety. However, due the complex performance characteristics constraints many external factors, it difficult obtain accurate non-linear features between various operating factors EGT. In order diagnose forecast quickly accurately, four d...

Daily groundwater level is an indicator of resources. Accurate and reliable (GWL) prediction crucial for resources management land subsidence risk assessment. In this study, a representative deep learning model, long short-term memory (LSTM), adopted to predict with the selected predictors by partial mutual information (PMI), bootstrap employed generate different samples combination training ma...

Micro-Electric Discharge Machining (μ-EDM) is one of the widely applied micromanufacturing processes. However, it has several limitations, such as a low cutting rate, difficult debris removal, and poor surface integrity, etc. Hybridization μ-EDM proposed an alternative to overcome process limitations. Conversely, complicates nature poses challenge for modelling predicting critical responses. Th...

Across the world, healthcare systems are under stress and this has been hugely exacerbated by COVID pandemic. Key Performance Indicators (KPIs), usually in form of time-series data, used to help manage that stress. Making reliable predictions these indicators, particularly for emergency departments (ED), can facilitate acute unit planning, enhance quality care optimise resources. This motivates...

The complexity and changefulness of inland navigation environment in space time makes it hard to guarantee the applicability accuracy existing ship speed models. In this paper, a novel method for modelling under complex changeful is proposed. Firstly, an unsupervised machine learning algorithm, Density-Based Spatial Clustering Application with Noise (DBSCAN), utilized cluster environmental data...