Signal selection for local module identification in linear dynamic networks: A graphical approach

In a dynamic network of interconnected transfer functions, it is not necessary to use all the node signals for estimating a local transfer function. Given the network topology, detailed conditions are available for selecting inputs and outputs in a (MIMO) predictor model that warrants consistent and minimum variance estimation of a target...

Prediction & optimization of alkali-activated concrete based on the random forest machine learning algorithm

Alkali-activated concrete (AAC) is regarded as a promising alternative construction material to reduce the CO₂ emission induced by Portland cement (PC) concrete. Due to the diversity in raw materials and complexity of reaction mechanisms, a commonly applied design code is still absent to date. This study attempts to directly...