Appropriate maintenance of industrial equipment keeps production systems in good health
and ensures the stability of production processes. In specific production sectors, such as the …

Data-driven models for industrial energy savings heavily rely on sensor data,
experimentation data and knowledge-based data. This work reveals that too much research …

Abstract The versatility of Artificial Intelligence (AI) in process systems is not restricted to
modelling and control only, but also as estimators to estimate the unmeasured parameters …

The growing internet concern (IC) over the crude oil market and related events influences
market trading, thus creating further instability within the oil market itself. We propose a …

Commodity price forecasting is challenging full of volatility, uncertainty and complexity. In
this paper, a novel modeling framework is proposed to predict the market price of commodity …

Price instability is a paramount concern since commodity prices are associated with the
livelihood and the economy of a nation as a whole; any extraordinary price fluctuation in the …

A new methodology for optimizing heat-integrated crude oil distillation systems is proposed
in this work. The new procedure considers an artificial neural networks (ANN) model for …

This paper presents a novel optimization-based approach for the design of heat-integrated
crude oil distillation units, which are widely used in refineries. The methodology presented …

This study is deals with artificial neural network (ANN) and fuzzy expert system (FES)
modelling of a gasoline engine to predict engine power, torque, specific fuel consumption …

Due to the difference of variable positions brought by process structure, time-delay exists
between process variables and quality variables. In this paper, this commonly overlooked …