The conversion of wet waste (eg, food waste, sewage sludge, and animal manure) into
bioenergy is a promising strategy for sustainable energy generation and waste …

This work introduces a novel methodology for real-time optimization (RTO) of process
systems using reinforcement learning (RL), where optimal decisions in response to external …

With decreasing computational costs, improvement in algorithms, and the aggregation of
large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for …

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for
understanding these methods generated. Existing Python programming packages for …

The physical field (temperature, gas concentration, etc.) inside the furnace is closely related
to the boiler combustion optimization. A novel multi-objective prediction framework based on …

Digital Transformation integrates information technology across a broad spectrum of
industrial sectors. Industrial Cyber-Physical Systems (ICPS) play a vital role in this …

Generally, because the actual operating data tends to be concentrated in local regions due
to the habits of operators and control system design, single models can only train a …

Accurate NOx emission monitoring is essential for an in-depth understanding of the
combustion state. However, establishing an accurate emission prediction model based on …

The reduction of NOx emissions is a paramount endeavor in contemporary engineering and
energy production, as these emissions are closely linked to adverse environmental and …

Owing to the high toxicity of cerium toward living organisms, it is necessary to remove cerium
from aqueous solutions. In this regard, the extraction of cerium (Ce (III)) from nitrate media by …