The characterization and analysis of rock types based on acoustic emission (AE) signals have long been focal points in earth science research. However, traditional analysis methods struggle to handle the influx of big data. While signal processing me...
Accurately predicting the concentration of organochlorine pesticides (OCPs) presents a challenge due to their complex sources and environmental behaviors. In this study, we introduced a novel and advanced model that combined the power of three distin...
The reliability of solid rocket motor grain structure during solidification cooling is analyzed. First, a three-dimensional parametric modeling of the grain is carried out by ANSYS finite element software. The dangerous point and dangerous moment can...
This study investigates the impact of maternal health on infant development by developing a mathematical model that delineates the relationship between maternal health indicators and infant behavioral characteristics and sleep quality. The main contr...
Environmental science and pollution research international
Aug 13, 2024
The Colorado River has experienced a significant streamflow reduction in recent decades due to climate change, resulting in pronounced hydrological droughts that pose challenges to the environment and human activities. However, current models struggl...
Water science and technology : a journal of the International Association on Water Pollution Research
Aug 12, 2024
The primary objective of this study is to develop a robust model that employs a fuzzy logic interface (FL) and particle swarm optimization (PSO) to forecast the optimal parameters of a pyramid solar still (PSS). The model considers a range of environ...
Preparation of activated carbons is an important way to utilize municipal sludge (MS) resources, while drying is a pretreatment method for making activated carbons from MS. In this study, machine learning techniques were used to develop moisture rati...
This study examines the role of intellectual property protection (IPP) in enhancing radical technological innovation (RTI) within national research project teams, using an innovation-driven theory and an ability-motivation-opportunity (AMO) perspecti...
A parallel hybrid ordinary differential equation (ODE) integrating the Activated Sludge Model No. 2d (ASM2d) and an artificial neural network (ANN) was developed to simulate biological phosphorus removal (BPR) with high accuracy and interpretability....
Ensuring the interpretability of machine learning models in chemical engineering remains challenging due to inherent limitations and data quality issues, hindering their reliable application. In this study, a qualitatively implicit knowledge-guided m...
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