Investigating important and necessary conditions to analyse traffic noise levels at intersections in mid-sized cities
Traffic noise is a major problem for urban residents, especially near intersections. In order to
effectively manage and control traffic noise, there is a need for a better understanding of …
effectively manage and control traffic noise, there is a need for a better understanding of …
Heavy metal concentrations in the soil near illegal landfills in the vicinity of agricultural areas—artificial neural network approach
Purpose To anticipate the impact of illegal landfills, development of new models should
become a part of environmental risk management strategies. One of such approaches …
become a part of environmental risk management strategies. One of such approaches …
Predicting road traffic accidents—Artificial neural network approach
Road traffic accidents are a significant public health issue, accounting for almost 1.3 million
deaths worldwide annually, with millions more experiencing non-fatal injuries. A variety of …
deaths worldwide annually, with millions more experiencing non-fatal injuries. A variety of …
Unlocking the Potential of the ANN Optimization in Sweet Potato Varieties Drying Processes
This study explores the unexploited potential of Artificial Neural Network (ANN) optimization
techniques in enhancing different drying methods and their influence on the characteristics …
techniques in enhancing different drying methods and their influence on the characteristics …
Random effect generalized linear model-based predictive modelling of traffic noise
Noise pollution is one of the negative consequences of growth and development in cities.
Traffic noise pollution due to traffic growth is the main aspect that worsens city quality of life …
Traffic noise pollution due to traffic growth is the main aspect that worsens city quality of life …
Chemometric approach to pesticide residue analysis in surface water
Dimethachlor is an herbicide used for oilseed rape protection. Previous studies have
demonstrated its high mobility in the soil, which could lead to water contamination. This …
demonstrated its high mobility in the soil, which could lead to water contamination. This …
Traffic noise prediction model using GIS and ensemble machine learning: a case study at Universiti Teknologi Malaysia (UTM) Campus
This study represents a pioneering effort to integrate geographic information systems (GIS)
and ensemble machine learning methods to predict noise levels on a university campus …
and ensemble machine learning methods to predict noise levels on a university campus …
Modeling the Effect of Selected Microorganisms' Exposure to Molasses's High-Osmolality Environment
Featured Application Developed mathematical models and correlations describing the
effects of the high-osmolality environment of sugar beet molasses on the viability of selected …
effects of the high-osmolality environment of sugar beet molasses on the viability of selected …
Osmotic Dehydration Model for Sweet Potato Varieties in Sugar Beet Molasses Using the Peleg Model and Fitting Absorption Data Using the Guggenheim–Anderson …
This study investigates the applicability of the Peleg model to the osmotic dehydration of
various sweet potato variety samples in sugar beet molasses, addressing a notable gap in …
various sweet potato variety samples in sugar beet molasses, addressing a notable gap in …
Road traffic noise prediction model based on artificial neural networks
This paper proposes a model based on machine learning for the prediction of road traffic
noise for the city of Bogota-Colombia. The input variables of the model were: vehicle …
noise for the city of Bogota-Colombia. The input variables of the model were: vehicle …