AIMC Topic: Gasoline

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Sulfuric Acid-Driven Nucleation Enhanced by Amines from Ethanol Gasoline Vehicle Emission: Machine Learning Model and Mechanistic Study.

Environmental science & technology Dec 5, 2024
The sulfuric acid (SA)-amine nucleation mechanism gained increasing attention due to its important role in atmospheric secondary particle formation. However, the intrinsic enhancing potential (IEP) of various amines remains largely unknown, restraini...
Machine Learning Ethanol Sulfuric Acids Gasoline Vehicle Emissions Amines
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Urban road BC emissions of LDGVs: Machine learning models using OBD/PEMS data.

Chemosphere Sep 14, 2024
Urban Black Carbon (BC) emissions from light-duty gasoline vehicles (LDGVs) are challenging to quantify in real-world settings. This study employed a Portable Emission Measurement System (PEMS) to assess BC emissions from five LDGVs on urban roads. W...
Gasoline Machine Learning Soot Cities China Environmental Monitoring Air Pollutants Vehicle Emissions
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Optimizing soybean biofuel blends for sustainable urban medium-duty commercial vehicles in India: an AI-driven approach.

Environmental science and pollution research international Apr 23, 2024
This article presents the outcomes of a research study focused on optimizing the performance of soybean biofuel blends derived from soybean seeds specifically for urban medium-duty commercial vehicles. The study took into consideration elements such ...
Biofuels Glycine max Artificial Intelligence India Vehicle Emissions Gasoline
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Optimization of diesel engine performance and emission using waste plastic pyrolytic oil by ANN and its thermo-economic assessment.

Environmental science and pollution research international Apr 20, 2023
The current study focuses on the engine performance and emission analysis of a 4-stroke compression ignition engine powered by waste plastic oil (WPO) obtained by the catalytic pyrolysis of medical plastic wastes. This is followed by their optimizati...
Vehicle Emissions Gasoline Plastics Pyrolysis Neural Networks, Computer
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Novel Method for Determining Internal Combustion Engine Dysfunctions on Platform as a Service.

Sensors (Basel, Switzerland) Jan 2, 2023
This article deals with a unique, new powertrain diagnostics platform at the level of a large number of EU25 inspection stations. Implemented method uses emission measurement data and additional data from significant sample of vehicles. An original t...
Vehicle Emissions Cloud Computing Gasoline Machine Learning
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A powerful tool for near-infrared spectroscopy: Synergy adaptive moving window algorithm based on the immune support vector machine.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jul 14, 2022
Traditional trial-and-error methods are time-consuming and inefficient, especially very unfriendly to inexperienced analysts, and are sometimes still used to select preprocessing methods or wavelength variables in near-infrared spectroscopy (NIR). To...
Gasoline Support Vector Machine Least-Squares Analysis Algorithms Spectroscopy, Near-Infrared
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Analysis of noise pollution emitted by stationary MF285 tractor using different mixtures of biodiesel, bioethanol, and diesel through artificial intelligence.

Environmental science and pollution research international May 26, 2019
In the present study, the noise pollution from different compositions of biodiesel, bioethanol, and diesel fuels in a four-cylinder and four-stroke engine of MF285 tractor was studied. Further, the noise pollution was measured from two positions, the...
Gasoline Noise, Transportation Noise Biofuels Artificial Intelligence Environmental Monitoring
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An efficient swarm intelligence approach to feature selection based on invasive weed optimization: Application to multivariate calibration and classification using spectroscopic data.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jan 12, 2018
Variable selection plays a key role in classification and multivariate calibration. Variable selection methods are aimed at choosing a set of variables, from a large pool of available predictors, relevant to the analyte concentrations estimation, or ...
Wine Artificial Intelligence Least-Squares Analysis Calibration Algorithms Gasoline Triticum Plant Weeds Introduced Species
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Modeling of yield and environmental impact categories in tea processing units based on artificial neural networks.

Environmental science and pollution research international Sep 30, 2017
In this study, an artificial neural network (ANN) model was developed for predicting the yield and life cycle environmental impacts based on energy inputs required in processing of black tea, green tea, and oolong tea in Guilan province of Iran. A li...
Global Warming Tea Gasoline Environmental Pollution Humans Iran Neural Networks, Computer Food-Processing Industry Eutrophication
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Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine.

Environmental science and pollution research international Sep 20, 2017
The purpose of this study is to investigate the performance, emission and combustion characteristics of a four-cylinder common-rail turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends. A kernel-based extreme learning machi...
Machine Learning Biofuels Jatropha Vehicle Emissions Gasoline
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