Chemical Analysis

Classification of a substance’s constituent elements


Articles & Tech Transfers


Pattern recognition for sensor array signals using Fuzzy ARTMAP
Abstract A Fuzzy ARTMAP classifier for pattern recognition in chemical sensor array was developed based on Fuzzy Set Theory and Adaptive Resonance Theory. In contrast to most current classifiers with difficulty in detecting new ...

Adaptive resonance theory based neural network for supervised chemical pattern recognition (FuzzyARTMAP) [1] Theory and network properties
Abstract The FuzzyARTMAP algorithm is studied with respect to its usefulness for supervised chemical pattern recognition. The theory of this relatively complex artificial neural classifier is presented in detail for chemists. An ...

Adaptive resonance theory based neural network for supervised chemical pattern recognition (FuzzyARTMAP) [2] Classification of post-consumer plastics by remote NIR spectroscopy using an InGaAs diode a
Abstract The supervised working FuzzyARTMAP pattern recognition algorithm has been applied to automated identification of post-consumer plastics by near-infrared spectroscopy (NIRS). Experimentally, a remote operating parallel ...

Classification of single particles analyzed by ATOFMS using an artificial neural network, ART-2A
Abstract Aerosol particles have received significant public and scientific attention in recent years due to studies linking them to global climatic changes and human health effects. In 1994, Prather et al, (Prather, K. A.; Nordmeyer, ...

Fuzzy ARTMAP based electronic nose data analysis
Abstract The Fuzzy ARTMAP neural network is a supervised pattern recognition method based on fuzzy adaptive resonance theory (ART). It is a promising method since Fuzzy ARTMAP is able to carry out on-line learning without forgetting ...

Inference of common genetic network using fuzzy adaptive resonance theory associated matrix methods
Abstract Inferring genetic networks from gene expression data is the most challenging work in the postgenomic era. However, most studies tend to show their genetic network inference ability by using artificial data. Here, we ...

A proteomic analysis of maize chloroplast biogenesis
Abstract Proteomics studies to explore global patterns of protein expression in plant and green algal systems have proliferated within the past few years. Although most of these studies have involved mapping of the proteomes of ...

Predicting bulk ambient aerosol compositions from ATOFMS data with ART-2a and multivariate analysis
Abstract The aerosol time-of-flight mass spectrometry (ATOFMS) has not generally been used to provide a quantitative estimation of chemical compositions of ambient aerosols. In an initial study, the possibility of developing a ...

Incorporating PCA and fuzzy-ART techniques into achieve organism classification based on codon usage consideration
Abstract To recognize the DNA sequence and mine the hidden information to achieve the classification of organisms are viewed as a difficult work to biologists. As we know, the amino acids are the basic elements to construct DNA. ...

Identification of long-range aerosol transport patterns to Toronto via classification of back trajectories by cluster analysis and neural network techniques
Abstract In this work, back trajectories of air masses arriving in Toronto were classified into distinct transport patterns by cluster analysis and, for the first time, by a neural network (Adaptive Resonance Theory-ART-2a). ...

Comparison of two cluster analysis methods using single particle mass spectra
Abstract Cluster analysis of aerosol time-of-flight mass spectrometry (ATOFMS) data has been an effective tool for the identification of possible sources of ambient aerosols. In this study, the clustering results of two typical ...

Odor discrimination using adaptive resonance theory
Abstract The paper presents two neural networks based on the adaptive resonance theory (ART) for the recognition of several odors subjected to drift. The neural networks developed by Grossberg (supervised and unsupervised) have been ...

Adaptive resonance neural classifier for identification of gases/odours using an integrated sensor array
Abstract A new approach to intelligent gas sensor (IGS) design using a classifier based on adaptive resonance theory (ART) artificial neural network (ANN) is presented. Using published data of sensor arrays fabricated and ...

Comparison of an adaptive resonance theory based neural network (ART-2a) against other classifiers for rapid sorting of post consumer plastics by remote near-infrared spectroscopic sensing using an In
Abstract An Adaptive Resonance Theory Based Artificial Neural Network (ART-2a) has been compared with Multilayer Feedforward Backpropagation of Error Neural Networks (MLF-BP) and with the SIMCA classifier. All three classifiers were ...

Adaptive resonance theory based neural networks - the ‘ART’ of real-time pattern recognition in chemical process monitoring?
Abstract The family of artificial neural networks based on Adaptive Resonance Theory (ART) forms a collection of distinct mathematical pattern recognition methods. The classification of sensor signals, process data analysis, spectral ...

Lithofacies identification using multiple adaptive resonance theory neural networks and group decision expert system
Abstract Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies ...

Airborne Particle Classification with a Combination of Chemical Composition and Shape Index Utilizing an Adaptive Resonance Artificial Neural Network
Abstract Airborne particle classification that leads to particle source identification is important to both the improvement of the environment and the protection of public health. In this study, individual airborne particles were ...

A Fuzzy ARTMAP-Based Quantitative Structure-Property Relationship (QSPR) for Predicting Physical Properties of Organic Compounds
Abstract A modified fuzzy ARTMAP neural-network-based QSPR for predicting normal boiling points, critical temperatures, and critical pressures of organic compounds was developed. Seven or eight molecular descriptors (the sum of ...

An Integrated SOM-Fuzzy ARTMAP Neural System for the Evaluation of Toxicity
Abstract Self-organized maps (SOM) have been applied to analyze the similarities of chemical compounds and to select from a given pool of descriptors the smallest and more relevant subset needed to build robust QSAR models based on ...