{"doi":"10.1080/00387019909349995","title":"Simultaneous Determination of Multicomponents in Air Toxic Organic Compounds Using Artificial Neural Networks in Ftir Spectroscopy","abstract":null,"journal":"Spectroscopy Letters","year":1999,"id":610008,"datarank":0.31191623125197543,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"self_citation_contribution":0.31191623125197543,"citation_network_contribution":0.0,"self_endowment_contribution":0.31191623125197543,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1568165,"name":"Shulin Yang","orcid":null,"position":1,"is_corresponding":false},{"id":1568166,"name":"Junde Wang","orcid":null,"position":2,"is_corresponding":false},{"id":1568167,"name":"Binghe Gu","orcid":null,"position":3,"is_corresponding":false},{"id":1467248,"name":"Fang Liu","orcid":"0000-0003-1522-5141","position":4,"is_corresponding":false},{"id":418221,"name":"Yan Li","orcid":"0000-0002-7884-8074","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Simultaneous Determination of Multicomponents in Air Toxic Organic Compounds Using Artificial Neural Networks in Ftir Spectroscopy","abstract":"The application of Artificial Neural Networks (ANNs) for nonlinear multivariate calibration using simulated FTIR data was demonstrated in this paper. Neural networks consisting of three layers of nodes were trained by using the back-propagation learning rule. Since parameters affect the performance of the network greatly, simulated data were used to train the network in order to get a satisfactory combination of all parameters. The mixtures of four air toxic organic compounds whose FTIR spectra are overlapped were chosen to evaluate the calibration and prediction ability of the network. The relative standard error (RSD%), the percent standard error of prediction samples (%SEP) and the percent standard error of calibration samples (%SEC) are used for evaluating the ability of the neural network.","is_dataset_classified":null,"base_score":2.0794415416798357,"endowment":2.0794415416798357,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"23304386","pmcid":null,"openalex_id":"https://openalex.org/W1985010875","authors":[],"funders":[],"total_grants":0,"fwci":1.0225,"citation_percentile":0.68990148,"influential_citations":0,"citation_trend":[{"year":2019,"count":1},{"year":2021,"count":1}],"oa_status":"closed","license":null,"oa_locations":[{"url":"https://www.tandfonline.com/doi/pdf/10.1080/00387019909349995","host_type":"publisher"},{"url":"https://doi.org/10.1080/00387019909349995","host_type":"journal"}],"fields_of_study":["Spectroscopy and Chemometric Analyses","Advanced Chemical Sensor Technologies","Water Quality Monitoring and Analysis"],"mesh_terms":[],"keywords":["Artificial neural network","Calibration","Biological system","Fourier transform infrared spectroscopy","Chemistry","Backpropagation","Spectroscopy","Approximation error","Analytical Chemistry (journal)","Artificial intelligence","Pattern recognition (psychology)","Statistics","Computer science","Algorithm","Chromatography","Mathematics","Engineering","Chemical engineering"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-31T18:29:14.441263Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}