{"doi":"10.1063/5.0081651","title":"Short-term forecast the dynamics of changes in the surface concentration of methane using a non-linear autoregressive neural network with external input and vector autoregression model","abstract":null,"journal":"AIP Conference Proceedings","year":2022,"id":631742,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"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":1637292,"name":"Andrey Shichkin","orcid":null,"position":1,"is_corresponding":false},{"id":1637294,"name":"Alexander Buevich","orcid":null,"position":2,"is_corresponding":false},{"id":1637295,"name":"Anna Rakhmatova","orcid":null,"position":3,"is_corresponding":false},{"id":1637297,"name":"Maria Remezova","orcid":null,"position":4,"is_corresponding":false},{"id":1637291,"name":"Alexander Sergeev","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Short-term forecast the dynamics of changes in the surface concentration of methane using a non-linear autoregressive neural network with external input and vector autoregression model","abstract":"In our work, we compared two approaches for predicting changes in the concentration of one of the main greenhouse gases - methane. The study is based on surface methane concentration data obtained by monitoring the dynamics of changes in major greenhouse gases on the Arctic Island Belyy, Russia. We used a nonlinear autoregressive neural network with an external input (NARX), and a vector regression model. An artificial neural network type NARX was more accurate for predicting methane concentration changes.","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19910364","pmcid":null,"openalex_id":"https://openalex.org/W4226315710","authors":[],"funders":[],"total_grants":0,"fwci":0.0,"citation_percentile":0.04907598,"influential_citations":0,"citation_trend":[],"oa_status":"green","license":"other-oa","oa_locations":[{"url":"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128520649&doi=10.1063%2f5.0081651&partnerID=40&md5=33167a0e57c2aaf23b13e88311dc3a9f","host_type":"repository"},{"url":"https://www.scopus.com/inward/record.uri?eid=2-s2.0-85128520649&doi=10.1063%2f5.0081651&partnerID=40&md5=33167a0e57c2aaf23b13e88311dc3a9f","host_type":"repository"},{"url":"http://aip.scitation.org/doi/pdf/10.1063/5.0081651","host_type":"publisher"},{"url":"https://doi.org/10.1063/5.0081651","host_type":"journal"}],"fields_of_study":["Atmospheric and Environmental Gas Dynamics","Air Quality Monitoring and Forecasting","Energy Load and Power Forecasting"],"mesh_terms":[],"keywords":["Nonlinear autoregressive exogenous model","Autoregressive model","Methane","Artificial neural network","Nonlinear system","Term (time)","Vector autoregression","Computer science","Environmental science","Econometrics","Mathematics","Artificial intelligence","Chemistry","Physics"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Life below water"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T00:35:37.717920Z","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":[]}