{"doi":"10.1109/cec.2018.8477826","title":"A Hybrid Grammar-Based Genetic Programming for Symbolic Regression Problems","abstract":null,"journal":"2018 IEEE Congress on Evolutionary Computation (CEC)","year":2018,"id":597340,"datarank":0.24141568686511508,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"self_citation_contribution":0.24141568686511508,"citation_network_contribution":0.0,"self_endowment_contribution":0.24141568686511508,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"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":1530331,"name":"Joao M. De Freitas","orcid":null,"position":1,"is_corresponding":false},{"id":1530332,"name":"Felipe R. De Souza","orcid":null,"position":2,"is_corresponding":false},{"id":1530333,"name":"Heder S. Bernardino","orcid":null,"position":3,"is_corresponding":false},{"id":1530334,"name":"Itamar L. De Oliveira","orcid":null,"position":4,"is_corresponding":false},{"id":1530335,"name":"Helio J.C. Barbosa","orcid":null,"position":5,"is_corresponding":false},{"id":1530330,"name":"Flavio A.A. Motta","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"A Hybrid Grammar-Based Genetic Programming for Symbolic Regression Problems","abstract":"Genetic Programming (GP) is an important technique in evolutionary computing. There has been extensive research and great achievement in GP and its variants. Grammar-based genetic programming (GGP) is one of the most promising ones. We propose here a hybrid approach of GGP with Evolution Strategies (ES). GGP is used to evolve the structure of the models while ES searches for the numerical coefficients in order to improve the overall performance when solving symbolic regression problems. Computational experiments conducted on a set of test-cases reveal that the proposed hybrid approach achieved a good performance when compared to other methods from the literature.","is_dataset_classified":null,"base_score":1.6094379124341003,"endowment":1.6094379124341003,"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/W2897801744","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[{"year":2019,"count":1},{"year":2022,"count":1},{"year":2025,"count":2}],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://xplorestaging.ieee.org/ielx7/8466244/8477640/08477826.pdf?arnumber=8477826","host_type":"publisher"},{"url":"https://doi.org/10.1109/cec.2018.8477826","host_type":""}],"fields_of_study":["Evolutionary Algorithms and Applications","Metaheuristic Optimization Algorithms Research","Reinforcement Learning in Robotics"],"mesh_terms":[],"keywords":["Symbolic regression","Genetic programming","Computer science","Grammatical evolution","Grammar","Set (abstract data type)","Artificial intelligence","Genetic algorithm","Evolutionary computation","Machine learning","Theoretical computer science","Programming language"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Quality Education"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-28T12:59:28.151860Z","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":[]}