{"id":"https://openalex.org/W7118183861","doi":"https://doi.org/10.1007/s44163-025-00726-7","title":"An efficient and high-quality circuit schematic generation method based on action mask and graph neural network","display_name":"An efficient and high-quality circuit schematic generation method based on action mask and graph neural network","publication_year":2026,"publication_date":"2026-01-05","ids":{"openalex":"https://openalex.org/W7118183861","doi":"https://doi.org/10.1007/s44163-025-00726-7"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00726-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00726-7","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1007/s44163-025-00726-7","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121935786","display_name":"Jie Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Yang","raw_affiliation_strings":["Information Engineering University, Zhengzhou, 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering University, Zhengzhou, 450000, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032832863","display_name":"Kai Qiao","orcid":"https://orcid.org/0000-0001-7057-9562"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Qiao","raw_affiliation_strings":["Information Engineering University, Zhengzhou, 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering University, Zhengzhou, 450000, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121915704","display_name":"Jian Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Chen","raw_affiliation_strings":["Information Engineering University, Zhengzhou, 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering University, Zhengzhou, 450000, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101616089","display_name":"Shuhao Shi","orcid":"https://orcid.org/0000-0003-2926-8230"},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhao Shi","raw_affiliation_strings":["Information Engineering University, Zhengzhou, 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering University, Zhengzhou, 450000, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121918164","display_name":"Chen Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Chen","raw_affiliation_strings":["Information Engineering University, Zhengzhou, 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering University, Zhengzhou, 450000, China","institution_ids":["https://openalex.org/I169689159"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121972683","display_name":"Bin Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I169689159","display_name":"PLA Information Engineering University","ror":"https://ror.org/00mm1qk40","country_code":"CN","type":"education","lineage":["https://openalex.org/I169689159"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bin Yan","raw_affiliation_strings":["Information Engineering University, Zhengzhou, 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Engineering University, Zhengzhou, 450000, China","institution_ids":["https://openalex.org/I169689159"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5121972683"],"corresponding_institution_ids":["https://openalex.org/I169689159"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0202685,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9240999817848206,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9240999817848206,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11527","display_name":"3D IC and TSV technologies","score":0.011500000022351742,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12122","display_name":"Physical Unclonable Functions (PUFs) and Hardware Security","score":0.009999999776482582,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/schematic","display_name":"Schematic","score":0.9150999784469604},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7702000141143799},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5440999865531921},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.48080000281333923},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.446399986743927},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.3865000009536743},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.37709999084472656}],"concepts":[{"id":"https://openalex.org/C192328126","wikidata":"https://www.wikidata.org/wiki/Q4514647","display_name":"Schematic","level":2,"score":0.9150999784469604},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7944999933242798},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7702000141143799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5465999841690063},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5440999865531921},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48080000281333923},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.446399986743927},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41440001130104065},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3865000009536743},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.37709999084472656},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.37389999628067017},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3181000053882599},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30790001153945923},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2946999967098236},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.2648000121116638}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-025-00726-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00726-7","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c9415f1d7f154e3f9d8c62e8c572fff8","is_oa":true,"landing_page_url":"https://doaj.org/article/c9415f1d7f154e3f9d8c62e8c572fff8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 6, Iss 1, Pp 1-18 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00726-7","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00726-7","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1927632649","https://openalex.org/W1968844180","https://openalex.org/W2013978926","https://openalex.org/W2052500981","https://openalex.org/W2079329679","https://openalex.org/W2089896087","https://openalex.org/W2098364892","https://openalex.org/W2114489553","https://openalex.org/W2116341502","https://openalex.org/W2164666318","https://openalex.org/W2168228892","https://openalex.org/W2346113357","https://openalex.org/W2475655475","https://openalex.org/W2567085614","https://openalex.org/W2754667819","https://openalex.org/W2945221971","https://openalex.org/W3037164854","https://openalex.org/W3083648874","https://openalex.org/W3092618035","https://openalex.org/W3110928049","https://openalex.org/W3151487785","https://openalex.org/W4248699322","https://openalex.org/W4293093669","https://openalex.org/W4297822278","https://openalex.org/W4389474325"],"related_works":[],"abstract_inverted_index":{"Deep":[0],"reinforcement":[1,51,108],"learning-based":[2],"methods":[3,28],"for":[4,58],"PCB":[5,163],"schematic":[6],"reverse":[7],"generation":[8],"have":[9],"demonstrated":[10],"substantial":[11],"potential,":[12],"successfully":[13],"producing":[14],"schematics":[15,128],"that":[16,118],"rival":[17],"the":[18,49,59,79,96,100,104,112,119,123,144,149,159],"designs":[19],"of":[20,99,107,126,148,162],"human":[21],"experts":[22],"in":[23,34,48],"prior":[24],"research.":[25],"However,":[26],"current":[27],"face":[29],"challenges":[30],"due":[31],"to":[32,102],"limitations":[33],"exploration":[35,106],"space":[36],"stemming":[37],"from":[38],"a":[39,83,153],"fixed":[40,84],"layout":[41,85],"order,":[42],"as":[43,45],"well":[44],"inefficiencies":[46],"inherent":[47],"deep":[50],"learning":[52,109,113],"process.":[53],"To":[54],"address":[55],"these":[56],"challenges,":[57],"first":[60],"time,":[61],"this":[62],"paper":[63],"proposes":[64],"an":[65,88],"component":[66],"placement":[67],"order":[68],"prediction":[69],"method":[70,121],"based":[71],"on":[72],"graph":[73],"neural":[74],"networks,":[75],"aimed":[76],"at":[77],"overcoming":[78],"constraints":[80],"imposed":[81],"by":[82,129,138],"order.":[86],"Furthermore,":[87],"invalid":[89,105],"action":[90],"masking":[91],"mechanism":[92],"is":[93],"incorporated":[94],"into":[95],"output":[97],"stage":[98],"model":[101],"reduce":[103],"and":[110,146,156],"improve":[111],"efficiency.":[114],"Experimental":[115],"results":[116],"indicate":[117],"proposed":[120,150],"improves":[122],"average":[124],"performance":[125],"generated":[127],"approximately":[130],"11%,":[131],"while":[132],"also":[133],"accelerating":[134],"training":[135],"convergence":[136],"speed":[137],"around":[139],"27%.":[140],"These":[141],"findings":[142],"validate":[143],"effectiveness":[145],"practicality":[147],"approach,":[151],"offering":[152],"novel":[154],"perspective":[155],"solution":[157],"towards":[158],"automated":[160],"design":[161],"schematics.":[164]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2026-01-05T00:00:00"}