{"id":"https://openalex.org/W7147545735","doi":"https://doi.org/10.1109/cnml68938.2026.11453302","title":"Simulation and Optimization of Adaptive Control for Multi-Axis CNC Tool Paths Based on Deep Learning","display_name":"Simulation and Optimization of Adaptive Control for Multi-Axis CNC Tool Paths Based on Deep Learning","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147545735","doi":"https://doi.org/10.1109/cnml68938.2026.11453302"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11453302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453302","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132667905","display_name":"Rongli Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104453","display_name":"Shaanxi Science and Technology Department","ror":"https://ror.org/01c2sx728","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210104453","https://openalex.org/I4210120069","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210124148","display_name":"Microbiology Institute of Shaanxi","ror":"https://ror.org/02wt4jg41","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210124148"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rongli Li","raw_affiliation_strings":["Shaanxi Institute of Technology,Xi'an,China,710300"],"affiliations":[{"raw_affiliation_string":"Shaanxi Institute of Technology,Xi'an,China,710300","institution_ids":["https://openalex.org/I4210104453","https://openalex.org/I4210124148"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5132667905"],"corresponding_institution_ids":["https://openalex.org/I4210104453","https://openalex.org/I4210124148"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94824772,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1230","last_page":"1233"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.13269999623298645,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.13269999623298645,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T13567","display_name":"AI and Multimedia in Education","score":0.09369999915361404,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13027","display_name":"Applied Advanced Technologies","score":0.07800000160932541,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6474000215530396},{"id":"https://openalex.org/keywords/overshoot","display_name":"Overshoot (microwave communication)","score":0.5202999711036682},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5163999795913696},{"id":"https://openalex.org/keywords/adaptive-control","display_name":"Adaptive control","score":0.4941999912261963},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.47870001196861267},{"id":"https://openalex.org/keywords/control-system","display_name":"Control system","score":0.44839999079704285},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.38609999418258667},{"id":"https://openalex.org/keywords/numerical-control","display_name":"Numerical control","score":0.38530001044273376},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.37049999833106995},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.36800000071525574}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6474000215530396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5974000096321106},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.5353000164031982},{"id":"https://openalex.org/C2780323453","wikidata":"https://www.wikidata.org/wiki/Q7113957","display_name":"Overshoot (microwave communication)","level":2,"score":0.5202999711036682},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5163999795913696},{"id":"https://openalex.org/C107464732","wikidata":"https://www.wikidata.org/wiki/Q235781","display_name":"Adaptive control","level":3,"score":0.4941999912261963},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.47870001196861267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45579999685287476},{"id":"https://openalex.org/C17500928","wikidata":"https://www.wikidata.org/wiki/Q959968","display_name":"Control system","level":2,"score":0.44839999079704285},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38609999418258667},{"id":"https://openalex.org/C175457265","wikidata":"https://www.wikidata.org/wiki/Q190247","display_name":"Numerical control","level":3,"score":0.38530001044273376},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.37049999833106995},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.36800000071525574},{"id":"https://openalex.org/C118974865","wikidata":"https://www.wikidata.org/wiki/Q7300773","display_name":"Real-time Control System","level":3,"score":0.3393000066280365},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C103088060","wikidata":"https://www.wikidata.org/wiki/Q1062839","display_name":"Error detection and correction","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C2776299755","wikidata":"https://www.wikidata.org/wiki/Q432449","display_name":"Carry (investment)","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.313400000333786},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.29280000925064087},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C183356978","wikidata":"https://www.wikidata.org/wiki/Q1779213","display_name":"Tracking error","level":3,"score":0.2824000120162964},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.27570000290870667},{"id":"https://openalex.org/C31531917","wikidata":"https://www.wikidata.org/wiki/Q915157","display_name":"Robust control","level":3,"score":0.27149999141693115},{"id":"https://openalex.org/C117619785","wikidata":"https://www.wikidata.org/wiki/Q6094414","display_name":"Iterative learning control","level":3,"score":0.26570001244544983},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C5941749","wikidata":"https://www.wikidata.org/wiki/Q19768","display_name":"Machine tool","level":2,"score":0.25949999690055847}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11453302","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11453302","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.4077358841896057,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W4318480208","https://openalex.org/W4392584873","https://openalex.org/W4402200430","https://openalex.org/W4408365212","https://openalex.org/W4410400913","https://openalex.org/W4412909551","https://openalex.org/W4413154991","https://openalex.org/W4414194663","https://openalex.org/W4415491086"],"related_works":[],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2],"meet":[3],"the":[4,34,37,44,49,53,61,68,72,82,97,107,116,123],"demanding":[5],"requirements":[6],"of":[7,36,48],"real":[8,125],"time":[9,91,111,126],"and":[10,40,58,79,85,96,135],"accuracy":[11],"for":[12],"complex":[13],"trajectory":[14,74],"control":[15,25,38,127,139],"in":[16,81],"multi-axes":[17],"CNC":[18],"processing":[19,64],"(CNC),":[20],"an":[21],"adaptive":[22],"tool":[23],"path":[24],"system":[26,39,89],"based":[27],"on":[28,60],"deep":[29],"learning":[30],"was":[31],"developed.":[32],"Model":[33],"structure":[35,47],"coordinate":[41],"transformation,":[42],"design":[43],"error":[45,75],"forecast":[46],"neural":[50],"network,":[51],"construct":[52],"high":[54],"fidelity":[55],"simulation":[56],"platform,":[57],"carry":[59],"typical":[62],"surface":[63],"tasks,":[65],"show":[66],"that":[67,106],"model":[69,109],"can":[70],"reduce":[71],"average":[73,108],"by":[76,94,101],"53.5%,":[77],"49.0%":[78],"48.6%":[80],"X,":[83],"Y":[84],"Z":[86],"axes.":[87],"The":[88],"response":[90],"is":[92,99,112,131],"reduced":[93,100],"27.5%,":[95],"overshoot":[98],"58.7%.":[102],"Resource":[103],"assessment":[104],"shows":[105],"inference":[110],"3.82":[113],"ms,":[114],"while":[115],"GPU":[117],"utilization":[118],"remains":[119],"below":[120],"60%,":[121],"meeting":[122],"industrial":[124],"requirements.":[128],"This":[129],"method":[130],"more":[132],"accurate,":[133],"responsive,":[134],"robust":[136],"than":[137],"traditional":[138],"strategies.":[140]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}