<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-VWTGMTXB</identifier><date>2025</date><creator>Luo, Zhenyu</creator><relation>documents/doc/V/URN_NBN_SI_doc-VWTGMTXB_001.pdf</relation><relation>documents/doc/V/URN_NBN_SI_doc-VWTGMTXB_001.txt</relation><format format_type="issue">13</format><format format_type="volume">49</format><format format_type="type">article</format><format format_type="extent">str. 91-103</format><identifier identifier_type="DOI">10.31449/inf.v49i13.7651</identifier><identifier identifier_type="ISSN">1854-3871</identifier><identifier identifier_type="COBISSID">241095171</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-VWTGMTXB</identifier><language>eng</language><publisher publisher_location="Ljubljana">Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">mehanizem temperaturnega popuščanja</subject><subject language_type_id="slv">optimizacija parametrov</subject><subject language_type_id="slv">raba energije</subject><subject language_type_id="slv">roj delcev</subject><subject language_type_id="slv">simulirano kaljenje</subject><subject language_type_id="slv">sinhroni motor s permanentnimi magneti</subject><subject language_type_id="slv">umetna inteligenca</subject><title>A hybrid self-optimizing simulated annealing and particle swarm optimization approach for PMSM parameter optimization</title></Record>