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        <identifier>oai:ipsj.ixsq.nii.ac.jp:00017161</identifier>
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          <dc:title>遺伝的アルゴリズムと勾配法の組合せによる物理モデルの自動合わせ込み</dc:title>
          <dc:title xml:lang="en">Automatic Calibration of Physical Models Utilizing Genetic Algorithms and Gradient Methods</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>村川, 正宏</jpcoar:creatorName>
            <jpcoar:creatorName>小田, 嘉則</jpcoar:creatorName>
            <jpcoar:creatorName>樋口, 哲也</jpcoar:creatorName>
            <jpcoar:creatorName>西, 謙二</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Masahiro, Murakawa</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="en">Yoshinori, Oda</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="en">Tetsuya, Higuchi</jpcoar:creatorName>
            <jpcoar:creatorName xml:lang="en">Kenji, Nishi</jpcoar:creatorName>
          </jpcoar:creator>
          <jpcoar:subject subjectScheme="Other">事例紹介論文</jpcoar:subject>
          <datacite:description descriptionType="Other">本論文では，遺伝的アルゴリズムを用いた物理モデルの自動合わせ込み手法を提案する．半導体デバイスプロセスの設計時にはTCAD（テクノロジCAD）が現在駆使されている．TCADによるシミュレーション結果が正確であるためには，計算に用いられる物理モデルのパラメータを，あらかじめ計測した実験データと一致するように調整しておく必要がある．この工程は合わせ込みと呼ばれ，特に精度を要求されるシミュレーションでは，モデルパラメータの数が多くなり，合わせ込みに要する工数が増大する．また，TCADで用いられる物理モデルにおいては，調整されたパラメータに微分可能性確保の制約条件があるために，これまで合わせ込みの自動化ができなかった．そこで提案手法では，遺伝的アルゴリズムと勾配法を組み合わせ，制約条件を満たしつつ，すべてのモデルパラメータを一括して自動的に合わせ込む．提案手法をイオン打ち込みモデルにおける不純物分布関数のパラメータ群（144個）の合わせ込みに適用した結果，1台のPCを用いて17分，8台のPCを用いて2分強での自動合わせ込みに成功した．この合わせ込み工程は従来熟練者でも数日程度要したことから，大幅に作業効率，作業コストを改善できる．</datacite:description>
          <datacite:description descriptionType="Other">In this paper, we present an application of GA (Genetic Algorithm) to physical model calibration. Although Technology CAD (TCAD) is already well-established as an indispensable tool for minimizing the development time and costs involved in new LSI processes and devices, maximum TCAD utilization is heavily dependant on the calibration of relevant model parameters. With the increasing complexity of TCAD models, however, calibration becomes more and more labor and time intensive. Moreover, the constraint of smoothness on extracted model parameters makes the calibration process much more difficult. To overcome this difficulty, we propose a calibration technique based on GA and the gradient method, which extracts all model parameters simultaneously preserving the smoothness on the extracted parameters. Experimental results on a PC cluster system (eight PCs) demonstrate that the calibration of 144 parameters for an ion implantation model can be completed within a few minutes, although this would typically take a human expert a few days.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2006-10-15</datacite:date>
          <dc:language>jpn</dc:language>
          <dc:type rdf:resource="http://purl.org/coar/resource_type/c_6501">journal article</dc:type>
          <jpcoar:identifier identifierType="URI">https://ipsj.ixsq.nii.ac.jp/records/17161</jpcoar:identifier>
          <jpcoar:sourceIdentifier identifierType="ISSN">1882-7780</jpcoar:sourceIdentifier>
          <jpcoar:sourceIdentifier identifierType="NCID">AA11464803</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>情報処理学会論文誌数理モデル化と応用（TOM）</jpcoar:sourceTitle>
          <jpcoar:volume>47</jpcoar:volume>
          <jpcoar:issue>SIG14(TOM15)</jpcoar:issue>
          <jpcoar:pageStart>161</jpcoar:pageStart>
          <jpcoar:pageEnd>170</jpcoar:pageEnd>
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            <jpcoar:URI>https://ipsj.ixsq.nii.ac.jp/record/17161/files/IPSJ-TOM4714017.pdf</jpcoar:URI>
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            <datacite:date dateType="Available">2008-10-15</datacite:date>
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