인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
This research focused on the needs of the defense industry to understand what companies should preemptively prepare from the perspective of their current management status in order to increase the probability of receiving benefits from being selected for defense industry development support projects. An experiment was conducted to build a prediction model for beneficiaries of the parts localization development support project and the weapon system modification development support project using corporate information. To compensate for the imbalance problem of data classes of variables, random sampling methods such as oversampling, undersampling, and hybrid sampling methods were applied. The backward elimination technique was applied as a variable selection technique, and the ensemble technique was additionally applied to improve the performance of the prediction model. What differentiates this study is that it analyzes corporate characteristics that determine beneficiary and non-beneficiary companies and builds a prediction model for beneficiary companies.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-25-02-092311431