인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
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.
피인용 0
초록·키워드
The growing global interest to decarbonize the transportation industry has resulted in numerous scientific publications. This study reviews the rapidly expanding body of research and identifies the knowledge gaps in transport decarbonization between regions. This study employs a hybrid approach combining topic modeling and machine learning to identify research topics and their knowledge structures, and then compares the main debated topics between Asia and non-Asian regions. A dataset of 777 articles, including 410 Asian and 367 non-Asian articles, published between 1990 and 2022 was extracted from the Scopus database. The latent Dirichlet allocation topic modeling results showed that five potential topics were derived from Asia, while six were derived from non-Asian regions, and the knowledge structure of each topic differed between the two regions. The K-nearest neighbor machine learning algorithm results indicated a 92% accuracy for Asian topics and an 89% accuracy for non-Asian topics. The findings suggest that the Asian studies focused on “energy use in transportation” and “drivers of CO2 emissions in transportation,” while the non-Asian studies focused on “electric vehicles” and “fuel consumption.” This paper will keep academics and practitioners updated on the paradigm shift in the research on transportation decarbonization.
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.
최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2023-339-000312081
