The scientific and technological achievements trigger people’s desire to learn new things and sometimes it turns into a competition among individuals. The competitive environmental so makes an important psychological pressure on individuals and it may manipulate their choices about their educational careers. Artificial neural networks are widely utilized to reach to a short-cut solution and as a method of decision making. The role of the machine learning techniques and data mining algorithms to define the factors affecting students’ success is important. The aim of this research is to make predictions about these factors by using Adaptive-Network Based Fuzzy Inference Systems (ANFIS). Student Performance data set in UCI platform is used for classification part of this study.
목차
Abstract 1. Introduction 2. Literature Review 3. Materials and Methods 3.1. Data Set 3.2. Establishing and Testing ANFIS Forecasting Model 4. Research Findings 5. Conclusion and Discussion 6. References
키워드
ANFISstudent successacademic successpredictiondata set
저자
E. U. Kucuksille [ Suleyman Demirel University, Department of Computer Engineering, Turkey ]
M. Catak [ Burdur Mehmet Akif Ersoy University, Ağlasun Vocational School, Turkey ]
Corresponding Author
한국AI디지털융합학회(구 한국디지털융합학회) [The Korean Academic Society of AI Digital Convergence]
설립연도
2015
분야
사회과학>경영학
소개
본 학회는 디지털 경영에 관련된 디지털 미디어, 디지털 통신, 디지털 방송, 디지털 콘텐츠, 디지털 문화, 디지털 사회, 디지털 유통, 디지털 금융, 디지털 물류, 디지털 정책, 디지털 기술, 디지털 교육 그리고 디지털과 아날로그의 비교 등에 대한 학제간 연구와 실사구시적인 적용을 통하여 디지털 경영의 발전과 한국이 세계적인 디지털 강국으로 성장하기 위한 학술적인 기반과 실무적인 지침을 조성하는 것을 목적으로 하고 있습니다.
간행물
간행물명
IJICTDC [International Journal of Information Communication Technology and Digital Convergence]