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Classification of Tourist Activity Patterns Using Electric Vehicle Driving Data

첫 페이지 보기
  • 발행기관
    한국차세대컴퓨팅학회 바로가기
  • 간행물
    한국차세대컴퓨팅학회 학술대회 바로가기
  • 통권
    The 7th International Conference on Next Generation Computing 2021 (2021.11)바로가기
  • 페이지
    pp.268-271
  • 저자
    Jun-Ho Yoon, Chang Choi, Jin-A Choi, Kiho Lim
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A448064

원문정보

초록

영어
Travel trends are changing due to the prolonged COVID-19 pandemic and vaccine development. The analysis of pre and post Covid-19 tourism trends, according to a survey by Jeju Tourism Organization, shows that the search volume for overseas travel has decreased compared to 2018 and 2019, but search volume for Jeju travel and the number of tourists visiting Jeju Island Increased. In the case of tourists in Jeju, many use vehicles, mostly rental cars, for transportation due to the geographical characteristics of the island, and the number of electric vehicles is increasing in Jeju Island’s rental car services due to the strengthening of electric car policies. However, most of the existing research on tourists have been conducted using public data. Therefore, based on the means of transportation mainly used by tourists, electric vehicle driving data recorded for three years provided by Korea Electric Power Corporation Knowledge Data Network (KEPCO KDN) was classified into a total of 11 areas by weather and time requirements and classified through an artificial intelligence-based multiclassification model. In this study, tourist activity patterns were classified according to season, time zone, and climate conditions, but in the future, it can be used for recommendations and advertisements for tourist destinations by subdividing zones and adding information on users.

목차

Abstract
I. INTRODUCTION
II. RELATED WORKS
A. Post-COVID-19 tourism trends
B. Distribution of tourist destinations in Jeju Island
C. Tourist activity patterns in Jeju area
III. JEJU ELECTRIC CAR DRIVING DATA
A. Data preprocessing
B. Data structure
IV. AI-BASED MULTI-CLASSIFICATION MODEL
A. K-Neares Neighbor(K-NN)
B. Support Vector Machine(SVM)
C. Ensemble Learning - Voting
D. Random Forest
E. LightGBM
F. XGBoost
V. RESULT
VI. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

키워드

Electric Vehicle Classification Travel Covid19 Jeju Island

저자

  • Jun-Ho Yoon [ dept. of Computer Engineering Gachon University ]
  • Chang Choi [ dept. of Computer Engineering Gachon University ]
  • Jin-A Choi [ dept. of Communication William Paterson University New Jersey, USA ]
  • Kiho Lim [ dept. of Computer Science William Paterson University New Jersey, USA ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국차세대컴퓨팅학회 [Korean Institute of Next Generation Computing]
  • 설립연도
    2005
  • 분야
    공학>컴퓨터학
  • 소개
    본 학회는 차세대 PC 및 그 관련분야의 학술활동을 통하여 차세대 PC의 학문 및 기술발전을 도모하고 산업발전 및 국제협력 증진을 목적으로 한다.

간행물

  • 간행물명
    한국차세대컴퓨팅학회 학술대회
  • 간기
    반년간
  • 수록기간
    2021~2025
  • 십진분류
    KDC 566 DDC 004

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