ScholarWorks@Korea University: Kang, Seung mo

Detailed Information

Kang, Seung mo (강승모)

공과대학 (건축사회환경공학부)

Research Area

Tel 02-3290-4862
Homepage

ResearcherID ORCiD Scopus Google Scholar ID ResearchGate

Keyword

network design:2||metaheuristics:2||KTDB:2||multiobjective optimization:2||Inherent variation:1||Empirical bayes method:1||toll plaza capacity:1||Geographic information system:1||Geographically weighted regression:1||Mixed Integer Programming:1||Passenger Railway:1||노선계획:1||postmile markers:1||Social benefit:1||Unplanned freeway closure:1||intermodal coordination:1||routing and scheduling:1||Bike lane:1||memetic algorithm:1||Network forensic evidence:1||Traffic safety:1||Stopschedule:1||여객철도:1||철도운영:1||정차스케줄:1||Traveling purchaser problem:1||Supply chain planning:1||Dynamic Site Length:1||Urban Railway Accident:1||Highspeed rail:1||Station choice probability:1||smart card:1||transit ridership:1||missing value imputation:1||metaheuristic algorithms:1||Bicycle:1||tabu search algorithm:1||IP traceback:1||Hazardous locations:1||traffic safety:1||Highway Safety:1||Optimization:1||Safety Improvement Project:1||통행시간 신뢰성 향상 편익:1||Trafficstate prediction:1||artificial intelligence:1||Compensation:1||Unit cost of rail accident:1||Random noise:1||Width:1||genetic algorithm:1||Kernel density estimation:1||Line Planning:1||Traffic congestion:1||Mixedinteger program:1||Empirical Bayesian Estimate:1||수요예측:1||역사 선택 확률:1||railway operation data:1||support vector machine:1||Cost of business suspension:1||Evaluation of the effectiveness of safety projects:1||Railway safety improvement project:1||Emergency response:1||public transportation:1||traffic conditions:1||facility location model:1||traffic congestion:1||Spatial interaction:1||linear referencing:1||Approximation:1||Hotspot Identification:1||Vehicle Device Failure:1||Benefit by Reduction of Delay Time:1||Benefit by Improvement of Travel Time Reliability:1||Travel assignment:1||고속철도:1||통행배정:1||Urban networks:1||machine learning:1||Benefits of reduction of railway accident:1||Improved reliability of transit time:1||integrated transit:1||Transit ridership:1||The regression to the mean:1||Continuous risk profile:1||Safety:1||logistics systems planning:1||metaheuristic algorithm:1||Packet marking:1||Accident:1||geocoding:1||Lagrangian relaxation:1||sustainable transit:1||Network Screening:1||principal component analysis:1||Reduction of delay time:1||Mode shift:1||Stability:1||proxy measure:1||analytical model:1||vehicle GHG emission:1||Network forensic:1||Crash involvement rate:1||혼합정수모형:1||expressway collisions:1||Heuristic:1||Integrated transit:1||Spatiotemporal dependency:1||dwell time estimation:1||metro timetable:1||multimodal feeder:1||Safety performance function:1||transit network design:1||feeder bus:1||GPS:1||Traffic state:1||Railway Operation:1||Stochastic price:1||Dynamic programming:1||Biofuel refinery location:1||Branchandbound:1||도시철도 사고:1||장치고장:1||지체시간 감소 편익:1||안전개선사업:1||Demand forecasting:1||

STATISTICS: Total View :8,631,023; Today View :11,433

RSS_1.0 RSS_2.0 ATOM_1.0

(02841) 서울특별시 성북구 안암로 14502-3290-1114

Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.

Detailed Information

Keyword

BROWSE