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Forecasting daily emergency ambulance service demand using biometeorological indexes
Ho Ting Wong
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Corresponding author for this work
Department of Business Administration
Research output
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Article
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peer-review
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Citation (Scopus)
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INIS
forecasting
100%
demand
100%
emergencies
100%
comparative evaluations
33%
taiwan
16%
weather
16%
patients
16%
cities
16%
humidity
16%
Nursing and Health Professions
Temperature
100%
Ambulance
100%
Dependent Variable
14%
Forecasting
14%
Medical Record
14%
Time Series Analysis
14%
Computer Science
Service
100%
Models
66%
Effective Temperature
33%
Records
16%
Relative Humidity
16%
Dependent Variable
16%
Agricultural and Biological Sciences
Temperature
100%
Models
57%
Cities
14%
Weather
14%
Relative Humidity
14%
Earth and Planetary Sciences
Ambulance
100%
Social Sciences
Demand Forecast
14%