Real-Time Prediction of Taxi Demand Using Recurrent Neural Networks
Product Description
Aim:
To predict the high demand need of pickup location
for taxi services based on their previous history.
Synopsis:
The
service industry is booming for the last couple of years and it is expected to
grow in the near future. One of the important natures of the business is the
serve the customer. To effectively utilize the resource at hand is the key
factor. Businesses are using advanced technology to achieve this.
Effective taxi
dispatching can help both drivers and passengers to minimize the wait-time to
find each other. Drivers do not have enough information about where passengers
and other taxis are and intend to go. Therefore, a taxi center can organize the
taxi fleet and efficiently distribute them according to the demand from the
entire city. To build such a taxi center, an intelligent system that can
predict the future demand throughout the city is required. Our system uses GPS
location and other properties of the taxi like drop point, pickup point etc. to
predict the future demand. An Recurrent Neural Networks (RNN) based model is
trained with given history data. This model is used to predict the demand in
different areas of the city.
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The
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Mini Projects - Hardware includes
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The Delivery time for Hardware Mini projects is 7-8 working days.