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After data exploration/cleaning, think about modelling. For example, consider the following two (of many?) options. Option 1: Build a regression model to predict mean miles per hour given a certain system traffic load. Option 2: Generate system traffic load by representing each (idealized) vehicle on the road. #5

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StevenMMortimer opened this issue Sep 7, 2016 · 1 comment
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After data exploration/cleaning, think about modelling. For example, consider the following two (of many?) options. Option 1: Build a regression model to predict mean miles per hour given a certain system traffic load. Option 2: Generate system traffic load by representing each (idealized) vehicle on the road. #5

StevenMMortimer opened this issue Sep 7, 2016 · 1 comment
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StevenMMortimer commented Sep 7, 2016 •
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@StevenMMortimer StevenMMortimer changed the title After data exploration/cleaning, think about modelling. For example, try to build a regression model that predicts average miles per hour given certain characteristics of the network. Or, try to generate the characteristics of the network by representing each driver, then calculating the average miles per hour achieved under that kind of traffic load (given a fixed network configuration). After data exploration/cleaning, think about modelling. For example, consider the following two (of many?) options. Option 1: Build a regression model to predict mean miles per hour given a certain system traffic load. Option 2: Generate system traffic load by representing each (idealized) vehicle on the road. Sep 7, 2016
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https://en.wikipedia.org/wiki/Agent-based_model provides a nice overview (from 30,000 ft) of agent-based (individual-based) simulation models.

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