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Microsimulation
Microsimulation (from microanalytic simulation) is a category of computerized analytical tools that perform highly detailed analysis of activities such as highway traffic flowing through an intersection, financial transactions, or pathogens spreading disease through a population. Microsimulation is often used to evaluate the effects of proposed interventions before they are implemented in the real world. For example, a traffic microsimulation model could be used to evaluate the effectiveness of lengthening a turn lane at an intersection, and thus help decide whether it is worth spending money on actually lengthening the lane.
==Introduction==
Microsimulation can be distinguished from other types of computer modeling in looking at the interaction of individual "units" such as people or vehicles. Each unit is treated as an autonomous entity and the interaction of the units is allowed vary depending on stochastic (randomized) parameters. These parameters are intended to represent individual preferences and tendencies. For example, in a traffic model some drivers are cautious and wait for a large gap before turning, while others are aggressive and accept small gaps. Similarly, in a public health model individuals could vary in their resistance to a virus, as well as in personal habits that contribute to the spread of the virus (e.g. how frequently/thoroughly they wash their hands).
The International Microsimulation Association,〔(The International Microsimulation Association - Aims )〕 defines microsimulation as a modelling technique that operates at the level of individual units such as persons, households, vehicles or firms. Within the model each unit is represented by a record containing a unique identifier and a set of associated attributes – e.g. a list of persons with known age, sex, marital and employment status; or a list of vehicles with known origins, destinations and operational characteristics. A set of rules (transition probabilities) are then applied to these units leading to simulated changes in state and behaviour. These rules may be deterministic (probability = 1), such as changes in tax liability resulting from changes in tax regulations, or stochastic (probability <=1), such as chance of dying, marrying, giving birth or moving within a given time period. In either case the result is an estimate of the outcomes of applying these rules, possibly over many time steps, including both total overall aggregate change and (importantly) the way this change is distributed in the population or location that is being modeled.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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