In Richmond, Va., police use predictive analysis to determine the
probability that a particular type of crime--armed robbery, auto theft,
murder--will occur in a specific area at a given time. Police lieutenants who
command the city's 12 sectors use desktop computers linked to the system to
decide where to deploy a mobile task force of 30 officers. "Based on the
predictive models, we deploy them almost every three or four hours," Police
Chief Rodney Monroe says.
Officers have arrested 16 fugitives and confiscated
18 guns based on the system's guidance. In the first week of May, Richmond had
no homicides, compared with three in the same week last year. Monroe attributes
that outcome, in part, to moving officers around based on the calculated
probability of shooting incidents. "It's more proactive," Monroe says. "We're
not waiting for a homicide to occur."
In the news, it shows the softwares apply several methods such as Markov decision process, stream mining, and support vector machines to predict the future. Also it is good news to inventory management.
IBM last week introduced an inventory management application for retailers
that uses built-in predictive analytics and replenishment rules to monitor
product inventory, develop safety stock, and recommend orders based on an
analysis of historical demand. The commercial app has been used by IBM
consultants for years.
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