The roles of neural networks in
predictive analytics are Function approximation,
Forecasting, Classification and Clustering.
Predictive analytics can be
helped with neural networks when there is a very large quantity of information
available for examination. Neural networks examine literally thousands of bits
of information to find relationships and patterns. The likelihood of future
events in neural networks are assisted by the fact that they can learn to
adjust to new circumstances, lend themselves to parallel processing, function
without having all the information or having that information in a structured
format, copy with huge amounts to data with different variables, and analyze
relationships found in the data
Blue Cross Blue Shield of Tennessee has a neural network which they use to predict health resources that will be needed after certain procedures. The patterns they find can help determine if a patient will have a reaction to the procedure. Having this data quickly can help save health care costs and patients.
Blue Cross Blue Shield of Tennessee has a neural network which they use to predict health resources that will be needed after certain procedures. The patterns they find can help determine if a patient will have a reaction to the procedure. Having this data quickly can help save health care costs and patients.
Question
2: What if the Richmond police began to add demographic data to its predictive
analytics system to further attempt to determine the type of person (by
demographic) who would commit a crime by demographic data (ethnicity, gender,
income level, and so on) good or bad?
There are good and bad to add demographic data to the predictive
analytics system. The good thing is that police not only can predict crime the
particular crime will occur, they even can focus on certain suspect and prevent
the crime happen. If the police have use demographic data in the predictive
analytics system, the possibility of 911 happen would be lower a lot.
However, it is hard to predict the true attitude of a human
being. Although some might be lower probability, anyone can commit a crime no
matter who is she/he, rich or not rich or even good or bad character. It is not
human to say someone will commit a crime just because of his/her ethnicity,
gender, income level, and so on. Is all muslim terrorist? Or because your skin
is black then you certainly violence? or because you commit a theft once means
you forever will steal? The answer is definitely not. We are using technology
to have better life, not use technology to make transform us to become robot.
Question
3: In the movie Gattaca, predictive analytics were used to determine the most
successful career for a person. Based on DNA information, the system determined
whether or not an individual was able to advance through an education track to
become something like an engineer or if a person should complete only a lower
level of education and become a junitor. The government then acted on the
system’s recommendations and placed people in various career tracks. Is this
good or bad use of technology? How is this different from the variety of
personal test you can take that informs you of your aptitude for different
career?
Using technology system to
determine a person future based on DNA is certainly a crazy thinking. Yes, by
using technology, People may predict a person strength or weakness from the DNA however, if the system show that your DNA is very
suitable to become a lawyer, does it means that even you do not put afford, you
will still become a lawyer? Did everyone still remember the story of turtle and
rabbit? From DNA or even physically, Rabbit is faster than turtle but if rabbit
did not put afford, it will still lose to a turtle.
Using technology system to
determine a person future is totally different with personal test. A personal
test is a test where let you know what is your current attitude and by having
such attitude, which career suitable you. It did not mention you only can
become what stated in the personal test. The lesson behind the personal test is
you must change in order to suitable to the career u aim for.
Question 4: What role can
geographic information system (GISs) play in the use of predictive analytics?
As you answer this question, specifically reference FedEx’s use of predictive
analytics to:
(1)
Determine which customers will respond
negatively to a price increase and(2) Project additional revenues from proposed drop-box locations.
GIS design to
analyze information in map form. By knowing a particular area preference, FedEx
could predict that the mindset of the customer toward the new policy or price.
Whether the people in that area could accept or could not. If a place is
developed and buying power is higher, normally the acceptance of increasing
prices is better as long as you provide better services as their aim is to have
best services rather than cost saving services. Besides, Fedex can choose area
that suitable to put dropbox by viewing the surrounding. If the surrounding is
more towards fast vihickle, it means that it is not suitable for vehicle or
people to stop and drop mail into the drop box.
Question 5: The
department of Defense (DoD) and the Pacific Northwest National Laboratory are
combining predictive analytics with visualization technologies to predict the
probability that a terrorist attack will occur. For example, suspected
terrorists caught on security cameras who loiter too long in a given place
might signal their intent to carry out terrorist attack. How can this type of
predictive analytics be used in airport? At what other buildings and structures
might this be used?
Predictive
analytics could be a powerful tool in fighting terrorism. For example, if
airport security saw a suspicious person frequenting an airline terminal, they
could detain him, check his background and if the findings warrant, do more
in-depth research on things like his travel activity. The results, when
compared to other terrorists’ profiles, might reveal his link to a terrorist
group.
Predictive profiling offers a unique approach to threat mitigation that begins from the point of view of the aggressor/adversary and is based on actual adversary's methods of operation, their modus operandi. This method is applicable to securing virtually any environment and to meeting any set of security requirements. When predictively profiling a situation, person or object one identifies suspicion indicators that correlate with an adversary's method of operation. For example, if a security officer observes a person walking with an empty suitcase in an airport (the suitcase appears very light; it bounces off the floor) he may identify this suspicious behavior as an indication of a possible terrorist or criminal method of operation because:
- The
person may be involved in theft or shop lifting (using the empty suitcase
to stash what he would steal)
- The
person may be involved in surveillance activities (the suitcase is only a
prop to fit the airport environment)
- The
person has dropped a bomb somewhere in the airport and is now exiting
Other than airport to use the predictive analytics with
visualization technologies, other buildings such as museums, public library,
shopping centre and historical places (such as monuments) can apply the same
method to detect the possible terrorists. The public places with crowd can
easily become the target of terrorists as they are not easily detected and can
escape within the public, not easily being spotted.
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