REAL ESTATE VALUE FORECASTING SYSTEM USING DATA MINING AND NEURAL NETWORK APPROACH (REVFOS)

Modern science and engineering are based on applying first-principle models in
order to describe physical, biological and social systems. It is an approach starts with a
basic scientific model such as Newton's Law of Motion or Maxwell's equations in
electromagnetism and it leads to building various applications in mechanical and
electrical engineering. However, in many domains that underlying first principle is
unknown and unable to elaborate or the systems developed are too complex to be
mathematically formalized. Thus, there is currently a paradigm shift from classical
modeling and analyses based on first principles to developing models and the
corresponding analyses directly from data.
The necessitate to understand large, complex, information-rich data sets in
widespread to virtually all fields of business, science and engineering as in the business
world, corporate and customer data are treated as a strategic assets. The ability to extract
useful knowledge hidden in these sets of data and to act on that knowledge is becoming
increasingly important in today's competitive world. The entire process of applying
computer-based methodologies including new techniques for discovering knowledge
from raw data is known as data mining.
Data mining is the process of identifying and analyzing data from diverse
perspectives and summarizing it into constructive and useful information which it can be
utilized as revenue increments, costs reductions and input productions. Technically, data
mining application orsoftware is been treated as one ofanalytical tools for analyzing data
and input gathered from various sources. Furthermore, it also allows users to scrutinize
data from different dimensions and angels in order to categorize it before summarize the
possible relationship identified. In addition, data mining is the process of identifying
correlations orpatterns among dozens of fields in large relational databases.