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

• Main Author: Abdullah, Azizul
• Format: Final Year Project
• Language: English
• Published: Universiti Teknologi Petronas 2008
• Subjects: ZA Information resources
• Online Access: http://utpedia.utp.edu.my/10242/1/2008%20-%20Real%20Estate%20Value%20Forecasting%20System%20Using%20Data%20Mining%20and%20Neural%20Network%20Approach%28Revfos%29.pdf; http://utpedia.utp.edu.my/10242/

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.