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SQIT 3033 (A)

KNOWLEDGE ACQUISITION IN DECISIONMAKING

INDIVIDUAL ASSIGNMENT

LECTURER:

Dr. Izwan Nizal Mohd Shaharanee

TITLE:

How data mining application can be utilized in

construction project?

DUE DATE:

6 MARCH 2014

PREPARED BY:

CHONG SIOW HUI 211650

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Data mining is the process of finding useful information and hidden patterns from a

huge amount of data by the mean of automatic or semiautomatic. In real life, it is impossible

for us to retrieve the information and identify the patterns manually. This is because the data

is very huge.

So, data mining is taking important role in the application of many sectors such as

industry sectors, manufacturing sectors, construction sectors and etc. It helps us to extract

important information from the raw data, in order for us to make a proper decision making.

In many construction projects, we can see that many projects have been done half way

due to insufficient budgets, weather conditions, and sudden termination of project. All these

are due to the high risk and uncertainty in the construction projects. This is because

construction projects are long-term projects, require a huge amount of budgets and also

involve many hidden risks and patterns.

All these uncertainty can be overcome by the application of data mining technique in

the construction project. Data mining technique can be applied into risk management, cost

analysis, weather forecasting and so on in construction project.

In J. Li, et al. (n.d.), the researchers make a research regarding the construction cost

and also factors of the construction cost in construction project such as highway, railway,

housing, municipal and metro constructions by using data mining approach. They have

analysed the cost composition of construction by using descriptive task and forecasting the

factors of the construction cost by using predictivetask. For the cost composition, they have

listed down the general characteristics of the item cost whereas predicting the impact factors

of the construction cost. By using data mining approach, they found out that the material,

labour and also equipment costs are the main components that made up the cost composition

in the construction projects. In addition, by using multiple regression, among all the

investigated factors, the total quantity of the construction project is the most important factor

effect on the construction cost.

In X. Deng, et al. (n.d.), the researchers are interested in finding the relationships of

risk factors in the construction project. By using data mining approach in risk management,

the researchers begin with object identification, data preparation, data selection, data

processing and lastly the application of data mining model. They are using descriptive

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approach in this research. The relationships of risk factors are investigated by using

association rule.

In H. Kim, et al. (2010), the researchers are interested in discovering the patterns of

energy-related behaviours to improve the energy building design in the construction project.

By using building insulation such as different materials roof and wall construction, the energy

used for cooling, heating and lightning can be minimised. They are using induction

algorithmand decision treein the research. By using predictiveapproach, they estimate the

annual energy cost of the roof construction, HVAC systems and also building orientation.

Besides, in descriptive approach, they have figured out the considered factors in the

construction such as materials used, air space, insulation and so on. Through the research, by

using true south building orientation, frame wall with Super High Insulation combined with

brick veneer, wood frame roof or metal frame roof with high insulation and also 17

SEER/0.85 AFUE split/Pkgrl of HVAC will give the greatest impact in the saving of the

energy costs in the construction projects.

The use of data mining approach has been applied into the construction projects by

using descriptive and predictive ways. In J. Zhang, et al. (2002), the researchers have used

predictive approach such as classification of decision tree and also descriptive approach

such as clustering and association rulein processing the data to be applied into construction

projects. For example, we can find out the distribution of eigenvalues with the help decision-

tree model of material use. With this, we can easily estimate what kinds of materials will be

used in the construction and plan for the amount of materials used. Moreover, the researchers

also mentions that by using data mining approach, the data mining models can predict the

resources required in the project such as labour and machines. Thus, we can make analysis

and prediction for material expenditure for our project. In addition, the schedule for the

construction events can also be done by using association rule. Lastly, the safety and quality

of the construction can be done by using clustering.

Thus, from all the research that have been made from the researchers, we can say that

data mining approach can be easily to be used to solve the problems exist in the construction

sectors. All the methods in the data mining approach can be classified into descriptive and

predictive ways. For instances, the regression can be used to find the relationships of the cost

analysis; the risk management analysis can be done by using associative rule, safety and

quality of the construction by using clustering analysis and so on.

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Reference

H. Kim, et al,. (2010).Automation in construction: Analysis of an energy efficient building

design through data mining approach.Doi:10.1016/j.autcon.2010.07.006

J. Li, H. Mao, G. Luo, and S. Peng. (n.d.).Research on cost compositions and influence

factors of construction project: Based on data mining of project cost. Adapted 28

February 2014 from Southwestern University of Finance and Economics.

J. Zhang, T. Ma, and Q. Shen. (2002).Application of data warehouse and data mining in

construction management. Adapted 1 March 2014 from http://e-pub.uni-

weimar.de/opus4/files/124/icccbe-x_182.pdf.

X. Deng, Q. Li, D. Li, and E. Zhang. (n.d.).Application of data mining in risk management of

construction projects. Adapted 28 February 2014 from http://www.paper.edu.cn