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Modified LVQ based clustering analysis for decision making in construction management

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dc.contributor.author Riaz, Muhammad Naveed
dc.contributor.author Husain, Syed Afaq
dc.contributor.author Ali, Asad
dc.contributor.author Shamshad, Tahir
dc.date.accessioned 2019-11-14T06:57:05Z
dc.date.available 2019-11-14T06:57:05Z
dc.date.issued 2015-12-17
dc.identifier.isbn 978-1-4799-7812-0
dc.identifier.uri http://142.54.178.187:9060/xmlui/handle/123456789/1273
dc.description.abstract Extracting the data and information from manual data repository is difficult, costly and time-consuming. They have prospects for making decision in construction process. Decision making can be performed by collecting data timely and cost effectively from the data warehouse by providing a model of the decision making process and programming pertinent knowledge into it. Data mining automates the process of finding predictive information from the large databases. To improve the decision making in construction management the artificial neural network (ANN) commonly known as neural network (NN) is one of the method which can be used in Data Mining. Clustering is one of the basic data analysis method used in data mining. In Construction Management, the problem is how to analyze the data to obtain quick analysis for the extraction of useful Clusters. In this research we have applied modified Learning Vector Quantization (LVQ) neural network to classify the construction projects into flexible Clusters for dynamic analysis. These examples are based upon past experiences of similar data, it can identify the problem and suggest suitable alternatives. The proposed modified LVQ technique is efficient with respect to the number of clusters and time. This system is fast and the accuracy of the system has been verified by domain experts through numerous case examples. en_US
dc.language.iso en_US en_US
dc.publisher IEEE International Conference on Open Source Systems & Technologies (ICOSST) en_US
dc.subject Engineering and Technology en_US
dc.subject Neural networks en_US
dc.subject Clustering algorithms en_US
dc.subject Algorithm design and analysis en_US
dc.subject Data mining en_US
dc.subject Decision making en_US
dc.subject Training en_US
dc.subject Databases en_US
dc.title Modified LVQ based clustering analysis for decision making in construction management en_US
dc.type Proceedings en_US


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