Application of Data Mining Techniques in the Analysis of by Nuno M.M. Ramos, João M.P.Q. Delgado, Ricardo M.S.F.

By Nuno M.M. Ramos, João M.P.Q. Delgado, Ricardo M.S.F. Almeida, Maria L. Simões, Sofia Manuel

The major advantage of the e-book is that it explores to be had methodologies for either engaging in in-situ measurements and correctly exploring the consequences, in keeping with a case learn that illustrates the advantages and problems of concurrent methodologies.

The case examine corresponds to a suite of 25 social housing dwellings the place an in depth in situ size crusade was once performed. The dwellings can be found within the related sector of a urban. Measurements integrated indoor temperature and relative humidity, with non-stop log in several rooms of every living, blower-door checks and whole outside stipulations supplied by means of a close-by climate station.

The e-book incorporates a number of clinical and engineering disciplines, akin to development physics, chance and records and civil engineering. It offers a synthesis of the present kingdom of data for advantage of specialist engineers and scientists.

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Extra resources for Application of Data Mining Techniques in the Analysis of Indoor Hygrothermal Conditions

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To determine which number of clusters is “best”, each of these cluster solutions is compared using Schwarz’s Bayesian Criterion (BIC) or the Akaike Information Criterion (AIC) as the clustering criterion. • Approaches to cluster analysis There are a number of different methods that can be used to carry out a cluster analysis; these methods can be classified as follows: Hierarchical methods • Agglomerative methods, in which subjects start in their own separate cluster. The two ‘closest’ (most similar) clusters are then combined and this is done repeatedly until all subjects are in one cluster.

Chapter 4 Case Study Abstract This chapter describes the case study, including sample description and presentation of the in situ measurements. The measurement results for both outdoor and indoor conditions are presented, highlighting the difficulty of deep analysis without using data mining techniques. 1 Sample Description For the purpose of the study a neighbourhood located in Portugal was chosen. All the buildings have similar features, usually 4 storey high and constituted by two flats per floor connected to a common staircase that was originally enclosed.

Selecting the optimum number of clusters As stated above, once the cluster analysis has been carried out it is then necessary to select the ‘best’ cluster solution. There are a number of ways in which this can be done, some rather informal and subjective, and some more formal. The more formal methods will not be discussed in this handout. Below, one of the informal methods is briefly described. When carrying out a hierarchical cluster analysis, the process can be represented on a diagram known as a dendrogram.

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