This paper reports the development of a methodology for identifying and improving occupant behavior in existing residential buildings. In this study, end-use loads were divided into two levels (i.e. main and sub-category), and they were used to deduce corresponding two-level user activities...

Highly imbalanced data sets are those where the class of interest is rare. In this paper, we compare the performance of several common data mining methods, logistic regression, discriminant analysis, Classification and Regression Tree (CART) models, C5, and Support Vector Machines (SVM) in...

Transportation demand modeling has evolved in scope, theory, and practice in the many decades since the US Bureau of Public Roads pioneered home interview transportation studies in metropolitan households in the early 1940s. The major currents of these developments are discussed in the present...

Workforce analytics (i.e., statistical analysis, modeling and mining of HR data) is particularly important in service industries. Service industries are people-intensive and the knowledge and expertise of the people within an organization is a strategic resource critical for success. Performance...

This paper demonstrates the hazard of “stir-fry” regressions, which are used extensively in financial research to produce desirable results by reporting only one or a small number of regressions out of the tens or hundreds that are typically estimated. It is shown, by using data on the...

Multivariate adaptive regression splines (MARS) has become a popular data mining (DM) tool due to its flexible model building strategy for high dimensional data. Compared to well-known others, it performs better in many areas such as finance, informatics, technology and science. Many studies...

In this paper, an algorithm for finding piecewise linear boundaries between pattern classes is developed. This algorithm consists of two main stages. In the first stage, a polyhedral conic set is used to identify data points which lie inside their classes, and in the second stage we exclude...

Based on debris-flow inventories and using a geographical information system, the susceptibility models presented here take into account fluvio-morphologic parameters, gathered for every first-order catchment. Data mining techniques on the morphometric parameters are used, to work out and test...

Landslides during earthquakes have led to severe casualties and have resulted in damaged structures and facilities. The goal of the present study is to analyze the landslide problems in a remote area—Shei-Pa National Park in Taiwan. Spatial information techniques (Remote Sensing and Geographic...

This work presents the development of a rainfall-runoff model for the Iguaçu River basin in southern Brazil. The model was developed to support the operation planning of hydroelectric power plants and is intended to predict the natural flow based on meteorological rain forecasts. A recurrent...