Search results for "Data mining"
showing 10 items of 907 documents
Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling
2011
Abstract Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced. The International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, has been working on the development of a framework for defining and assessing uncertainties in the field of urban drainage modelling. A part of that work is the assessment and comparison of different techniques generally used in the uncertainty assessm…
Global sensitivity analysis in wastewater applications: A comprehensive comparison of different methods
2013
Three global sensitivity analysis (GSA) methods are applied and compared to assess the most relevant processes occurring in wastewater treatment systems. In particular, the Standardised Regression Coefficients, Morris Screening and Extended-FAST methods are applied to a complex integrated membrane bioreactor (MBR) model considering 21 model outputs and 79 model factors. The three methods are applied with numerical settings as suggested in literature. The main objective considered is to classify important factors (factors prioritisation) as well as non-influential factors (factors fixing). The performance is assessed by comparing the most reliable method (Extended-FAST), by means of proposed…
Parameter subset selection for the dynamic calibration of activated sludge models (ASMs): experience versus systems analysis.
2007
In this work we address the issue of parameter subset selection within the scope of activated sludge model calibration. To this end, we evaluate two approaches: (i) systems analysis and (ii) experience-based approach. The evaluation has been carried out using a dynamic model (ASM2d) calibrated to describe nitrogen and phosphorus removal in the Haaren WWTP (The Netherlands). The parameter significance ranking shows that the temperature correction coefficients are among the most influential parameters on the model output. This outcome confronts the previous identifiability studies and the experience based approaches which excluded them from their analysis. Systems analysis reveals that parame…
An imprecise Fault Tree Analysis for the estimation of the Rate of OCcurrence Of Failure (ROCOF)
2013
Abstract The paper proposes an imprecise Fault Tree Analysis in order to characterize systems affected by the lack of reliability data. Differently from other research works, the paper introduces a classification of basic events into two categories, namely Initiators and Enablers . Actually, in real industrial systems some events refer to component failures or process parameter deviations from normal operating conditions ( Initiators ), whereas others refer to the functioning of safety barriers to be activated on demand ( Enablers ). As a consequence, the output parameter of interest is not the classical probability of occurrence of the top event, but its Rate of OCcurrence (ROCOF) over a s…
Proposal of geographic information systems methodology for quality control procedures of data obtained in naturalistic driving studies
2015
The primary goal of naturalistic driving studies is to provide a comprehensive observation of the driver's behaviour under real-life conditions by measureing a great number of parameters at high temporal frequencies. Achieving this goal, however, is a complex endeavor that faces many challenges such as the complexity of the vehicle instrumentation during the phase of data collection, and the difficult handling of large data volumes during the phase of data analysis. These drawbacks often cause episodes of data losses. Improving the technical aspects of the collection of naturalistic data is of paramount importance to increase the return of the investment made in it. An aspect to consider is…
Preface to Data Mining in Biomedical Informatics and Healthcare
2013
Real-time 3D imaging of Haines jumps in porous media flow.
2013
Newly developed high-speed, synchrotron-based X-ray computed microtomography enabled us to directly image pore-scale displacement events in porous rock in real time. Common approaches to modeling macroscopic fluid behavior are phenomenological, have many shortcomings, and lack consistent links to elementary pore-scale displacement processes, such as Haines jumps and snap-off. Unlike the common singular pore jump paradigm based on observations of restricted artificial capillaries, we found that Haines jumps typically cascade through 10–20 geometrically defined pores per event, accounting for 64% of the energy dissipation. Real-time imaging provided a more detailed fundamental understanding o…
Memetic Differential Evolution Frameworks in Filter Design for Defect Detection in Paper Production
2009
This chapter studies and analyzes Memetic Differential Evolution (MDE) Frameworks for designing digital filters, which aim at detecting paper defects produced during an industrial process. MDE Frameworks employ the Differential Evolution (DE) as an evolutionary framework and a list of local searchers adaptively coordinated by a control scheme. Here, three different variants of MDE are taken into account and their features and performance are compared. The binomial explorative features of the DE framework in contraposition to the exploitative features of the local searcher are analyzed in detail in light of the stagnation prevention problem, typical for the DE. Much emphasis in this chapter …
Variable Selection in Predictive MIDAS Models
2014
In short-term forecasting, it is essential to take into account all available information on the current state of the economic activity. Yet, the fact that various time series are sampled at different frequencies prevents an efficient use of available data. In this respect, the Mixed-Data Sampling (MIDAS) model has proved to outperform existing tools by combining data series of different frequencies. However, major issues remain regarding the choice of explanatory variables. The paper first addresses this point by developing MIDAS based dimension reduction techniques and by introducing two novel approaches based on either a method of penalized variable selection or Bayesian stochastic searc…
DRIFTS Sensor: Soil Carbon Validation at Large Scale (Pantelleria, Italy)
2013
A fast and accurate measurement of soil carbon is needed in current scientific issues. Today there are many sensors suitable for these purposes, but choosing the appropriate sensor depends on the spatial scale at which the studies are conducted. There are few detailed studies that validate these types of measures allowing their immediate use. Here it is validated the quick use of a sensor in execution at Pantelleria, chosen for size, use and variability of the parameter measured, to give an operational tool for carbon stocks studies. The DRIFT sensor used here has been validated in the first 60 cm of the soil of the whole island, and it has shown predictivity higher than 90%.