Browsing
     by title


0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

or enter first few letters:   
OK
See detailData assimilation in nested-grid models
Vandenbulcke, Luc ULg; Barth, Alexander ULg; Ben Bouallegue, Z. et al

Conference (2004, May)

Detailed reference viewed: 16 (2 ULg)
See detailData cleaning
Monseur, Christian ULg

in Adams, R.; Wu, M. (Eds.) PISA 2000 : technical report (2002)

Detailed reference viewed: 7 (1 ULg)
Full Text
See detailData Clustering for the Identification of the Bifurcation Behaviour in Non-Linear Aeroelastic Systems using a Coupled Harmonic Balance/Genetic Algorithm Approach
Vio, Gareth Arthur; Dimitriadis, Grigorios ULg; Cooper, Jonathan Edward

in Proceedings of the 2008 International Conference on Noise and Vibration Engineering (2008, September)

This paper describes an efficient method for calculating the bifurcation behaviour of an aeroelastic system using a Harmonic Balance expansion coupled with a Genetic Algorithm, combined with a clustering ... [more ▼]

This paper describes an efficient method for calculating the bifurcation behaviour of an aeroelastic system using a Harmonic Balance expansion coupled with a Genetic Algorithm, combined with a clustering algorithm in order to determine all the solutions at every single flight condition. It will be shown how it is possible to obtain all the bifurcation branches in one step. Two clustering algorithms, K-Means and PAM, together with a number of cluster index techniques, such as Davies-Boulding, Calinski-Harabasz are investigated. The method is applied to an aeroelastic galloping problem as this phenomenon presents a number of co-existing limit cycles at a range of airspeeds. [less ▲]

Detailed reference viewed: 34 (1 ULg)
Full Text
Peer Reviewed
See detailData driven choice of the classification rule in discriminant analysis applied to isoberlinia stands
Glele Kakaï, R. L.; Palm, Rodolphe ULg

in West African Journal of Biophysics and Biomathematics (2007), 1

A simulation study is performed to evaluate, in discriminant analysis, the relative performance of the linear, quadratic and logistic rules, on 52,800 sample couples, characterized by the distribution and ... [more ▼]

A simulation study is performed to evaluate, in discriminant analysis, the relative performance of the linear, quadratic and logistic rules, on 52,800 sample couples, characterized by the distribution and the overlap of the populations, the number of variables, the samples size and the theoretical heteroscedasticity degree of the populations, defined in the study. For each sample couple, the relative error of the actual error rate of each classification rule is computed as well as the estimated heteroscedasticity degree and the multinormality test's statistic. The results obtained helps to notice that the linear rule can be advised when the multinormality hypothesis is accepted and the logistic rule in the other cases. The quadratic rule gives the lowest performance in most of the considered cases. Anoter method is based on the estimated heteroscedasticity and normality degrees of the considered sample couple. [less ▲]

Detailed reference viewed: 10 (0 ULg)
Full Text
Peer Reviewed
See detailData Entry Errors and Design for Model-Based Tight Glycemic Control in Critical Care
Ward, Logan; Steel, James; Le Compte, Aaron et al

in Journal of Diabetes Science and Technology (2012)

Detailed reference viewed: 11 (8 ULg)
See detailData Fauna-Flora 1.0. Guide d’utilisation.
Barbier, Yvan; Rasmont, Pierre; Dufrêne, Marc ULg et al

Software (2000)

Detailed reference viewed: 5 (1 ULg)
Peer Reviewed
See detailData Fusion by Belief Propagation for Multi-Camera Tracking
Du, Wei ULg; Piater, Justus ULg

in The 9th International Conference on Information Fusion (2006)

Detailed reference viewed: 14 (0 ULg)
Full Text
Peer Reviewed
See detailA Data Imputation Method with Support Vector Machines for Activity-Based Transportation Models
Yang, Banghua; Janssens, Davy; Ruan, Da et al

in Wang, Y.; Li, T. (Eds.) Foundations of Intelligent Systems: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE 2011) (2011)

In this paper, a data imputation method with a Support Vector Machine (SVM) is proposed to solve the issue of missing data in activity-based diaries. Here two SVM models are established to predict the ... [more ▼]

In this paper, a data imputation method with a Support Vector Machine (SVM) is proposed to solve the issue of missing data in activity-based diaries. Here two SVM models are established to predict the missing elements of ‘number of cars’ and ‘driver license’. The inputs of the former SVM model include five variables (Household composition, household income, Age oldest household member, Children age class and Number of household members). The inputs of the latter SVM model include three variables (personal age, work status and gender). The SVM models to predict the ‘number of cars’ and ‘driver license’ can achieve accuracies of 69% and 83% respectively. The initial experimental results show that missing elements of observed activity diaries can be accurately inferred by relating different pieces of information. Therefore, the proposed SVM data imputation method serves as an effective data imputation method in the case of missing information. [less ▲]

Detailed reference viewed: 43 (2 ULg)
See detailData in astronomy -- Carlos Jaschek
Manfroid, Jean ULg

in Ciel et Terre (1990), 106

Not Available

Detailed reference viewed: 8 (0 ULg)
Full Text
Peer Reviewed
See detailData Interpolating Empirical Orthogonal Functions (DINEOF): a tool for geophysical data analyses
Alvera Azcarate, Aïda ULg; Barth, Alexander ULg; Sirjacobs, Damien ULg et al

in Mediterranean Marine Science (2011), 12(3), 5-11

An overview of the technique called DINEOF (Data Interpolating Empirical Orthog- onal Functions) is presented. DINEOF reconstructs missing information in geophys- ical data sets, such as satellite imagery ... [more ▼]

An overview of the technique called DINEOF (Data Interpolating Empirical Orthog- onal Functions) is presented. DINEOF reconstructs missing information in geophys- ical data sets, such as satellite imagery or time series. A summary of the technique is given, with its main characteristics, recent developments and future research di- rections. DINEOF has been applied to a large variety of oceanographic variables in various domains of different sizes. This technique can be applied to a single variable (monovariate approach), or to several variables together (multivariate approach), with no complexity increase in the application of the technique. Error fields can be computed to establish the accuracy of the reconstruction. Examples are given to illustrate the capabilities of the technique. DINEOF is freely offered to download, and help is provided to users in the form of a wiki and through a discussion email list. [less ▲]

Detailed reference viewed: 180 (26 ULg)
See detailData mining
Martin, Didier ULg

Scientific conference (2011, June 15)

Detailed reference viewed: 18 (1 ULg)
Full Text
Peer Reviewed
See detailA Data Mining Analysis Applied to a Straightening Process Database
Caprace, Jean-David ULg; Losseau, N.; Bair, Frédéric ULg et al

in Ship Technology Research = Schiffstechnik (2007), 54(4), 177-183

Detailed reference viewed: 38 (4 ULg)
Full Text
Peer Reviewed
See detailA Data Mining Analysis Applied to a Straightening Process Database
Caprace, Jean-David ULg; Losseau, Nicolas ULg; Archambeau, Dominique et al

in Conference on Computer Applications and Information Technology in the Maritime Industries (COMPIT) (2007, April)

The paper presents the results of a data mining analysis aiming to improve the cost knowledge of the labour intensive straightening process. The data mining approach yields a formula linking the ... [more ▼]

The paper presents the results of a data mining analysis aiming to improve the cost knowledge of the labour intensive straightening process. The data mining approach yields a formula linking the straightening cost to the sections scantlings (plate thickness, dimension and inter-distance of longitudinal stiffeners, dimension and inter-distance of transversal frames) and to other section characteristics. [less ▲]

Detailed reference viewed: 87 (27 ULg)
Full Text
Peer Reviewed
See detailA Data Mining Analysis Applied to a Straightening Process Database
Caprace, Jean-David ULg; Losseau, Nicolas; Bair, Frédéric ULg et al

in Ship Technology Research = Schiffstechnik (2007), 54(4), 177-183

The complexity of modern manufacturing processes in a highly competitive environment forces the manufacturers to invest massively in automation and monitoring systems. The large data flows from these new ... [more ▼]

The complexity of modern manufacturing processes in a highly competitive environment forces the manufacturers to invest massively in automation and monitoring systems. The large data flows from these new installations are sources of valuable and hidden knowledge that is so far hardly used. Data mining methods through integrated data analysis tools give a solution to this situation, allowing easy retrieval of knowledge starting from a data base. This is also a unique opportunity to learn faster about the process and to detect hidden and complex relationships between parameters involved. Within this framework we have decided to apply this data analysis method to the straightening process in shipbuilding. We refer to Caprace et al. (2007) for additional illustrations. In shipbuilding, the assembly of elements by welding involves temperature gradients within the ma- terial. These cause deformations which sometimes have to be reduced to obtain an acceptable surface flatness. The straightening process to eliminate these distortions for esthetical or functional reasons is labour intensive. Estimating the straightening impact on the production workload is interesting in the context of production simulation, cost assessment of ship hull, structure optimization, design for production, etc. To reach these objectives, the idea was to elaborate, through a data mining approach, a formula linking the straightening cost to the sections scantlings (plate thickness, dimension and inter-distance of longitudinal stiffeners, dimension and inter-distance of transversal frames) and to other section characteristics. This paper describes each stage of the methodology: data description, analysis of data quality, data exploration and finally choice of discriminatory attributes and the generation of the data-driven models. [less ▲]

Detailed reference viewed: 131 (33 ULg)
Full Text
Peer Reviewed
See detailA Data Mining Analysis to evaluate the additional workloads caused by welding distortions
Losseau, Nicolas ULg; Caprace, Jean-David ULg; Aracil Fernandez, Francisco et al

in MARSTRUCT'09 (2009, March)

This paper presents a way to minimize cost in shipbuilding industry by using the results of a data mining analysis aiming to improve the cost knowledge of the additional operations caused by welding ... [more ▼]

This paper presents a way to minimize cost in shipbuilding industry by using the results of a data mining analysis aiming to improve the cost knowledge of the additional operations caused by welding distortions. This statistical analysis had the scope to establish assessment formulas of the supplementary workloads in function of scantlings and welding distortions. Those formulas can be useful to evaluate the profitability of new welding devices and can improve the research in the following domains: production simulation, cost assessment of ship hull, structure optimization, design for production, etc. [less ▲]

Detailed reference viewed: 79 (15 ULg)
Full Text
See detailData Mining in Ship Construction and operation
Caprace, Jean-David ULg

Conference (2011, January)

Detailed reference viewed: 33 (3 ULg)
Full Text
Peer Reviewed
See detailData mining tools and application in power system engineering
Olaru, Cristina; Geurts, Pierre ULg; Wehenkel, Louis ULg

in Proceedings of the 13th Power System Computation Conference, PSCC99 (1999)

The power system field is presently facing an explosive growth of data. The data mining (DM) approach provides tools for making explicit some implicit subtle structure in data. Applying data mining to ... [more ▼]

The power system field is presently facing an explosive growth of data. The data mining (DM) approach provides tools for making explicit some implicit subtle structure in data. Applying data mining to power system engineering is an iterative and interactive process, requiring an acquainted user with the application specifics. The paper describes data mining tools like statistical methos, visualization, machine learning and neural networks, exemplifying by results obtained with a DM software developed for dynamic security assessment studies. Power system engineering applications where data mining would be useful are reviewed in the second part of the paper. [less ▲]

Detailed reference viewed: 119 (0 ULg)