NDLI: Effective localized regression for damage detection in large complex mechanical structures

Please wait, while we are loading the content...

An iterative method for multi-class cost-sensitive learning

TiVo: making show recommendations using a distributed collaborative filtering architecture

On demand classification of data streams

Cross channel optimized marketing by reinforcement learning

User-centered design for KDD

Approximating a collection of frequent sets

Predicting customer shopping lists from point-of-sale purchase data

A generalized maximum entropy approach to bregman co-clustering and matrix approximation

Interactive training of advanced classifiers for mining remote sensing image archives

Graphical models for data mining

Mining reference tables for automatic text segmentation

A rank sum test method for informative gene discovery

An objective evaluation criterion for clustering

Exploring the community structure of newsgroups

Recovering latent time-series from their observed sums: network tomography with particle filters.

Early detection of insider trading in option markets

Column-generation boosting methods for mixture of kernels

Feature selection in scientific applications

Fast nonlinear regression via eigenimages applied to galactic morphology

Mining coherent gene clusters from gene-sample-time microarray data

IncSpan: incremental mining of sequential patterns in large database

A general approach to incorporate data quality matrices into data mining algorithms

Clustering time series from ARMA models with clipped data

Eigenspace-based anomaly detection in computer systems

Parallel computation of high dimensional robust correlation and covariance matrices

ANN quality diagnostic models for packaging manufacturing: an industrial data mining case study

A probabilistic framework for semi-supervised clustering

Effective localized regression for damage detection in large complex mechanical structures

Belief state approaches to signaling alarms in surveillance systems

A system for automated mapping of bill-of-materials part numbers

Data mining in metric space: an empirical analysis of supervised learning performance criteria

Visually mining and monitoring massive time series

Locating secret messages in images

Tracking dynamics of topic trends using a finite mixture model

Fully automatic cross-associations

Learning to detect malicious executables in the wild

Kernel k-means: spectral clustering and normalized cuts

Mining traffic data from probe-car system for travel time prediction

Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods

Predicting prostate cancer recurrence via maximizing the concordance index

A microeconomic data mining problem: customer-oriented catalog segmentation

Programming the K-means clustering algorithm in SQL

Adversarial classification

Density-based spam detector

k-TTP: a new privacy model for large-scale distributed environments

Document preprocessing for naive Bayes classification and clustering with mixture of multinomials

Regularized multi--task learning

V-Miner: using enhanced parallel coordinates to mine product design and test data

Diagnosing extrapolation: tree-based density estimation

Learning a complex metabolomic dataset using random forests and support vector machines

Fast discovery of connection subgraphs

Discovering additive structure in black box functions

1-dimensional splines as building blocks for improving accuracy of risk outcomes models

Systematic data selection to mine concept-drifting data streams

SPIN: mining maximal frequent subgraphs from graph databases

Analytical view of business data

Efficient closed pattern mining in the presence of tough block constraints

On detecting space-time clusters

Discovering complex matchings across web query interfaces: a correlation mining approach

Why collective inference improves relational classification

Cyclic pattern kernels for predictive graph mining

When do data mining results violate privacy?

Mining and summarizing customer reviews

Improved robustness of signature-based near-replica detection via lexicon randomization

Interestingness of frequent itemsets using Bayesian networks as background knowledge

Learning spatially variant dissimilarity (SVaD) measures

Mining the space of graph properties

Clustering moving objects

Web usage mining based on probabilistic latent semantic analysis

A framework for ontology-driven subspace clustering

Towards parameter-free data mining

The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data

A graph-theoretic approach to extract storylines from search results

Sleeved coclustering

Incremental maintenance of quotient cube for median

Semantic representation: search and mining of multimedia content

Mining, indexing, and querying historical spatiotemporal data

A quickstart in frequent structure mining can make a difference

Machine learning for online query relaxation

Automatic multimedia cross-modal correlation discovery

Rapid detection of significant spatial clusters

Estimating the size of the telephone universe: a Bayesian Mark-recapture approach

Turning CARTwheels: an alternating algorithm for mining redescriptions

Cluster-based concept invention for statistical relational learning

Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage

Identifying early buyers from purchase data

A Bayesian network framework for reject inference

Privacy preserving regression modelling via distributed computation

Support envelopes: a technique for exploring the structure of association patterns

Probabilistic author-topic models for information discovery

Generalizing the notion of support

Scalable mining of large disk-based graph databases

Ordering patterns by combining opinions from multiple sources

Incorporating prior knowledge with weighted margin support vector machines

A generative probabilistic approach to visualizing sets of symbolic sequences

Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs

Rotation invariant distance measures for trajectories

The complexity of mining maximal frequent itemsets and maximal frequent patterns

Privacy-preserving Bayesian network structure computation on distributed heterogeneous data

GPCA: an efficient dimension reduction scheme for image compression and retrieval

Mining scale-free networks using geodesic clustering

IDR/QR: an incremental dimension reduction algorithm via QR decomposition

IMMC: incremental maximum margin criterion

On the discovery of significant statistical quantitative rules

2PXMiner: an efficient two pass mining of frequent XML query patterns

Fast mining of spatial collocations

Redundancy based feature selection for microarray data

A cross-collection mixture model for comparative text mining

A data mining approach to modeling relationships among categories in image collection

A DEA approach for model combination

Optimal randomization for privacy preserving data mining

Effective localized regression for damage detection in large complex mechanical structures

Content Provider	ACM Digital Library
Author	Lazarevic, Aleksandar Kanapady, Ramdev Kamath, Chandrika
Abstract	In this paper, we propose a novel data mining technique for the efficient damage detection within the large-scale complex mechanical structures. Every mechanical structure is defined by the set of finite elements that are called structure elements. Large-scale complex structures may have extremely large number of structure elements, and predicting the failure in every single element using the original set of natural frequencies as features is exceptionally time-consuming task. Traditional data mining techniques simply predict failure in each structure element individually using global prediction models that are built considering all data records. In order to reduce the time complexity of these models, we propose a localized clustering-regression based approach that consists of two phases: (1) building a local cluster around a data record of interest and (2) predicting an intensity of damage only in those structure elements that correspond to data records from the built cluster. For each test data record, we first build a cluster of data records from training data around it. Then, for each data record that belongs to discovered cluster, we identify corresponding structure elements and we build a localized regression model for each of these structure elements. These regression models for specific structure elements are constructed using only a specific set of relevant natural frequencies and merely those data records that correspond to the failure of that structure element. Experiments performed on the problem of damage prediction in a large electric transmission tower frame indicate that the proposed localized clustering-regression based approach is significantly more accurate and more computationally efficient than our previous hierarchical clustering approach, as well as global prediction models.
Starting Page	450
Ending Page	459
Page Count	10
File Format	PDF
ISBN	1581138881
DOI	10.1145/1014052.1014103
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2004-08-22
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Structure elements Damage detection Mechanical structures Localized regression Clustering
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in