Colloque avec actes et comité de lecture. internationale.International audienceThis article presents a study performed in the scope of an industrial research project supported by the ECSC. Unsupervised methods of signal encoding and unsupervised extraction of evolution pattern are presented. The main advantages are the ability of proposed clustering method to process arbitrary long input vectors and the adapted coding method that is based on feature extraction of the analysed signals. First results obtained on electric arc furnace data are shown || Cet article présente une étude réalisée dans le cadre d'un projet industriel de recherche subventionné par la CECA. Des méthodes non-supervisées de codage et d'extraction de prototypes d'évolutio...
Modern industrial mining and mineral processing applications are characterized by large volumes of h...
The growing popularity of the electrical arc furnace in metallurgical industries causes significant ...
The main objective of this thesis is to propose a dynamic clustering algorithm that can handle not o...
This study is interested in analyzing the contribution of artificial neuralnetworks in order to impr...
The electric arc furnace has been the subject of extensive research due to its complex and chaotic n...
International audienceThe sensitivity of AE sensors makes the AE technique very interesting for dete...
Modern process logging systems for electric arc furnaces have the capability of storing large quanti...
As feature sizes on semiconductor chips continue to shrink plasma etching is becoming a more and mo...
A new method for analyzing time series data is introduced in this paper. Inspired by data mining, th...
Energiency est une entreprise qui vend à des industriels une plate-forme pour leur permettre d’analy...
International audienceNowadays systems must adapt to rapidly changing environments and must show beh...
This paper proposes an unsupervised learning schema for seeking the patterns in rms voltage variatio...
In this article, the extraction of features from acoustic signals generated by a 60-kW direct curren...
The rapid growth of data storage capacities of process automation systems provides new possibilities...
A new method for analyzing time series data is introduced in this paper. Inspired by data mining, th...
Modern industrial mining and mineral processing applications are characterized by large volumes of h...
The growing popularity of the electrical arc furnace in metallurgical industries causes significant ...
The main objective of this thesis is to propose a dynamic clustering algorithm that can handle not o...
This study is interested in analyzing the contribution of artificial neuralnetworks in order to impr...
The electric arc furnace has been the subject of extensive research due to its complex and chaotic n...
International audienceThe sensitivity of AE sensors makes the AE technique very interesting for dete...
Modern process logging systems for electric arc furnaces have the capability of storing large quanti...
As feature sizes on semiconductor chips continue to shrink plasma etching is becoming a more and mo...
A new method for analyzing time series data is introduced in this paper. Inspired by data mining, th...
Energiency est une entreprise qui vend à des industriels une plate-forme pour leur permettre d’analy...
International audienceNowadays systems must adapt to rapidly changing environments and must show beh...
This paper proposes an unsupervised learning schema for seeking the patterns in rms voltage variatio...
In this article, the extraction of features from acoustic signals generated by a 60-kW direct curren...
The rapid growth of data storage capacities of process automation systems provides new possibilities...
A new method for analyzing time series data is introduced in this paper. Inspired by data mining, th...
Modern industrial mining and mineral processing applications are characterized by large volumes of h...
The growing popularity of the electrical arc furnace in metallurgical industries causes significant ...
The main objective of this thesis is to propose a dynamic clustering algorithm that can handle not o...