Recent advances in Machine Learning have brought to attention new theories of learning as well as new approaches. Among these, the Ensemble method has received wide attention and has been shown to be a promising method for classification problems. Simply speaking, the ensemble method is a learning algorithm that constructs a set of “weak” classifiers and then combines their predictions to produ...

Un automate bous t roph6don est un automate fini (non d&erministe) muni d 'une t&e de lecture pouvant se d6placer dans les deux sens. Le compor tement fini d 'un tel au tomate est bien connu: il est identique h celui d 'un automate fini (cf. [5] et [4]). Nous montrons ici qu' i l e n e s t de m~me de son compor tement infini. Dans ce qui suit A d6signe un alphabet fini, A* l 'ensemble des mots ...

Bias correction is a very important pre-processing step in satellite data assimilation analysis, as data assimilation itself cannot circumvent satellite biases. We introduce a retrieval algorithm-specific and spatially heterogeneous Instantaneous Field of View (IFOV) bias correction method for Soil Moisture and Ocean Salinity (SMOS) soil moisture. To the best of our knowledge, this is the first...

Appropriate precautions in the case of flood occurrence often require long lead times (several days) in hydrological forecasting. This in turn implies large uncertainties that are mainly inherited from the meteorological precipitation forecast. Here we present a case study of the extreme flood event of August 2005 in the Swiss part of the Rhine catchment (total area 34 550 km2). This event caus...

With the development of in-situ monitoring techniques, the ensemble Kalman filter (EnKF) has become a popular data assimilation method due to its capability to jointly update model parameters and state variables in a sequential way, and to assess the uncertainty associated with estimation and prediction. To take the conceptual model uncertainty into account during the data assimilation process,...

The Wisdom of Crowds, an innovative theory described in social science, claims that the aggregate decisions made by a group will often be better than those of its individual members if the four fundamental criteria of this theory are satisfied. This theory used for in clustering problems. Previous researches showed that this theory can significantly increase the stability and performance of...

Numerical model predictions of tropical cyclone (TC) intensity and structure suffer from deficiencies associated with initial conditions and model formulation. Here, we propose to study how errors in the HWRF model’s initial conditions impact subsequent forecasts of TC intensity and wind structure using ensemble forecasts and the ensemble-based sensitivity method. This study will utilize the se...

architecture has been always recognized as a framework which is influenced by social beliefs, traditions and interactions and furthermore affects individual soul and tendency. therefore it is impossible to analyze and consequently identify an architectural artifact if not accompanied by analysis of intellectual fundamentals of its contemporary society. the ensemble of sheikh safi al-din which i...

Recently Semi-Supervised learning algorithms such as co-training are used in many application domains. In co-training, two classifiers based on different views of data or on different learning algorithms are trained in parallel and then unlabeled data that are classified differently by the classifiers but for which one classifier has large confidence are labeled and used as training data for th...

In many modern day systems such as information extraction and knowledge management agents, ontologies play a vital role in maintaining the concept hierarchies of the selected domain. However, ontology population has become a problematic process due to its nature of heavy coupling with manual human intervention. With the use of word embeddings in the filed of natural language processing, it beca...