Quantification of Neural Network Uncertainties on the Hydrogeological Predictions by Probability Density Functions

International audienceThe risk of drought impacting the drinking water and agricultural production is worrying in the developed countries, especially in a changing climate context. To manage and prevent this phenomenon, real-time monitoring and predictive systems are emerging as the key solutions. In the field of artificial intelligence, neural networks are one of these predictive systems. This family of parameterized models is a composition of neuronal functions, which apply a non-linear transformation from their inputs to their outputs. These networks are able to learn a hydro(geo)logical system behaviour using a database composed of observed inputs (rainfall, evapotranspiration, etc.) and outputs (groundwater level, discharge, etc.), thanks to an algorithm minimizing a cost function between observed and simulated outputs. However, it remains difficult to assess the uncertainty generated by these models, possibly leading to misinterpretations by the end users. These uncertainties are mainly of three types. The first is related to the input data. Indeed, hydrosystems are surface elements whereas meteorological inputs are punctual elements. The interpolation error can, therefore, be significant because of the lack of knowledge between gauging stations. The second is the neural network model architecture itself. It is possible to deal with this source of uncertainty using regularization methods. Finally, the neural networks are submitted to uncertainties related to parameter initialization, before the training step. The initial parameters may have an important impact on the results. In this paper, we address the prediction of the Blavet groundwater level (Bretagne, France). In order to assess uncertainties, we will first focus on the parameters initialization of the model. Neuronal models are optimized using cross-validation and early stopping. Then, an ensemble model is realized, in which each member is the result of a unique set of parameters initialization. The purpose of the study is to define how many initializations are necessary to obtain a reasonable confidence interval for forecasts, with the smallest interval and the higher rate of observed points inside this interval. The best model will be determined using cross-validation scores thereby ensuring optimal robustness. We show that, in this case study, an ensemble model of 20 different initializations is sufficient to estimate uncertainty while preserving quality. In the second part, the resulting ensemble model will be used to estimate the global model uncertainty using probability density functions (pdf) applied to the distribution of groundwater level data and cross-validation scores of forecasts. It reveals that the groundwater level predictions are composed of two mixed distributions. Therefore, we will use the expectation-maximization algorithm (EM) to obtain parameters of mixed models. Mixed normal and mixed Gumbel laws, among five mixed distributions assessed, give the best groundwater distribution and are able to generate an abacus drawing uncertainty of mode

Tuning, Impedance Matching, and Temperature Regulation during High-Temperature Microwave Sintering of Ceramics

International audienceOver the years, microwave radiation has emerged as an efficient source of energy for material processing. This technology provides a rapid and a volumetric heating of material. However, the main issues that prevent microwave technology from being widespread in material processing are temperature control regulation and heating distribution within the sample. Most of the experimental works are usually manually monitored, and their reproducibility is rarely evaluated and discussed. In this work, an originally designed 915MHz microwave single-mode applicator for high-temperature processing is presented. The overall microwave system is described in terms of an equivalent electrical circuit. This circuit has allowed to point out the different parameters which need to be adjusted to get a fully controlled heating process. The basic principle of regulation is then depicted in terms of a block function diagram. From it, the process has been developed and tested to sinter zirconia-and spinel-based ceramics. It is clearly shown that the process can be successfully used to program multistep temperature cycles up to similar to 1550 degrees C, improving significantly the reproducibility and the ease of use of this emerging high-temperature process technology

Monocomponent photoinitiators based on benzophenone-carbazole structure for LED photoinitiating systems and application on 3D printing

In this article, different substituents (benzoyl, acetyl, styryl) are introduced onto the carbazole scaffold to obtain 8 novel carbazole derivatives. Interestingly, a benzoyl substituent, connected to a carbazole group, could form a benzophenone moiety, which composes a monocomponent Type II benzophenone-carbazole photoinitiator (PI). The synergetic effect of the benzophenone moiety and the amine in the carbazole moiety is expected to produce high performance photoinitiating systems (PISs) for the free radical photopolymerization (FRP). For different substituents, clear effects on the light absorption properties are demonstrated using UV-Visible absorption spectroscopy. Benzophenone-carbazole PIs can initiate the FRP of acrylates alone (monocomponent Type II photoinitiator behavior). In addition, fast polymerization rates and high function conversions of acrylate are observed when an amine and/or an iodonium salt are added in systems. Benzophenone-carbazole PIs have good efficiencies in cationic photopolymerization (CP) upon LED @ 365 nm irradiation in the presence of iodonium salt. In contrast, other PIs without synergetic effect demonstrate unsatisfied photopolymerization profiles in the same conditions. The best PIS identified for the free radical photopolymerization were used in three-dimensional (3D) printing. Steady state photolysis and fluorescence quenching experiments were carried out to investigate the reactivity and the photochemistry and photophysical properties of PIs. The free radicals, generated from the studied PISs, are detected by the electron spin resonance - spin trapping technique. The proposed chemical mechanisms are provided and the structure/reactivity/efficiency relationships are also discussed. All the results showed that the benzophenone-carbazole PIs have a good application potential, and this work provides a rational design route for PI molecules. Remarkably, BPC2-BPC4, C6, C8 were never synthetized before; therefore, 5 of the 8 compounds are completely new

Representation and parsing of multiword expressions: Current trends

This book consists of contributions related to the definition, representation and parsing of MWEs. These reflect current trends in the representation and processing of MWEs. They cover various categories of MWEs such as verbal, adverbial and nominal MWEs, various linguistic frameworks (e.g. tree-based and unification-based grammars), various languages including English, French, Modern Greek, Hebrew, Norwegian), and various applications (namely MWE detection, parsing, automatic translation) using both symbolic and statistical approaches

Representation and parsing of multiword expressions: Current trends

This book consists of contributions related to the definition, representation and parsing of MWEs. These reflect current trends in the representation and processing of MWEs. They cover various categories of MWEs such as verbal, adverbial and nominal MWEs, various linguistic frameworks (e.g. tree-based and unification-based grammars), various languages including English, French, Modern Greek, Hebrew, Norwegian), and various applications (namely MWE detection, parsing, automatic translation) using both symbolic and statistical approaches

Representation and parsing of multiword expressions: Current trends

This book consists of contributions related to the definition, representation and parsing of MWEs. These reflect current trends in the representation and processing of MWEs. They cover various categories of MWEs such as verbal, adverbial and nominal MWEs, various linguistic frameworks (e.g. tree-based and unification-based grammars), various languages including English, French, Modern Greek, Hebrew, Norwegian), and various applications (namely MWE detection, parsing, automatic translation) using both symbolic and statistical approaches

Representation and parsing of multiword expressions: Current trends

This book consists of contributions related to the definition, representation and parsing of MWEs. These reflect current trends in the representation and processing of MWEs. They cover various categories of MWEs such as verbal, adverbial and nominal MWEs, various linguistic frameworks (e.g. tree-based and unification-based grammars), various languages including English, French, Modern Greek, Hebrew, Norwegian), and various applications (namely MWE detection, parsing, automatic translation) using both symbolic and statistical approaches

Representation and parsing of multiword expressions: Current trends

This book consists of contributions related to the definition, representation and parsing of MWEs. These reflect current trends in the representation and processing of MWEs. They cover various categories of MWEs such as verbal, adverbial and nominal MWEs, various linguistic frameworks (e.g. tree-based and unification-based grammars), various languages including English, French, Modern Greek, Hebrew, Norwegian), and various applications (namely MWE detection, parsing, automatic translation) using both symbolic and statistical approaches

Representation and parsing of multiword expressions: Current trends

This book consists of contributions related to the definition, representation and parsing of MWEs. These reflect current trends in the representation and processing of MWEs. They cover various categories of MWEs such as verbal, adverbial and nominal MWEs, various linguistic frameworks (e.g. tree-based and unification-based grammars), various languages including English, French, Modern Greek, Hebrew, Norwegian), and various applications (namely MWE detection, parsing, automatic translation) using both symbolic and statistical approaches