Letteratura scientifica selezionata sul tema "Intelligence artificielle hybride"
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Articoli di riviste sul tema "Intelligence artificielle hybride":
Borot, Sophie. "Cent ans après la découverte de l’insuline : une nouvelle révolution pour les patients vivant avec un diabète de type 1 ?" Biologie Aujourd’hui 216, n. 1-2 (2022): 29–35. http://dx.doi.org/10.1051/jbio/2022005.
Larsonneur, Claire. "Intelligence artificielle ET/OU diversité linguistique : les paradoxes du traitement automatique des langues". Hybrid, n. 7 (8 aprile 2021). http://dx.doi.org/10.4000/hybrid.650.
Tesi sul tema "Intelligence artificielle hybride":
Kriaa, Hassen. "Analyse et conception révisable par interaction entre agents : Une approche hybride". Pau, 2000. http://www.theses.fr/2000PAUU3011.
Roy, Patrice. "Un modèle hybride de reconnaissance de plans pour les patients Alzheimer : dilemme entrecroisé/erroné /". Thèse, Chicoutimi : Montréal : Université du Québec à Chicoutimi ; Université du Québec à Montréal, 2007. http://theses.uqac.ca.
La p. de t. porte en outre: Mémoire présenté à l'Université du Québec à Chicoutimi comme exigence partielle de la maîtrise en informatique. CaQQUQ Bibliogr.: f. 133-138. Document électronique également accessible en format PDF. CaQQUQ
Ortiz, Paul. "Conception d’un système hybride de stockage de l’énergie pour la réduction des émissions carbone dans l’habitat individuel". Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0208.
Private homes are increasingly fitted with PhotoVoltaics (PV) for increasing the renewable energy use. Typical issues of this type of installation are : (1) the production of green energy is not necessary in line with the inhabitants' energy consumption (2) a peak of energy demand on smart grid increases the carbon emission. Mitigating carbon emission in using efficiently PV is the main objective of this research, which is part of the INTERREG NW Europe RED WOLF project (H2020 programme). This project is led led by Leeds Beckett University and involves 21 partners across Europe, including University of Lorraine. The RED WOLF project aims at installing PV solar panels and home batteries across UK, France, Netherlands, and Ireland, with the overall goal to design a Smart Storage Driver (SDS) system capables at storing solar energy produced at home, and using it when a peak of energy demand is detected on smart grid. To this end, the research is divided into three steps: (i) first, it is necessary to understand how inhabitants behave in order to obtain an energy consumption pattern for each home. This pattern will be used to size the batteries and to smartly manage the switching between the use of local and smart grid energy. Specific instrumentation will be deployed to achieve this step ; (ii) second, it is necessary to design a SDS system aiming at analysing data coming from multiple sources (e.g., smart grid, weather, indoor temperature, inhabitant behaviour, battery charge level) with one major target : the limitation of carbon emission ; (iii) finally, a global analysis ofdata management (Cloud and Fog) and network management (SDN, IoT) must be carried out in order to find the best trade off between Quality of Service offered for inhabitants and environmental impact
Bultey, Alexis. "Représentation hybride des heuristiques et métaconnaissances utilisées pour la conception innovante". Strasbourg, 2009. http://www.theses.fr/2009STRA6106.
This PhD thesis is about a theoretical and practical analysis of the conceptual phases of the design process. It aims at extracting its recurrent elements in order to be reusable in different contexts and it also aims at making that process easily computer implemented. With this goal, we have studied the russian theory TRIZ, which pretends to formalize the inventive process. We conclude that this theory has a great interest for design process and we prove that this theory might be implemented in a computer-aided design system. The results of this PhD thesis can be decomposed in three parts: formalization, operationalisation and implementation. Formalization suggests an ontological modelling of one of the TRIZ methodologies, named Substance-Field analysis. Operationalisation proposes a translation of the formalization to be supported by a computer. The implementation is a software tool based on a hybrid system combining description logics and first order logic rules
Liu, Ziming. "Méthodes hybrides d'intelligence artificielle pour les applications de navigation autonome". Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4004.
Autonomous driving is a challenging task that has a wide range of applications in the real world. The autonomous driving system can be used in different platforms, such as cars, drones, and robots. These autonomous systems will reduce a lot of human labor and improve the efficiency of the current transportation system. Some autonomous systems have been used in real scenarios, such as delivery robots, and service robots. In the real world, autonomous systems need to build environment representations and localize themselves to interact with the environment. There are different sensors can be used for these objectives. Among them, the camera sensor is the best choice between cost and reliability. Currently, visual autonomous driving has achieved significant improvement with deep learning. Deep learning methods have advantages for environment perception. However, they are not robust for visual localization where model-based methods have more reliable results. To utilize the advantages of both data-based and model-based methods, a hybrid visual odometry method is explored in this thesis. Firstly, efficient optimization methods are critical for both model-based and data-based methods which share the same optimization theory. Currently, most deep learning networks are still trained with inefficient first-order optimizers. Therefore, this thesis proposes to extend efficient model-based optimization methods to train deep learning networks. The Gaussian-Newton and the efficient second-order methods are applied for deep learning optimization. Secondly, the model-based visual odometry method is based on the prior depth information, the robust and accurate depth estimation is critical for the performance of visual odometry module. Based on traditional computer vision theory, stereo vision can compute the depth with the correct scale, which is more reliable than monocular solutions. However, the current two-stage 2D-3D stereo networks have the problems of depth annotations and disparity domain gap. Correspondingly, a pose-supervised stereo network and an adaptive stereo network are investigated. However, the performance of two-stage networks is limited by the quality of 2D features that build stereo-matching cost volume. Instead, a new one-stage 3D stereo network is proposed to learn features and stereo-matching implicitly in a single stage. Thirdly, to keep robust, the stereo network and the dense direct visual odometry module are combined to build a stereo hybrid dense direct visual odometry (HDVO). Dense direct visual odometry is more reliable than the feature-based method because it is optimized with global image information. The HDVO is optimized with the photometric minimization loss. However, this loss suffers noises from the occlusion area, homogeneous texture area, and dynamic objects. This thesis explores removing noisy loss values with binary masks. Moreover, to reduce the effects of dynamic objects, semantic segmentation results are used to improve these masks. Finally, to be generalized for a new data domain, a test-time training method for visual odometry is explored. These proposed methods have been evaluated on public autonomous driving benchmarks, and show state-of-the-art performances
Ali, Sadaqat. "Energy management of multi-source DC microgrid systems for residential applications". Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0159.
Compared to the alternating current (AC) electrical grid, the direct current (DC) electrical grid has demonstrated numerous advantages, such as its natural interface with renewable energy sources (RES), energy storage systems, and DC loads. It offers superior efficiency with fewer conversion steps, simpler control without skin effect or reactive power considerations. DC microgrids remain a relatively new technology, and their network architectures, control strategies, and stabilization techniques require significant research efforts. In this context, this thesis focuses on energy management issues in a multi-source DC electrical grid dedicated to residential applications. The DC electrical grid consists of distributed generators (solar panels), a hybrid energy storage system (HESS) with batteries and a supercapacitor (SC), and DC loads interconnected via DC/DC power converters. The primary objective of this research is to develop an advanced energy management strategy (EMS) to enhance the operational efficiency of the system while improving its reliability and sustainability. A hierarchical simulation platform of the DC electrical grid has been developed using MATLAB/Simulink. It comprises two layers with different time scales: a local control layer (time scale of a few seconds to minutes due to converter switching behavior) for controlling local components, and a system-level control layer (time scale of a few days to months with accelerated testing) for long-term validation and performance evaluation of the EMS. In the local control layer, solar panels, batteries, and the supercapacitor have been modeled and controlled separately. Various control modes, such as current control, voltage control, and maximum power point tracking (MPPT), have been implemented. A low-pass filter (LPF) has been applied to divide the total HESS power into low and high frequencies for the batteries and supercapacitor. Different LPF cutoff frequencies for power sharing have also been studied. A combined hybrid bi-level EMS and automatic sizing have been proposed and validated. It mainly covers five operational scenarios, including solar panel production reduction, load reduction, and three scenarios involving HESS control combined with supercapacitor state of charge (SOC) control retention. An objective function that considers both capital expenditure (CAPEX) and operating costs (OPEX) has been designed for EMS performance evaluation. The interaction between the HESS and EMS has been jointly studied based on an open dataset of residential electrical consumption profiles covering both summer and winter seasons. Finally, an experimental platform of a multi-source DC electrical grid has been developed to validate the EMS in real-time. It comprises four lithium-ion batteries, a supercapacitor, a programmable DC power supply, a programmable DC load, corresponding DC/DC converters, and a real-time controller (dSPACE/Microlabbox). Accelerated tests have been conducted to verify the proposed EMS in different operational scenarios by integrating real solar panels and load consumption profiles. The hierarchical simulation and experimental DC electrical grid platforms can be generally used to verify and evaluate various EMS
Guitton, Julien. "Architecture hybride pour la planification d'actions et de déplacements". Phd thesis, Université Paul Sabatier - Toulouse III, 2010. http://tel.archives-ouvertes.fr/tel-00648244.
Lucien, Laurent. "Contribution à une modélisation globale de la collaboration dans les systèmes multi-agents : Application aux entités mobiles intelligentes". Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCD039/document.
We live today in an increasingly complex and interconnected world where many entities, increasingly intelligent, generate a multitude of interactions that can contribute to enrich their capabilities.We are interested in collaboration that will enable complex tasks to be performed by these machines of today and tomorrow by stimulating these structured interactions and integrating intelligent decision-making processes. In this way, it will contribute to improve their functioning and will be able to participate in their improvement (better knowledge of their environment, speed of action and decision-making, provision of new skills).The main objective of the thesis is therefore to contribute to the understanding of what collaboration is, from its definition to its implementation, by highlighting its underlying concepts. We propose a method of analysis (needs and constraints) and a collaborative agent architecture model (HACCA) to integrate all the characteristics of the collaborative processes that we present. We are also showing a first implementation in the GAMA multi-agent platform.As part of this study, we are interested in two cases of application of mobile entities: drones and connected vehicles.Thus we also contribute more to the autonomy needs and decision-making process of drones, connected and autonomous vehicles of the future, in a constrained temporal context where the quality of interactions is essential to optimize the process of achieving objectives
Osório, Fernando Santos. "Inss : un système hybride neuro-symbolique pour l'apprentissage automatique constructif". Grenoble INPG, 1998. https://tel.archives-ouvertes.fr/tel-00004899.
Various Artificial Intelligence methods have been developed to reproduce intelligent human behaviour. These methods allow to reproduce some human reasoning process using the available knowledge. Each method has its advantages, but also some drawbacks. Hybrid systems combine different approaches in order to take advantage of their respective strengths. These hybrid intelligent systems also present the ability to acquire new knowledge from different sources and so to improve their application performance. This thesis presents our research in the field of hybrid neuro-symbolic systems, and in particular the study of machine learning tools used for constructive knowledge acquisition. We are interested in the automatic acquisition of theoretical knowledge (rules) and empirical knowledge (examples). We present a new hybrid system we implemented: INSS - Incremental Neuro-Symbolic System. This system allows knowledge transfer from the symbolic module to the connectionist module (Artificial Neural Network - ANN), through symbolic rule compilation into an ANN. We can refine the initial ANN knowledge through neural learning using a set of examples. The incremental ANN learning method used, the Cascade-Correlation algorithm, allows us to change or to add new knowledge to the network. Then, the system can also extract modified (or new) symbolic rules from the ANN and validate them. INSS is a hybrid machine learning system that implements a constructive knowledge acquisition method. We conclude by showing the results we obtained with this system in different application domains: ANN artificial problems(The Monk's Problems), computer aided medical diagnosis (Toxic Comas), a cognitive modelling task (The Balance Scale Problem) and autonomous robot control. The results we obtained show the improved performance of INSS and its advantages over others hybrid neuro-symbolic systems
Singer, Benjamin. "L'intelligence artificielle au service du rugby : acquisition et modélisationd'une expertise visuelle de prise de décision tactique : construction d'un système expert hybride d'aide à l'intervention pour la formation des joueurs et des cadres techniques". Paris 10, 1995. http://www.theses.fr/1995PA100048.
We focus on our contribution at the visual knowledge acquisition and modelling levels. After justifying its necessity we propose a visual knowledge elicitation language whose formal definition is given via its static and dynamic component s. The second part of our contribution is related to the design and realization of a visual knowledge acquisition software tool driven by the previous language. The third part of our contribution deals with visual knowledge modelling at the methodological and tool levels by extending the initial method and software. The fourth part describes the whole case study carried out for modelling the visual expertise considered for tactical decision-making in rugby the complete conceptual model is built. Then we describe the design, implementation and validation of the final expert system on the target architecture. The conclusion points out the interests of our contribution both at the theoretical and practical levels, and the generality of the results achieved for team games study
Libri sul tema "Intelligence artificielle hybride":
Orlan. Orlanoïde robot hybride: Avec intelligence artificielle et collective : Orlanoide hybrid robot with artificial and collective intelligence. Paris: LienArt, 2018.
Nebel, Bernhard. Reasoning and revision in hybrid representation systems. Berlin: Springer-Verlag, 1990.
Rapporti di organizzazioni sul tema "Intelligence artificielle hybride":
Rousseau, Henri-Paul. Gutenberg, L’université et le défi numérique. CIRANO, dicembre 2022. http://dx.doi.org/10.54932/wodt6646.