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Titre : Fuzzy logic Type de document : Monographie Auteurs : Constantin Volosencu, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 Importance : 188 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-1-83968-540-8 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] Inférence floue
[Termes IGN] logique floue
[Termes IGN] réseau neuronal artificiel
[Termes IGN] système expertRésumé : (éditeur) This book promotes new research results in the field of advanced fuzzy logic applications. The book has eight chapters, with the following thematic areas: fuzzy mathematics, adaptive neuro-fuzzy inference system, inference methods, expert systems, electrical systems, and application in management and field-programmable gate array. The introductory chapter aims to recall some algebraic relations that describe fuzzy rule bases and fuzzy blocks as algebraic applications. Other works presented are: a study on the convergence of sequence spaces with respect to intuitionistic fuzzy norms and their topological and algebraic properties; an ANFIS application to identifying the online bearing fault; methods of conditional inference for fuzzy control systems; an application of fuzzy logic and fuzzy expert systems in material synthesis methods; control of electrical systems in conditions of incomplete information regarding the values of diagnostic parameters; a methodology for evaluating the causality of factors in organization management; and a technical study on the functional safety of an FPGA fuzzy logic controller. The authors have published worked examples and case studies resulting from their research in the field. Readers will have access to new solutions and answers to questions related to the emerging field of theoretical fuzzy logic applications and their implementation. Note de contenu : 1- Introductory chapter: Basic properties of fuzzy relations
2- Some topological properties of intuitionistic fuzzy normed spaces
3- ANFIS: Establishing and applying to managing online damage
4- Some methods of fuzzy conditional inference for application to fuzzy control systems
5- Fuzzy logic and fuzzy expert system-based material synthesis
6- Determination of optimal transformation ratios of power system transformers in conditions of incomplete
information regarding the values of diagnostic parameter
7- The fuzzy logic methodology for evaluating the causality of factors in organization management
8- Functional safety of FPGA fuzzy logic controllerNuméro de notice : 28488 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.77460 En ligne : https://doi.org/10.5772/intechopen.77460 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99189
Titre : Geographic Information Systems in geospatial intelligence Type de document : Monographie Auteurs : Rustam B. Rustamov, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 Importance : 190 p. ISBN/ISSN/EAN : 978-1-83880-505-0 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] Airborne Data Acquisition and Registration
[Termes IGN] apprentissage automatique
[Termes IGN] base de données localisées
[Termes IGN] détection automatique
[Termes IGN] détection d'objet
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] Global Positioning System
[Termes IGN] image hyperspectrale
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] route
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du solRésumé : (Editeur) Earth observation systems, by use of space science and technology advances, present a large-scale opportunity for applying remote sensing methods with geographical information system (GIS) developments. Integrating these two methods makes it possible to achieve high-accuracy satellite data processing. This book considers aspects of GIS technology applications with space science technology and innovation approaches. It examines the potential of Earth observation satellite systems as well as existing challenges and problems in the field. Chapters cover topics such as RGB-D sensors for autonomous pothole detection, machine learning in GIS, interferometric synthetic aperture radar (InSAR) modeling, and others. Note de contenu : Chapter 1 - InSAR modeling of geophysics measurements
Chapter 2 - Expanding navigation systems by integrating it with advanced technologies
Chapter 3 - A review of the machine learning in GIS for megacities application
Chapter 4 - Study of equatorial plasma bubbles using ASI and GPS systems
Chapter 5 - Spectral optimization of airborne multispectral camera for land cover classification: automatic feature selection and spectral band clustering
Chapter 6 - Clustering techniques for land use land cover classification of remotely sensed images
Chapter 7 - Building an integrated database of road design elements
Chapter 8 - On the use of low-cost RGB-D sensors for autonomous pothole detection with spatial fuzzy c-means segmentationNuméro de notice : 26559 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.84925 En ligne : http://doi.org/10.5772/intechopen.84925 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98242
Titre : Introduction to data science and machine learning Type de document : Monographie Auteurs : Keshav Sud, Éditeur scientifique ; Pakize Erdogmus, Éditeur scientifique ; Seifedine Kadry, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 Importance : 236 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-1-83880-371-1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage automatique
[Termes IGN] classification par nuées dynamiques
[Termes IGN] langage à objets
[Termes IGN] logique floue
[Termes IGN] métadonnées
[Termes IGN] optimisation (mathématiques)
[Termes IGN] Python (langage de programmation)
[Termes IGN] segmentation d'imageRésumé : (éditeur) “Introduction to Data Science and Machine Learning” has been created with the goal to provide beginners seeking to learn about data science, data enthusiasts, and experienced data professionals with a deep understanding of data science application development using open-source programming from start to finish. This book is divided into four sections: the first section contains an introduction to the book, the second covers the field of data science, software development, and open-source based embedded hardware; the third section covers algorithms that are the decision engines for data science applications; and the final section brings together the concepts shared in the first three sections and provides several examples of data science applications. Note de contenu : 1- Introductory chapter: clustering with nature-inspired optimization algorithms
2- Best practices in accelerating the data science process in python
3- Software design for success
4- Embedded systems based on open source platforms
5- The K-means algorithm evolution
6- “Set of strings” framework for big data modeling
7- Investigation of fuzzy inductive modeling method in forecasting problems
8- Segmenting images using hybridization of K-means and fuzzy C-means algorithms
9- The software to the soft target assessment
10- The methodological standard to the assessment of the traffic simulation in real time
11- Augmented post systems: Syntax, semantics, and applications
12- Serialization in object-oriented programming languagesNuméro de notice : 28388 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.77469 En ligne : https://doi.org/10.5772/intechopen.77469 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98687
Titre : Mixed Reality and Three-Dimensional Computer Graphics Type de document : Monographie Auteurs : Branislav Sobota, Éditeur scientifique ; Dragan Cvetković, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 Importance : 180 p. Format : 17 x 23 cm ISBN/ISSN/EAN : 978-1-83962-624-1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Informatique
[Termes IGN] infographie
[Termes IGN] modélisation 3D
[Termes IGN] réalité augmentée
[Termes IGN] réalité mixte
[Termes IGN] réalité virtuelle
[Termes IGN] reconstruction 3D
[Termes IGN] stéréoscopieRésumé : (éditeur) Mixed reality is an area of computer research that deals with the combination of real-world and computer-generated data, where computer-generated objects are visually mixed into the real environment and vice versa in real time. It is the newest virtual reality technology. It usually uses 3D computer graphics technologies for visual presentation of the virtual world. The mixed reality can be created using the following technologies: augmented reality and augmented virtuality. Mixed and virtual reality, their applications, 3D computer graphics and related technologies in their actual stage are the content of this book. 3D-modeling in virtual reality, a stereoscopy, and 3D solids reconstruction are presented in the first part. The second part contains examples of the applications of these technologies, in industrial, medical, and educational areas. Note de contenu : 1- Using augmented reality technology to construct a wood furniture sampling platform for designers and sample makers to narrow the gap between judgment and prototype
2- Augmented reality as a new and innovative learning platform for the medical area
3- An interactive VR system for anatomy training
4- Learning by augmented reality: Cluster analysis approach
5- 3D modeling and computer graphics in virtual reality
6- 3D solid reconstruction from 2D orthographic views
7- Blockchain-based data integrity for collaborative CAD
8- Mixed reality in the presentation of industrial heritage development
9- Stereoscopy and autostereoscopy
10- Mixed reality: A known unknownNuméro de notice : 28330 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.77405 En ligne : https://www.intechopen.com/books/7603 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98417
Titre : Multi-agent systems : Strategies and applications Type de document : Monographie Auteurs : Ricardo Lopez-Ruiz, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2020 Importance : 170 p. Format : 19 x 27 cm ISBN/ISSN/EAN : 978-1-78985-394-0 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage par renforcement
[Termes IGN] reconstruction 3D
[Termes IGN] reconstruction d'image
[Termes IGN] réseau neuronal artificiel
[Termes IGN] système multi-agentsRésumé : (éditeur) Research on multi-agent systems is enlarging our future technical capabilities as humans and as an intelligent society. During recent years many effective applications have been implemented and are part of our daily life. These applications have agent-based models and methods as an important ingredient. Markets, finance world, robotics, medical technology, social negotiation, video games, big-data science, etc. are some of the branches where the knowledge gained through multi-agent simulations is necessary and where new software engineering tools are continuously created and tested in order to reach an effective technology transfer to impact our lives. This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. We hope that this book can be useful and become a guide or reference to an audience interested in the developments and applications of multi-agent systems. Note de contenu : 1- Cooperative adaptive learning control for a group of nonholonomic UGVs by output feedback
2- Multiagent systems for 3D reconstruction applications
3- A Q-learning-based approach for simple and multi-agent systems
4- Multi-Agent systems, simulation and nanotechnology
5- Applications of multi-agent system in power system engineering
6- Architecture of a microgrid and optimal energy management system
7- Multi-agent systems based advanced energy management of smart micro-grid
8- Smart learning environment: Paradigm shift for onlint learning
9- ICT: Vehicle for educational development and social TransformationNuméro de notice : 28572 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.81766 Date de publication en ligne : 22/04/2020 En ligne : https://doi.org/10.5772/intechopen.81766 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97871 PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkGeographic Information Systems in Geospatial Intelligence, ch. 5. Spectral optimization of airborne multispectral camera for land cover classification: automatic feature selection and spectral band clustering / Arnaud Le Bris (2019)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkUnderstanding of atmospheric systems with efficient numerical methods for observation and prediction / Lei-Ming Ma (2019)PermalinkPermalink