AI-Based Services for Smart Cities and Urban Infrastructure / Lyu Kangjuan (2021)

Public ISBD Titre : AI-Based Services for Smart Cities and Urban Infrastructure Type de document : document électronique Auteurs : Lyu Kangjuan, Auteur ; Hu Min, Auteur ; Du Juan, Auteur ; Sugumaran Vijayan, Auteur Editeur : Engineering Science Reference. Année de publication : 2021 Importance : 1 fichier PDF ISBN/ISSN/EAN : 978-1-79985-025-0 Note générale : Mode d'accès : accès au texte intégral par : - authentification après inscription à la plateforme EBSCOhost ou - adresse IP de l'École. Langues : Anglais (eng) Mots-clés : City planning--Technological innovations Smart cities Urbanization Artificial intelligence--Engineering applications Index. décimale : 004.8 Intelligence artificielle Résumé : Cities are the next frontier for artificial intelligence to permeate. As smart urban environments become possible, probable, and even preferred, artificial intelligence offers the chance for even further advancement through infrastructure and industry boosting. Opportunity overflows, but without thorough research to guide a complicated development and implementation process, urban environments can become disorganized and outright dangerous for citizens. AI-Based Services for Smart Cities and Urban Infrastructure is a collection of innovative research that explores artificial intelligence (AI) applications in urban planning. In addition, the book looks at how the internet of things and AI can work together to enable a real smart city and discusses state-of-the-art techniques in urban infrastructure design, construction, operation, maintenance, and management. While highlighting a broad range of topics including construction management, public transportation, and smart agriculture, this book is ideally designed for engineers, entrepreneurs, urban planners, architects, policymakers, researchers, academicians, and students. Série Note de contenu : Summary : I.Fundamentals of Smart Cities 1.Definition and History of Smart Cities 2.The Development of Smart Cities in the World 3.Core Technology of Smart Cities 4.Interpretation of the Construction Standard of Smart City Standard Systems 5.Framework and Structure of Smart Cities II.Infrastructure and Engineering Construction of Smart Cities 6.Infrastructure and Industry Economy 7.Intelligent Engineering Construction Management: On-Site Construction Management 8.Intelligent Engineering Construction Management: Long-Distance Construction Management 9.Performance Evaluation on the Intelligent Operation and Maintenance Mode of Public-Private 10.Policy Recommendations on the Application of AI to the Development of Smart Cities 11.Smart City Service III.Application of AI for Smart City Services 12.Application of Fuzzy Analytic Hierarchy Process for Evaluation of Ankara-Izmir High-Speed Train Project. 13.Applications of Artificial Intelligence for Smart Agriculture 14.The Role of AI-Based Integrated Physical Security Governance for Optimizing IoT Devices Connectivity in Smart Cities 15.Smart Home Environment AI-Based Services for Smart Cities and Urban Infrastructure [document électronique] / Lyu Kangjuan, Auteur ; Hu Min, Auteur ; Du Juan, Auteur ; Sugumaran Vijayan, Auteur . - Engineering Science Reference., 2021 . - 1 fichier PDF. ISBN : 978-1-79985-025-0 Mode d'accès : accès au texte intégral par : - authentification après inscription à la plateforme EBSCOhost ou - adresse IP de l'École. Langues : Anglais (eng) Mots-clés : City planning--Technological innovations Smart cities Urbanization Artificial intelligence--Engineering applications Index. décimale : 004.8 Intelligence artificielle Résumé : Cities are the next frontier for artificial intelligence to permeate. As smart urban environments become possible, probable, and even preferred, artificial intelligence offers the chance for even further advancement through infrastructure and industry boosting. Opportunity overflows, but without thorough research to guide a complicated development and implementation process, urban environments can become disorganized and outright dangerous for citizens. AI-Based Services for Smart Cities and Urban Infrastructure is a collection of innovative research that explores artificial intelligence (AI) applications in urban planning. In addition, the book looks at how the internet of things and AI can work together to enable a real smart city and discusses state-of-the-art techniques in urban infrastructure design, construction, operation, maintenance, and management. While highlighting a broad range of topics including construction management, public transportation, and smart agriculture, this book is ideally designed for engineers, entrepreneurs, urban planners, architects, policymakers, researchers, academicians, and students. Série Note de contenu : Summary : I.Fundamentals of Smart Cities 1.Definition and History of Smart Cities 2.The Development of Smart Cities in the World 3.Core Technology of Smart Cities 4.Interpretation of the Construction Standard of Smart City Standard Systems 5.Framework and Structure of Smart Cities II.Infrastructure and Engineering Construction of Smart Cities 6.Infrastructure and Industry Economy 7.Intelligent Engineering Construction Management: On-Site Construction Management 8.Intelligent Engineering Construction Management: Long-Distance Construction Management 9.Performance Evaluation on the Intelligent Operation and Maintenance Mode of Public-Private 10.Policy Recommendations on the Application of AI to the Development of Smart Cities 11.Smart City Service III.Application of AI for Smart City Services 12.Application of Fuzzy Analytic Hierarchy Process for Evaluation of Ankara-Izmir High-Speed Train Project. 13.Applications of Artificial Intelligence for Smart Agriculture 14.The Role of AI-Based Integrated Physical Security Governance for Optimizing IoT Devices Connectivity in Smart Cities 15.Smart Home Environment

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Apprentissage artificiel / Antoine Cornuéjols (2018)

Public ISBD Titre : Apprentissage artificiel : deep learning, concepts et algorithmes Type de document : texte imprimé Auteurs : Antoine Cornuéjols, Auteur ; Laurent Miclet, Auteur ; Vincent Barra, Auteur Mention d'édition : 3ème éd Editeur : Paris : Eyrolles Année de publication : 2018 Collection : Algorithmes Importance : X, 899 p. Présentation : ill. Format : 23 cm ISBN/ISSN/EAN : 978-2-212-67522-1 Note générale : Bibliogr. p. [851]-889. - Index Langues : Français (fre) Mots-clés : Apprentissage automatique Intelligence artificielle Algorithmes Index. décimale : 004.8 Intelligence artificielle Résumé : Ce livre présente les concepts qui sous-tendent l'apprentissage artificiel, les algorithmes qui en découlent et certaines de leurs applications. Son objectif est de décrire un ensemble d'algorithmes utiles en tentant d'établir un cadre théorique pour l'ensemble des techniques regroupées sous ce terme "d'apprentissage artificiel". La troisième édition de ce livre a été complètement réorganisée pour s'adapter aux évolutions très significatives de l'apprentissage artificiel ces dernières années. Une large place y est accordée aux techniques d'apprentissage profond et à de nouvelles applications, incluant le traitement de flux de données. Note de contenu : Au sommaire : 1. Des machines apprenantes ! 2. L'induction exploitant la structure de l'espace des hypothèses. 3. L'induction par optimisation d'un critère inductif. 4. L'induction par comparaison à des exemples (et par collaboration). 5. L'apprentissage descriptif. 6. Apprentissage en environnement non stationnaire. 7. Aspects pratiques et suppléments. 8. Annexes techniques Apprentissage artificiel : deep learning, concepts et algorithmes [texte imprimé] / Antoine Cornuéjols, Auteur ; Laurent Miclet, Auteur ; Vincent Barra, Auteur  . -  3ème éd . - Paris : Eyrolles, 2018 . - X, 899 p. : ill. ; 23 cm. - (Algorithmes) . ISBN : 978-2-212-67522-1 Bibliogr. p. [851]-889. - Index Langues : Français (fre) Mots-clés : Apprentissage automatique Intelligence artificielle Algorithmes Index. décimale : 004.8 Intelligence artificielle Résumé : Ce livre présente les concepts qui sous-tendent l'apprentissage artificiel, les algorithmes qui en découlent et certaines de leurs applications. Son objectif est de décrire un ensemble d'algorithmes utiles en tentant d'établir un cadre théorique pour l'ensemble des techniques regroupées sous ce terme "d'apprentissage artificiel". La troisième édition de ce livre a été complètement réorganisée pour s'adapter aux évolutions très significatives de l'apprentissage artificiel ces dernières années. Une large place y est accordée aux techniques d'apprentissage profond et à de nouvelles applications, incluant le traitement de flux de données. Note de contenu : Au sommaire : 1. Des machines apprenantes ! 2. L'induction exploitant la structure de l'espace des hypothèses. 3. L'induction par optimisation d'un critère inductif. 4. L'induction par comparaison à des exemples (et par collaboration). 5. L'apprentissage descriptif. 6. Apprentissage en environnement non stationnaire. 7. Aspects pratiques et suppléments. 8. Annexes techniques

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Artificial intelligence and quantum computing for advanced wireless networks / Savo G. Glisic (2022)

Public ISBD Titre : Artificial intelligence and quantum computing for advanced wireless networks Type de document : texte imprimé Auteurs : Savo G. Glisic, Auteur ; Beatriz Lorenzo, Auteur Editeur : New York : John Wiley and Sons Année de publication : 2022 Importance : XIII, 850 p. Présentation : ill. Format : 27 cm ISBN/ISSN/EAN : 978-1-119-79029-7 Note générale : Références bibliogr. en fin de chapitres. - Index Langues : Anglais (eng) Mots-clés : Artificial intelligence Quantum computing Wireless communication systems Intelligence artificielle Informatique quantique Transmission sans fil Index. décimale : 004.8 Intelligence artificielle Résumé : "By increasing the density and number of different functionalities in wireless networks there is more and more need for the use of artificial intelligence for planning network deployment, running their optimization and dynamically controlling their operation. For example, machine learning algorithms are used for the prediction of traffic and network state in order to timely reserve resources for smooth communication with high reliability and low latency; Big data mining is used to predict customer behaviour and pre-distribute the information content across the network so that it can be efficiently delivered as soon as requested; Intelligent agents can search the internet on behalf of the customer in order to find the best options when it comes to buying any product online. This timely book presents a review of AI-based learning algorithms with a number of case studies supported by Python and R programs, providing a discussion of the learning algorithms used in decision making based on game theory and a number of specific applications in wireless networks, such as channel, network state and traffic prediction. It is expected that once quantum computing becomes a commercial reality, it will be used in wireless communications systems in order to speed up specific processes due to its inherent parallelization capabilities. This is a practical book packed with case studies and follows a basic through to advanced level path and is an ideal course accompaniment for graduate/masters students, and online professional study." Note de contenu : Summary : Part I Artificial Intelligence 1. Introduction 2. Machine Learning Algorithms 3. Artificial Neural Networks 4. Explainable Neural Networks 5. Graph Neural Networks 6. Learning Equilibria and Games 7. AI Algorithms in Networks Part II Quantum Computing 8. Fundamentals of Quantum Communications 9. Quantum Channel Information Theory 10. Quantum Error Correction 11. Quantum Search Algorithms 12. Quantum Machine Learning 13. QC Optimization 14. Quantum Decision Theory 15. Quantum Computing in Wireless Networks 16. Quantum Network on Graph 17. Quantum Internet Artificial intelligence and quantum computing for advanced wireless networks [texte imprimé] / Savo G. Glisic, Auteur ; Beatriz Lorenzo, Auteur . - New York : John Wiley and Sons, 2022 . - XIII, 850 p. : ill. ; 27 cm. ISBN : 978-1-119-79029-7 Références bibliogr. en fin de chapitres. - Index Langues : Anglais (eng) Mots-clés : Artificial intelligence Quantum computing Wireless communication systems Intelligence artificielle Informatique quantique Transmission sans fil Index. décimale : 004.8 Intelligence artificielle Résumé : "By increasing the density and number of different functionalities in wireless networks there is more and more need for the use of artificial intelligence for planning network deployment, running their optimization and dynamically controlling their operation. For example, machine learning algorithms are used for the prediction of traffic and network state in order to timely reserve resources for smooth communication with high reliability and low latency; Big data mining is used to predict customer behaviour and pre-distribute the information content across the network so that it can be efficiently delivered as soon as requested; Intelligent agents can search the internet on behalf of the customer in order to find the best options when it comes to buying any product online. This timely book presents a review of AI-based learning algorithms with a number of case studies supported by Python and R programs, providing a discussion of the learning algorithms used in decision making based on game theory and a number of specific applications in wireless networks, such as channel, network state and traffic prediction. It is expected that once quantum computing becomes a commercial reality, it will be used in wireless communications systems in order to speed up specific processes due to its inherent parallelization capabilities. This is a practical book packed with case studies and follows a basic through to advanced level path and is an ideal course accompaniment for graduate/masters students, and online professional study." Note de contenu : Summary : Part I Artificial Intelligence 1. Introduction 2. Machine Learning Algorithms 3. Artificial Neural Networks 4. Explainable Neural Networks 5. Graph Neural Networks 6. Learning Equilibria and Games 7. AI Algorithms in Networks Part II Quantum Computing 8. Fundamentals of Quantum Communications 9. Quantum Channel Information Theory 10. Quantum Error Correction 11. Quantum Search Algorithms 12. Quantum Machine Learning 13. QC Optimization 14. Quantum Decision Theory 15. Quantum Computing in Wireless Networks 16. Quantum Network on Graph 17. Quantum Internet

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Artificial intelligence by example / Denis Rothman (2020)

Public ISBD Titre : Artificial intelligence by example : acquire advanced AI, machine learning, and deep learning design skills Type de document : texte imprimé Auteurs : Denis Rothman, Auteur Mention d'édition : 2nd ed Editeur : Birmingham : Packt Publishing Année de publication : 2020 Importance : XXI, 549 p. Présentation : ill. Format : 24 cm ISBN/ISSN/EAN : 978-1-83921-153-9 Langues : Anglais (eng) Mots-clés : Artificial intelligence Machine learning Index. décimale : 004.8 Intelligence artificielle Résumé : This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions. Note de contenu : Summary : 1. Getting started with next-generation artificial intelligence through reinforcement learning. 2. Building a reward matrix designing your datasets. 3. Machine intelligence evaluation functions and numerical convergence. 4. Optimizing your solutions with k-means clustering. 5. How to use decision trees to enhance k-means clustering. 6. Innovating ai with google translate. 7. Optimizing blockchains with naive bayes. 8. Solving the xor problem with a fnn. 9. Abstract image classification with cnn. 10. Conceptual representation learning. 11. Combining rl and dl. 12. Ai and the iot. 13. Visualizing networks with tensorflow 2.x and tensorboard. 14. Preparing the input of chatbots with rbms and pca. 15. Setting up a cognitive nlp ui/cui chatbot 16. Improving the emotional intelligence. deficiencies of chatbots. 17. Genetic algorithms in hybrid neural networks. 18. Neuromorphic computing. 19. Quantum computing Artificial intelligence by example : acquire advanced AI, machine learning, and deep learning design skills [texte imprimé] / Denis Rothman, Auteur  . -  2nd ed . - Birmingham : Packt Publishing, 2020 . - XXI, 549 p. : ill. ; 24 cm. ISBN : 978-1-83921-153-9 Langues : Anglais (eng) Mots-clés : Artificial intelligence Machine learning Index. décimale : 004.8 Intelligence artificielle Résumé : This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions. Note de contenu : Summary : 1. Getting started with next-generation artificial intelligence through reinforcement learning. 2. Building a reward matrix designing your datasets. 3. Machine intelligence evaluation functions and numerical convergence. 4. Optimizing your solutions with k-means clustering. 5. How to use decision trees to enhance k-means clustering. 6. Innovating ai with google translate. 7. Optimizing blockchains with naive bayes. 8. Solving the xor problem with a fnn. 9. Abstract image classification with cnn. 10. Conceptual representation learning. 11. Combining rl and dl. 12. Ai and the iot. 13. Visualizing networks with tensorflow 2.x and tensorboard. 14. Preparing the input of chatbots with rbms and pca. 15. Setting up a cognitive nlp ui/cui chatbot 16. Improving the emotional intelligence. deficiencies of chatbots. 17. Genetic algorithms in hybrid neural networks. 18. Neuromorphic computing. 19. Quantum computing

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Computational intelligence / Nazmul Siddique ; Hojjat Adeli (2013)

Public ISBD Titre : Computational intelligence : synergies of fuzzy logic, neural networks, and evolutionary computing Type de document : texte imprimé Auteurs : Nazmul Siddique, Auteur ; Hojjat Adeli, Auteur Editeur : New York : John Wiley & Sons Année de publication : 2013 Importance : XVII, 512 p. Présentation : ill. Format : 25 cm. ISBN/ISSN/EAN : 978-1-118-33784-4 Note générale : Annexe. - Index Langues : Anglais (eng) Mots-clés : Computational intelligence Computers -- Enterprise Applications -- Business Intelligence Tools Computers -- Intelligence (AI) & Semantics Index. décimale : 004.8 Intelligence artificielle Résumé : This book presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Note de contenu : Summary : 1. Introduction to computational intelligence 2. Introduction to fuzzy logic 3. Fuzzy systems and applications 4. Neural networks 5. Neural systems and applications ... Computational intelligence : synergies of fuzzy logic, neural networks, and evolutionary computing [texte imprimé] / Nazmul Siddique, Auteur ; Hojjat Adeli, Auteur . - New York : John Wiley & Sons, 2013 . - XVII, 512 p. : ill. ; 25 cm. ISBN : 978-1-118-33784-4 Annexe. - Index Langues : Anglais (eng) Mots-clés : Computational intelligence Computers -- Enterprise Applications -- Business Intelligence Tools Computers -- Intelligence (AI) & Semantics Index. décimale : 004.8 Intelligence artificielle Résumé : This book presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Note de contenu : Summary : 1. Introduction to computational intelligence 2. Introduction to fuzzy logic 3. Fuzzy systems and applications 4. Neural networks 5. Neural systems and applications ...

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Convergence (2022)

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Deep learning with TensorFlow 2 and Keras / Antonio Gulli (2019)

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Engineering intelligent systems / Barclay R. Brown (2023)

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Guide pratique de l'intelligence artificielle dans l'entreprise / Stéphane Roder (2019)

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Hands-on machine learning with Scikit-Learn, Keras and TensorFlow / Aurélien Géron (2019)

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Intelligence artificielle / Tristan Cazenave (2011)

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Intelligence artificielle avec AWS / Marc (19..-.... ; ingénieur) Israël (2019)

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Intelligence artificielle / Stuart (1962-....) Russell (2010)

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L'intelligence artificielle par la pratique / Faltings, Boi (2009)

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