Buch, Englisch, 404 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 703 g
Proceedings of the 16th International Conference on Autonomous Systems
Buch, Englisch, 404 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 703 g
Reihe: Lecture Notes in Networks and Systems
ISBN: 978-3-031-98696-3
Verlag: Springer
This book serves as both a cutting-edge reference and a practical guide to building AI systems that are transparent, trustworthy, and tuned for real-world impact, featuring contributors from three continents and backed by leading institutions.
Unlock the next wave of graph-based artificial intelligence, fuzzy logic, and human-centric machine learning with this authoritative Springer proceedings book. Twenty-four rigorously peer-reviewed chapters—spanning semantic similarity in Wikipedia, sparse distributed representations, explainable image generation, privacy-preserving mobility analytics, sentiment mining in public transport, counterfeit-banknote detection, 5G network capacity planning, and mixed-order traffic prediction—provide a panoramic view of state-of-the-art research that turns theory into deployable solutions.
Readers gain step-by-step methodologies for building restricted Boltzmann machines enhanced with fuzziness, dual-graph semantic extractors, Bloom-filter variants, and the versatile GraphLearner simulator. Each contribution includes reproducible workflows, comparative baselines, and publicly available code or datasets—accelerating adoption in academia and industry alike.
Highlights include a blueprint for emotion-aware AI agents, a cloud-intelligence framework that empowers SMEs with decision support, and an adaptive metric for privacy-preserving urban-mobility sharing that balances usability and anonymity.
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Research
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Weitere Infos & Material
The importance of being fuzzy.- Artificial emotion: The research on making machines more human-like.- Construction and comparison of linkage-graph-based representations with co-occurrence graphs and word2Vec embeddings: A case study on English Wikipedia articles - Efficient generation of sparse distributed representations (SDRS) with singular value decomposition (SVD).- Word embedding through a spring-force system.- Dual graph representation for semantic extraction.- Academic paper recommendation using co-occurrence graphs.- Sentiment analysis in public transport: A comparative study of machine learning and deep learning models.- The GraphLearner as a high order Markov chain simulator.- Edge decisions and N-Gram midpoints with the GraphLearner.- Empirical comparison of different bloom filter variants.- Learn, predict and generate note sequences.- Empowering non-experts with interactive graph visualization in generative AI: The case of GraphLearner.- The psychological background of the emotional machine.- Designing an emotion-based motivation model for adaptive AI agents.- Personalised cloud-intelligence: AI-driven decision making for small businesses.- Mixed-order spatio-temporal representation learning for traffic prediction.- The role of entropy-based features in classifying tor traffic using machine learning.- An adaptive metric-based method for privacy-preserving sharing of anonymized urban mobility data.- Explainable prompt-based image generation: developing transparent generative models.- Enhancing mobile network capacity planning with emerging technologies: A system dynamics and machine learning-based approach.- Counterfeit Thai banknote detection using deep learning.- StepIn: A context-aware decentralized social networking system.- Conceptual design of intelligent services in decentralized social networks.- Enhancing web crawling efficiency with adaptive scheduling algorithms and chatgpt integration.




