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1. |
Record Nr. |
UNINA9911057015703321 |
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Autore |
Pedrycz Witold |
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Titolo |
Advances in Information, Computing and Technology : Proceedings of the International Conference on Information, Computing and Technology (ICICT2025), Volume 2 / / edited by Witold Pedrycz, John Wang, Jianqi Li |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026 |
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ISBN |
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Edizione |
[1st ed. 2026.] |
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Descrizione fisica |
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1 online resource (686 pages) |
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Collana |
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Lecture Notes in Networks and Systems, , 2367-3389 ; ; 1735 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Computational intelligence |
Artificial intelligence |
Engineering - Data processing |
Computational Intelligence |
Artificial Intelligence |
Data Engineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Prediction and Analysis of the Trend of Economic Management Strategy of Tourism Industry by Neural Network Model -- Research on the Application of Big Data-Driven Multi-Agent Reinforcement Learning in Autonomous Driving Traffic Control -- Low-Carbon Green Indicator System for Transportation Logistics and Energy Efficiency Optimization Methods. |
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Sommario/riassunto |
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This book delivers a practical, forward-looking guide to cutting-edge developments at the intersection of information science, computing, and technology, equipping readers to bridge theoretical advancements with real-world application. By prioritizing actionable insights over abstract theory, it addresses the gap between rapid tech evolution and the need for accessible, applicable knowledge for professionals and learners alike. Rather than organizing content by traditional subdisciplines, this book adopts an interdisciplinary, problem-centric approach This novelty ensures readers grasp how technologies interact to solve complex challenges, a perspective often missing in more siloed |
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texts. Intended for a broad audience, it serves as a go-to resource for tech professionals seeking to update their skills, upper-level undergraduate/graduate students in related fields, and researchers needing a concise overview of cross-domain progress. |
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