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World Conference of AI-Powered Innovation and Inventive Design 24th IFIP WG 5.4 International TRIZ Future Conference, TFC 2024, Cluj-Napoca, Romania, November 6–8, 2024, Proceedings, Part I /

This book constitutes the proceedings of the 24th IFIP WG 5.4 International TRIZ Future Conference on AI-Powered Innovation and Inventive Design, TFC 2024, held in Cluj-Napoca, Romania, during November 6–8, 2024. The 42 full papers presented were carefully reviewed and selected from 72 submissions....

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Dades bibliogràfiques
Autor corporatiu: SpringerLink (Online service)
Altres autors: Cavallucci, Denis (Editor), Brad, Stelian (Editor), Livotov, Pavel (Editor)
Format: Electrònic eBook
Idioma:anglès
Publicat: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edició:1st ed. 2025.
Col·lecció:IFIP Advances in Information and Communication Technology, 735
Matèries:
Artificial intelligence.
Computers.
Coding theory.
Information theory.
Database management.
Computer science > Mathematics.
Information storage and retrieval systems.
Artificial Intelligence.
Computing Milieux.
Coding and Information Theory.
Database Management.
Mathematics of Computing.
Information Storage and Retrieval.
Accés en línia:https://doi.org/10.1007/978-3-031-75919-2
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Taula de continguts:
  • -- AI-Driven TRIZ and Innovation.
  • LLM-based Extraction of Contradictions from Patents.
  • AI based search engine to deploy a TRIZ pointer to chemical effects.
  • Integrating Generative AI with TRIZ for Evolutionary Product Design. . Harnessing Generative AI for Sustainable Innovation: A Comparative Study of Prompting Techniques and Integration with Nature-Inspired Principles.
  • Neuro-Symbolic AI-Driven Inventive Design of a Benzoic Acid Extraction Installation from Styrax Resin.
  • Enhancing TRIZ Contradiction Resolution with AI-driven Contradiction Navigator (AICON).
  • Research on disruptive technology prediction methods based on BERT model and graph theory analysis.
  • Exploring Cross-Domain Technological Opportunities through Customized Training of the Bert Model.
  • Resource Mining Method of Idealization Driven Product Innovation Process of AI-Aided.
  • Use of AI in the TRIZ innovation process: a TESE-based forecast.
  • Evaluating the effectiveness of generative AI in TRIZ: A comparative case study.
  • On opportunities and challenges of large language models and GPT for problem solving and TRIZ education.
  • Challenges in Inventive Design Problem Solving with Generative AI: Interactive Problem Definition, Multi-Directional Prompting, and Concept Development.
  • The Evolving Landscape of TRIZ: A Generative AI-Powered Perspective.

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