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All issues Volume 412 (2023) E3S Web Conf., 412 (2023) 01072 References
Open Access
Issue
E3S Web Conf.
Volume 412, 2023
International Conference on Innovation in Modern Applied Science, Environment, Energy and Earth Studies (ICIES’11 2023)
Article Number 01072
Number of page(s) 19
DOI https://doi.org/10.1051/e3sconf/202341201072
Published online 17 August 2023
  1. M. van Assen, S. J. Lee, C. N. De Cecco, Artificial intelligence from A to Z: From neural network to legal framework, European Journal of Radiology, Volume 129, (2022) [Google Scholar]
  2. S. Russell, P. Norvig, Artificial Intelligence: a Modern Approach, (third ed.), Prentice Hall Press, Upper Saddle River, NJ, USA (2009) [Google Scholar]
  3. Z. Ghahramani, Probabilistic machine learning and artificial intelligence, Nature, 521 (7553) (2015) [Google Scholar]
  4. European-Commission, White Paper on Artificial Intelligence, (2023) [Google Scholar]
  5. D. Hernandez, D. Amodei, S. Girish, et al., OpenAI.Org AI Comput. (2019) [Google Scholar]
  6. Knapik, M., Johnson, J., Developing Inteligent Agents for Distributed Systems. Computing McGraw-Hill, NY:McGraw-Hill, (1998) [Google Scholar]
  7. Brownlee J, Deep Learning for Natural Language Processing, Available at:https://cutt.ly/EbjQujj, OCTOBER 17, (2022) [Google Scholar]
  8. A. Kao, S. Poteet, Text Mining and Natural Language Processing-Introduction for the Special issue, SIGKDD Exploration 7 (1) (2005) 1. [CrossRef] [Google Scholar]
  9. D. M. Bikel, I. Zitouni, Multilingual Natural Language Processing Applications, Edited by IBM Press Pearson Upper Saddle River, ibmpressbooks.com ISBN-13: 978-0-13715144-8, May (2012) [Google Scholar]
  10. S. Bird, E. Klein, E. Loper, Natural Language Processing with Python, Analyzing Text with the Natural Language Toolkit, June (2009):O’reilly publication ISBN: 978-0-59651649-9 [Google Scholar]
  11. T. Miwa, R. Minoda, R. Yamaguchi, S. I. Kita, K. Osaka, H. Takeda, S. I. Kanemaru, K. Omori, Application of artificial intelligence using a convolutional neural network for detecting cholesteatoma in endoscopic enhanced images, Auris Nasus Larynx, (2022) [Google Scholar]
  12. Kassou, M., Bourekkadi, et al. (2021). Blockchain-based medical and water waste management conception. E3S Web of Conferences, 2021, 234, 00070 [CrossRef] [EDP Sciences] [Google Scholar]
  13. El Imrani, O. et al (2022). The consumer price index and it effect in the new ecosystems and energy consumption during the sanitary confinement: The case of an emerging country. IOP Conference Series: Earth and Environmental Science, 975(1), 012006 [CrossRef] [Google Scholar]
  14. Kahraman C., Öztaysi B., Çevik Onar S. A comprehensive literature review of 50 years of fuzzy set theory, Int. J. Comput. Intell. Syst., 9 (1) (2016) [CrossRef] [Google Scholar]
  15. Zadeh, Fuzzy sets, Inf. Control, 8 (1965) [Google Scholar]
  16. Bustince H., Barrenechea E., Pagola M., Fernandez J., Xu Z., Bedregal B., Montero J., Hagras H., Herrera F., De Baets, A historical account of types of fuzzy sets and their relationships, IEEE Trans. Fuzzy Syst., 24 (1) (2016) [Google Scholar]
  17. Hühn J., Hüllermeier E. FURIA: An algorithm for unordered fuzzy rule induction, Data Min. Knowl. Discov., 19 (3) (2009) [Google Scholar]
  18. Bing L., Chan K., A fuzzy logic approach for opinion mining on large scale Twitter data 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing, International Conference on Utility and Cloud Computing (2014) [Google Scholar]
  19. Han Y., Zhao S., Multi-scale clustering algorithm, Comput. Sci., 43 (2016) [Google Scholar]
  20. Homem T.P.D., Santos P.E., Costa A.H.R., Bianchi R.A.D.C., Mantaras R.L.D. Qualitative case-based reasoning and learning Artif. Intell., 283 (2020), Article 103258.1–103258.23 [Google Scholar]
  21. Aamodt and Plaza, 1994, A. Aamodt, E. Plaza, Case-based reasoning: Foundational issues, methodological variations, and system approaches, AI Communications, 7 (1) (1994) [Google Scholar]
  22. Li C., Wang R. (2012) The Research and Application of Case-Based Reasoning in Fixture Design. In: Luo J. (eds) Soft Computing in Information Communication Technology. Advances in Intelligent and Soft Computing, vol 158. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29148-7_46 [Google Scholar]
  23. Y. Bengio, A. Courville, “Apprentissage en profondeur”, (2016) (Y. Bengio, 2016) [Google Scholar]
  24. M. Nielsen, “Réseaux de neurones et apprentissage profond”,(2015) (M. Nielsen, 2015) [Google Scholar]
  25. A. Géron, « Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow », (2019) (A. Géron, 2019) [Google Scholar]
  26. K. Suzuki, “Réseaux de neurones artificiels Architectures et applications”, (2018) (K. Suzuki, 2018) [Google Scholar]
  27. Imrani, O.E. et al., Impact of industrial free zones on the business environment of emerging countries, cta Logistica, 2023, 10(1), pp. 105–110 [CrossRef] [Google Scholar]
  28. J. Yen and R. Langari, “Fuzzy Logic: Intelligence, Control, and Information”, (2019) [Google Scholar]
  29. T. Ross, “Fuzzy Logic with Engineering Applications”, (2022) [Google Scholar]
  30. H. Prade and A. Skowron, “An Introduction to Fuzzy Logic Applications in Intelligent Systems”, (2016) [Google Scholar]
  31. D. Toshniwaland V. P. Singh, “Fuzzy Logic in Environmental Sciences: Theory, Applications and Future Research Directions”, (2018) [Google Scholar]
  32. D. Wu and J. M. Mendel, “Fuzzy Logic for Planning and Decision Making”,(2021) [Google Scholar]
  33. M. Richter and R. O. Weber, “Case-Based Reasoning: A Textbook”, (2016) [Google Scholar]
  34. A. Aamodt and E. Plaza, “Case-Based Reasoning Research and Development”,(2015) [Google Scholar]
  35. J. L. Kolodner and D. H. Leake, “Case-Based Reasoning: Experiences, Lessons, and Future Directions”, (2016) [Google Scholar]
  36. S. Li and S. Liang “Case-Based Reasoning in Environmental Decision Making”, (2015) [Google Scholar]
  37. A. L. Rector and A. W. A. Boxwala, “Case-Based Reasoning in the Health Sciences”, (2021) (A. L. Rector and A. W. A. Boxwala, 2021) [Google Scholar]
  38. Y. Shoham and K. Leyton-Brown, “Multi-agent systems: A survey”, (2018) [Google Scholar]
  39. M. Wooldridge, “An Introduction to MultiAgentSystems”, (2019) [Google Scholar]
  40. Y. Shoham and K. Leyton-Brown “Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations”, (2021) [Google Scholar]
  41. M. Wooldridge and N. Jennings, “Engineering Societies in the Agents World”, (2017) [Google Scholar]
  42. D. Weyns and T. Holvoet, “Introducing Multiagent Systems”, (2022) [Google Scholar]
  43. D. Jurafsky and J. H. Martin, “Speech and language processing (3rded.)”, (2019) [Google Scholar]
  44. C. D. Manning and D. Jurafsky, “Foundations of statistical natural language processing”, (2018) [Google Scholar]
  45. S. Bird, E. Klein and E. Loper, “Natural language processing with Python: analyzing text with the natural language toolkit”, (2019) [Google Scholar]
  46. F. Chollet, “Deep learning with Python”,(2018) [Google Scholar]
  47. Y. Goldberg, “Neural network methods for natural language processing (Vol. 1)”, (2017) [CrossRef] [Google Scholar]
  48. C. DManning, “Introduction to Linguistics and Natural Language Processing”, (2020) [Google Scholar]

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