La inteligencia artificial y sus aplicaciones en ciencias e ingenierías
DOI:
https://doi.org/10.19136/jeeos.a9n2.6423Keywords:
Inteligencia artificial, redes neuronales artificiales, ciencias e ingenierías.Abstract
El término inteligencia artificial (IA) es cada vez más común en la conversación diaria, generando opiniones diversas sobre su uso, así como temores en torno a su implementación en escala global. Sin embargo, en ocasiones no se tiene completa claridad acerca del significado del término, las ramificaciones que existen dentro de la IA, así como la manera en que se implementan las técnicas existentes. Este artículo describe estos conceptos. Asimismo, se discute la gran diversidad de aplicaciones que tiene la IA en ciencias e ingenierías, con énfasis particular en la Ingeniería de Procesos, una de las ramas de mayor relevancia en la Ingeniería Química. Finalmente, se discuten las perspectivas y áreas de oportunidad que se perciben para las diversas aplicaciones de la IA.
References
[1] R. Kamble and D. Shah, “Applications of artificial intelligence in human life,” International Journal of Research-Granthaalayah, vol. 6, no. 6, pp. 178–188, 2018.
[2] L. Spector, “Evolution of artificial intelligence,” Artificial Intelligence, vol. 170, pp. 1251–1253, 2006.
[3] M. Ghosh and A. Thirugnanam, “Introduction to Artificial Intelligence,” in Artificial Intelligence for Information Management: A Healthcare Perspective, K. G. Srinivasa, M. M. Patnaik and R. Kumar, Eds., Studies in Big Data, vol. 88. Singapore: Springer Nature Singapore, 2021, pp. 23–44, doi: 10.1007/978-981-16-0415-7_2..
[4] M. Alfonseca, “¿Basta la prueba de Turing para definir la ‘IA’?,” Science et Fides, vol. 2, no. 2, pp. 129–134, 2014.
[5] A. Alonso Betanzos and V. Bolón Canedo, IA, algoritmos y derecho. Una introducción. Barcelona, España: Fundación para la Universitat Oberta de Catalunya, 2020.
[6] S. Dhokare and A. Gaikwad, “A study of artificial intelligence: Types, opportunities & challenges,” Shodh Sanchar Bulletin, vol. 11, no. 41, pp. 133–137, 2021.
[7] J. Díaz-Ramírez, “Aprendizaje Automático y Aprendizaje Profundo,” Ingeniare. Revista Chilena de Ingeniería, vol. 29, no. 2, pp. 180–181, 2021.
[8] V. Pedrero, K. Reynaldos-Grandón, J. Ureta-Achurra and E. Cortez-Pinto, “Generalidades del Machine Learning y su aplicación en la gestión sanitaria en Servicios de Urgencia,” Revista Médica de Chile, vol. 149, no. 2, pp. 248–254, 2021.
[9] J. L. Sarmiento-Ramos, “Aplicaciones de las redes neuronales y el deep learning a la ingeniería biomédica,” Revista UIS Ingenierías, vol. 19, no. 4, pp. 1–18, 2020.
[10] I. K. Nti, A. F. Adekoya, B. A. Weyori and O. Nyarko-Boateng, “Applications of artificial intelligence in engineering and manufacturing: A systematic review,” Journal of Intelligent Manufacturing, vol. 33, pp. 1581–1601, 2021.
[11] C. H. Sheehan, “Various Artificial Intelligence in Information Systems,” School of Information Systems, Oct. 18, 2023. [Online]. Available: https://sis.binus.ac.id/2023/10/18/various-artificial-intelligence-in-information-systems/
[12] Y. Xu, X. Liu, X. Cao, C. Huang, E. Liu, S. Qian et al., “Artificial intelligence: A powerful paradigm for scientific research,” The Innovation, vol. 2, no. 4, Art. no. 100179, 2021.
[13] A. Haleem, M. Javaid, M. A. Qadri, R. P. Singh and R. Suman, “Artificial intelligence (AI) applications for marketing: A literature-based study,” International Journal of Intelligent Networks, vol. 3, pp. 119–132, 2022.
[14] Y. Zhan, Y. Xiong, R. Han, H. K. Lam and C. Blome, “The impact of artificial intelligence adoption for business-to-business marketing on shareholder reaction: A social actor perspective,” International Journal of Information Management, vol. 76, Art. no. 102768, 2024.
[15] M. I. Ali, S. M. Ali, S. Tahseen, M. Nisar and M. F. Saleem, “Application of Mathematics in Artificial Intelligence and Machine Learning,” International Journal of Research in Engineering, Science and Management, vol. 4, no. 12, pp. 140–141, 2021.
[16] R. E. Zapata, E. C. Guerrero and R. E. Montilla, “Emerging Technologies in Education: A Bibliometric Analysis of Artificial Intelligence and its Applications in Health Sciences,” Seminars in Medical Writing and Education, vol. 3, p. 49, 2024.
[17] Z. Wen, Y. Wang, Y. Zhong, Y. Hu, C. Yang, Y. Peng et al., “Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images,” Frontiers in Neurology, vol. 15, Art. no. 1391382, 2024.
[18] T. Kotsilieris, H. Karanikas, A. Tsanas and I. Anagnostopoulos, “Emerging E-Health Applications and Medical Information Systems,” Electronics, vol. 13, no. 13, Art. no. 2470, 2024.
[19] A. Maqsood, C. Chen and T. J. Jacobsson, “The Future of Material Scientists in an Age of Artificial Intelligence,” Advanced Science, vol. 11, no. 19, Art. no. 2401401, 2024.
[20] K. M. Jablonka, Q. Ai, A. Al-Feghali, S. Badhwar, J. D. Bocarsly, A. M. Bran et al., “14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon,” Digital Discovery, vol. 2, no. 5, pp. 1233–1250, 2023.
[21] A. Boehnlein, M. Diefenthaler, N. Sato, M. Schram, V. Ziegler, C. Fanelli et al., “Colloquium: Machine learning in nuclear physics,” Reviews of Modern Physics, vol. 94, Art. no. 031003, 2022.
[22] I. Zarembo, “Analysis of artificial intelligence applications for automated testing of video games,” in Proc. 12th Int. Scientific and Practical Conf. Environment. Technology. Resources (ETR), Rezekne, Latvia, vol. 2, pp. 170–174, 2019, doi:10.17770/ETR2019VOL2.4158.
[23] V. G. Goecks, N. Waytowich, D. E. Asher, S. J. Park, M. Mittrick, J. Richardson et al., “On games and simulators as a platform for development of artificial intelligence for command and control,” Journal of Defense Modeling and Simulation, vol. 20, no. 4, pp. 495–508, 2022.
[24] T. Savage, H. F. Almeida-Trasvina, E. A. Del Río-Chanona, R. Smith and D. Zhang, “An adaptive data-driven modelling and optimization framework for complex chemical process design,” Computer-Aided Chemical Engineering, vol. 48, pp. 73–78, 2020.
[25] V. Mann, M. Sales-Cruz, R. Gani and V. Venkatasubramanian, “eSFILES: Intelligent process flowsheet synthesis using process knowledge, symbolic AI, and machine learning,” Computers & Chemical Engineering, vol. 181, Art. no. 108505, 2024.
[26] M. Nayak, G. Dhanarajan, R. Dineshkumar and R. Sen, “Artificial intelligence driven process optimization for cleaner production of biomass with co-valorization of wastewater and flue gas in an algal biorefinery,” Journal of Cleaner Production, vol. 201, pp. 1092–1100, 2018.
[27] F. Mahmoudian, A. H. Moghaddam and S. M. Davachi, “Genetic-based multi-objective optimization of alkylation process by a hybrid model of statistical and artificial intelligence approaches,” Canadian Journal of Chemical Engineering, vol. 100, no. 1, pp. 90–102, 2021.
[28] Z. Wu, D. Rincon and P. D. Christofides, “Process structure-based recurrent neural network modeling for model predictive control of nonlinear processes,” Journal of Process Control, vol. 89, pp. 74–84, 2020.
[29] Y. Wang, Y. M. Ren and H. Li, “Symbolic multivariable hierarchical clustering based convolutional neural networks with applications in industrial process operating trend predictions,” Industrial & Engineering Chemistry Research, vol. 59, no. 34, pp. 15133–15145, 2020.
[30] W. Zhu, Y. Zhan and J. Romagnoli, “A deep learning approach on industrial pyrolysis reactor monitoring,” Chemical Engineering Transactions, vol. 74, pp. 691–696, 2019.
[31] F. Machado Cavalcanti, C. E. Kozonoe, K. A. Pacheco and R. M. de Brito Alves, “Application of Artificial Neural Networks to Chemical and Process Engineering,” in Deep Learning Applications, P. L. Mazzeo and P. Spagnolo, Eds. Rijeka, Croatia: IntechOpen, 2021, doi: 10.5772/intechopen.96641.
[32] R.-Z. Xu, J.-S. Cao, Y. Wu, S.-N. Wang, J.-Y. Luo, X. Chen et al., “An integrated approach based on virtual data augmentation and deep neural networks modeling for VFA production prediction in anaerobic fermentation process,” Water Research, vol. 184, Art. no. 116103, 2020.
[33] Z. J. Mosqueda-Huerta, O. D. Lara-Montaño, M. Toledano-Ayala and F. I. Gómez-Castro, “Desarrollo de modelos de red neuronal artificial para el diseño de intercambiadores de calor de tubos y coraza,” Avances en Ingeniería Química, vol. 3, no. 1, pp. PRO75–PRO80, 2024
[34] S. Manzhos and T. Carrington Jr., “Neural network potential energy surfaces for small molecules and reactions,” Chemical Reviews, vol. 121, pp. 10187–10217, 2021.
[35] A. Teixeira Lopes, E. de Aguiar, A. F. De Souza and T. Oliveira-Santos, “Facial expression recognition with Convolutional Neural Networks: Coping with few data and the training sample order,” Pattern Recognition, vol. 61, pp. 610–628, 2017.
[36] H. Yu, “Reflection on whether ChatGPT should be banned by academia from the perspective of education and teaching,” Frontiers in Psychology, vol. 14, Art. no. 1181712, 2023.
[37] Ö. Aydin and E. Karaarslan, “OpenAI ChatGPT Generated Literature Review: Digital Twin in Healthcare,” in Emerging Computer Technologies 2, Ö. Aydin, Ed. İzmir, Türkiye: İzmir Akademi Derneği, 2022, pp. 22–31, doi: 10.2139/ssrn.4308687.
[38] P. Bhatia, “ChatGPT for academic writing: a game changer of a disruptive tool?,” Journal of Anaesthesiology Clinical Pharmacology, vol. 39, no. 1, pp. 1–2, 2023.
[39] S. Ariyaratne, K. P. Iyengar, N. Nischal, N. C. Babu and R. Botchu, “A comparison of ChatGPT-generated articles with human-written articles,” Skeletal Radiology, vol. 52, pp. 1755–1758, 2023.
[40] Forbes Staff, “Creadores de ChatGPT afrontan demanda colectiva por violación de datos personales,” Forbes México. [Online]. Available: https://www.forbes.com.mx/creadores-de-chatgpt-afrontan-demanda-colectiva-por-violacion-de-datos-personales/
[41] W. Xiong, H. Fan, L. Ma and C. Wang, “Challenges of human-machine collaboration in risky decision-making,” Frontiers of Engineering Management, vol. 9, no. 1, pp. 89–103, 2022.
[42] B. H. Li, B. C. Hou, W. T. Yu, X. B. Lu and C. W. Yang, “Applications of artificial intelligence in intelligent manufacturing: a review,” Frontiers of Information Technology & Electronic Engineering, vol. 18, no. 1, pp. 86–96, 2017.
[43] P. Dhamija and S. Bag, “Role of artificial intelligence in operations environment: a review and bibliometric analysis,” The TQM Journal, vol. 32, no. 4, pp. 869–896, 2020.
[44] M. Abdallah, M. A. Talib, S. Feroz, Q. Nasir, H. Abdalla and B. Mahfood, “Artificial intelligence applications in solid waste management: A systematic research review,” Waste Management, vol. 109, pp. 231–246, 2020.
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