Computational Intelligence in Engineering and Project Managemen (2024) Springer » Histórico » Revisión 3
Revisión 2 (Pedro Yobanis Piñero Pérez, 2025-07-29 16:58) → Revisión 3/4 (Pedro Yobanis Piñero Pérez, 2025-07-29 17:03)
h1. Computational Intelligence in Engineering and Project Managemen (2024) Springer
Pérez, P. Y. P., Kacprzyk, J., Pérez, R. B., & Pupo, I. P. (Eds.). (2024). Computational Intelligence in Engineering and Project Management. Springer. https://doi.org/10.1007/978-3-031-50495-2
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h2. Conversational Systems and Computational Intelligence, A Critical Analysis
* Mir, Y.O.V., Piñero Pérez, P.Y., Pupo, I.P., Acuña, L.A., Pérez, R.B. (2024). Conversational Systems and Computational Intelligence, A Critical Analysis. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_1
*Abstract*
The increase in research on conversational systems and their applications, constitutes the main motivation of this work. In this research, a critical analysis of the growth of smart chatbots and their combination with computational intelligence techniques is carried out. The analysis is oriented on three fundamental fronts. First, a review protocol is applied to identify the main schools and centers of knowledge. Then the conversational systems are characterized based on the level of inclusion of artificial intelligence techniques. Finally, the integration of conversational systems with different computational intelligence techniques is reviewed. The analysis identifies that there are many opportunities and lines open to research. In particular, the need to strengthen the application of neutrosophic theory and sets for the evaluation of conversations is identified. Also, the need to combine linguistic data summarization techniques and reinforcement learning is identified to improve training methods and reduce the computational cost of conversational systems responses.
h2. Fuzzy Cognitive Maps, Extensions and Applicability as an Explanatory Artificial Intelligence Model
* Ruiz, Y.M., Piñero Pérez, P.Y., Pérez Pupo, I., García Vacacela, R., Al-Subhi, S.H.S. (2024). Fuzzy Cognitive Maps, Extensions and Applicability as an Explanatory Artificial Intelligence Model. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_2
*Abstract*
The growth of the prediction capabilities of deep neural networks constitutes one of the elements that has allowed the generalization of these models to dissimilar problems. But in the particular case of decision-making in project management, in addition to the quality of the prediction, it is necessary to know the explanation of the responses. This aims to increase the confidence of the systems in decision-making and agility in project management. The explanation of the answers is also important during project cuts, a process that manifests itself as a multistage sequential decision-making problem. In this research, it is proposed to explore the potential of fuzzy cognitive maps and their extensions, considering the potential of these techniques to represent causal relationships. To carry out this work, a conceptual theoretical framework is developed based on a systematic review. It is identified that there are insufficiencies in the research reported in the bibliography consulted regarding the treatment of indeterminacy and the solution of decision-making problems in project management.
h2. Project Scheduling a Critical Review of Both Traditional and Metaheuristic Techniques
* Piñero Pérez, P.Y., Pupo, I.P., Mahdi, G.S.S., Quintana, J.M., Acuña, L.A. (2024). Project Scheduling a Critical Review of Both Traditional and Metaheuristic Techniques. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_3
*Abstract*
Project planning is a problem usually discussed in the different project management standards as an essential problem to be addressed from the project initiation stage. It is a problem that has traditionally been treated by formal methodologies. But current trends in project development have a greater focus on agile methodologies. This situation causes greater variability in project plans. In the particular case of BIM methodologies, the approach is aimed at achieving the simulation of the production process through virtual construction. In this context, in this work, a critical analysis of different approaches that deal with the construction of project schedules is carried out. In particular, the problem is analyzed from a hybrid perspective. The approach proposed by project management standards and the approach to scheduling problems raised by computer science are analyzed. As a result of the analysis, a group of lines open to research are proposed that combine traditional tendencies with metaheuristics.