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All Outputs (4)

Developing an industry 4.0 readiness model using fuzzy cognitive maps approach (2022)
Journal Article
Monshizadeh, F., Moghadam, M., Mansouri, T., & Kumar, M. (2022). Developing an industry 4.0 readiness model using fuzzy cognitive maps approach. International Journal of Production Economics, 255, https://doi.org/10.1016/j.ijpe.2022.108658

Industry 4.0, or the fourth industrial revolution, is a new paradigm in manufacturing digitalization, which provides various opportunities for enterprises. Industry 4.0 readiness models are worthy methods to aid manufacturing organizations in trackin... Read More about Developing an industry 4.0 readiness model using fuzzy cognitive maps approach.

Markowitz-based cardinality constrained portfolio selection using Asexual Reproduction Optimization (ARO) (2022)
Journal Article
Mansouri, T., Sadeghi Moghadam, M. R., & Sheykhizadeh, M. (2022). Markowitz-based cardinality constrained portfolio selection using Asexual Reproduction Optimization (ARO). https://doi.org/10.22059/IJMS.2021.313393.674293

The Markowitz-based portfolio selection turns to an NP-hard problem when considering cardinality constraints. In this case, existing exact solutions like quadratic programming may not be efficient to solve the problem. Many researchers, therefore, us... Read More about Markowitz-based cardinality constrained portfolio selection using Asexual Reproduction Optimization (ARO).

A deep explainable model for fault prediction using IoT sensors (2022)
Journal Article
Mansouri, T., & Vadera, S. (2022). A deep explainable model for fault prediction using IoT sensors. IEEE Access, https://doi.org/10.1109/ACCESS.2022.3184693

IoT sensors and deep learning models can widely be applied for fault prediction. Although deep learning models are considerably more potent than many conventional machine learning models, they are not transparent. This paper first examines differen... Read More about A deep explainable model for fault prediction using IoT sensors.