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Implementation of explainable artificial intelligence in commercial communication systems using micro systems

The developments in the field of artificial intelligence (AI) and decision making systems are identified as virtuous models for banking and finance sector (BFS) applications. Even though AI provides great advantage in application changes it is essential to remodel the system using explainable artifi...

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Detalles Bibliográficos
Autores principales: Manoharan, Hariprasath, Yuvaraja, Teekaraman, Kuppusamy, Ramya, Radhakrishnan, Arun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10399265/
https://www.ncbi.nlm.nih.gov/pubmed/37533330
http://dx.doi.org/10.1177/00368504231191657
Descripción
Sumario:The developments in the field of artificial intelligence (AI) and decision making systems are identified as virtuous models for banking and finance sector (BFS) applications. Even though AI provides great advantage in application changes it is essential to remodel the system using explainable artificial intelligence (XAI) design system. Also the standard sensing models provides appropriate monitoring values but huge size of sensors is considered as a major drawback. Thus two diverse problems are addressed in this research work where XAI has been integrated with micro electro-mechanical systems (MEMS) for solving the problems related to BFS applications. Further the data security has been enhanced as XAI is implemented with conviction managements and real time experiments are carried out by developing a unique application by integrating new mathematical designs. To validate the effectiveness of BFS application the developed model is tested with five scenarios which includes multiple parametric arrangements with interpretability process. The tested and compared outcomes with existing models indicates that XAI and MEMS provides inordinate improvements in terms of data impairments thus increasing the transparency of the projected system to an average 96%.