Addressing the Smart Systems design challenge: The SMAC platform

Bombieri, Nicola; Drogoudis, Dimitrios; Gangemi, Giuliana; Gillon, Renaud; Grosso, M.; Macii, Enrico; Poncino, Massimo; Rinaudo, Salvatore

doi:10.1016/j.micpro.2015.05.013

Cited by 5 publications

(1 citation statement)

References 17 publications

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“…Over its application, a comfortable and secure operation site, unaffected via way of means of terrible weather, turned into a discount in labour prerequisite, removal of dangerous works and a discount in material waste. In the year of 2017 researcher named Philips, has put forward the idea of knowledge management automation and implementing artificial intelligence in libraries (Bombieri et al, 2015). The development of robots and artificial intelligence brought a greater potential in the applications which provide knowledge management services.…”

Section: Literature Reviewmentioning

confidence: 99%

The Role of Smart Systems in Enhancing the Performance of Knowledge Management in Libraries Based on the Adoption of Using Expert System and Robots

Qhal¹

2023

J. Professional Business Review

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Purpose: This study aims to enhance the performance of Knowledge management (KM). Additionally, the advantages and the applications of this export system and the smart systems are analyzed. Theoretical framework: Selecting an algorithm isn’t an easy process. With a deep exploration of techniques and algorithms, the appropriate algorithm should be chosen and implemented to ascertain the solution for the problems like analyzing the trend of the business, identifying the age group, and finding the most desired articles and publications. Design/methodology/approach: Contented and Expressive review approaches are implemented to conduct the research. The investigators significantly studied the materials associated with robots and expert systems in the reference to knowledge management in libraries. The results are obtained using the data visualization tool tableau. the Genetic algorithm is also used to analyze the results. Findings: Smart systems are not easy to implement in knowledge management because knowledge management contains a large number of datasets. It has to be categorized first, then needs to be analyzed and the decisions must be taken accordingly. Research, Practical & Social implications: The expert systems and the robots are to be implemented in the KM so the knowledge management will have enhanced performance with the help of the implementation of smart systems. Originality/value: In the study, the Genetic algorithm is used to find the analysis results. This algorithm was chosen because it works well in a noisy environment and is also easy to understand along with this GA is compared with the neural network algorithm.

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Section: Literature Reviewmentioning

confidence: 99%