Artificial intelligence system based on multi-value classification of fully connected neural network for construction management
| Autor: | Honcharenko, Tetyana, Akselrod, Roman, Shpakov, Andrii, Khomenko, Oleksandr |
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| Rok vydání: | 2022 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | This study is devoted to solving the problem to determine the professional adaptive capabilities of construction management staff using artificial intelligence systems.It is proposed Fully Connected Feed-Forward Neural Network architecture and performed empirical modeling to create a Data Set. Model of artificial intelligence system allows evaluating the processes in an Fully Connected Feed-Forward Neural Network during the execution of multi-value classification of professional areas. A method has been developed for the training process of a machine learning model, which reflects the internal connections between the components of an artificial intelligence system that allow it to learn from training data. To train the neural network, a data set of 35 input parameters and 29 output parameters was used; the amount of data in the set is 936 data lines. Neural network training occurred in the proportion of 10% and 90%, respectively. Results of this study research can be used to further improve the knowledge and skills necessary for successful professional realization. Comment: 10 pages, 7 figures |
| Databáze: | arXiv |
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