Said Al Maqbali
Biographic Data
| ID | 10120995 |
|---|---|
| NAME | Said Al Maqbali |
| GIVEN NAMES | Said |
| FAMILY NAME | Al Maqbali |
| SIGNATURE | AL MAQBALI S |
| AFFILIATIONS | University of Buraimi |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Exploring the role of machine learning models in risk assessment models for developed organizations’ management decision policies
The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machin…
Advancing user classification models
In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pic…
No prominent works on this page.
Exploring the role of machine learning models in risk assessment models for developed organizations’ management decision policies
The goal of this work was to create and assess machine-learning models for estimating the risk of budget overruns in developed projects. Finding the best model for risk forecasting required evaluating the performance of several models. Using a dataset of 177 projects took into account variables like environmental risks employee skill level safety incidents and project complexity. In our experiments, we analyzed the application of different machin…
Advancing user classification models
In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pic…
Computer Science (2 works) · Computer security (2 works) · Artificial Intelligence (1 work) · Business (1 work) · Economic and Technological Systems Analysis (1 work) · Engineering (1 work) · Finance (1 work) · Knowledge management (1 work) · Machine learning (1 work) · Management science (1 work)