Titlebook: Emerging Trends in Intelligent Systems & Network Security; Mohamed Ben Ahmed,Boudhir Anouar Abdelhakim,Didi R Conference proceedings 2023

Feigned

TIA742

https://doi.org/10.1057/978-1-349-96048-4t of smart public transportation, it has been evaluated that it is a system that provides information such as speed, route, location and arrival time for all vehicles used in public transportation in real time. It is an efficient, effective, innovative, dynamic, environmentalist, value-added and sus

MURKY

A. Bankier,J. Brady,N. A. Myersusing a hidden units parameter of 128, dropout parameter of 0.3, and recurrent dropout parameter of 0.3. Results show that the attention mechanism can improve the performance of the LSTM model in performing aspect-based sentiment analysis.

反饋

Of Books, Barns, and BoardroomsTE and without SMOTE with Stratified K-Fold CV algorithm. The highest performance accuracy with SMOTE is obtained at 90.7% with the SVM model. Whereas without SMOTE, the highest performance accuracy uses the SVM with a value of 87.8%. Furthermore, with the addition of the Stratified K-Fold CV algori

Irksome

Emerging Trends in Intelligent Systems & Network Security

LAY

ostrish

A Proposed Big Data Architecture Using Data Lakes for Education Systems,e management of the different data sources to their final consumption. The proposal approach includes data lake as a means of modernizing decision-making processes, in particular data warehouses and OLAP methods. It will be used as a means for data consolidation for the integration of heterogeneous

委屈

獨(dú)輪車

Aspect-Based Sentiment Analysis of Indonesian-Language Hotel Reviews Using Long Short-Term Memory wusing a hidden units parameter of 128, dropout parameter of 0.3, and recurrent dropout parameter of 0.3. Results show that the attention mechanism can improve the performance of the LSTM model in performing aspect-based sentiment analysis.

Parameter