<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In order to improve the efficiency of the intelligent control system of the port tipping line, this paper builds a port tipping line simulation intelligent control system based on WITHNESS software. Firstly, through ARTG (Konecranes Automation System) control switch, the simulation model of single-vessel loading and unloading transportation of the road network from the port front to the yard is established. Secondly, the Kalman filter algorithm and genetic algorithm are used to informally manage the port loading and unloading truck entry and exit data, and the assembly balance in the genetic algorithm is used to improve the data mining efficiency, and finally, the simulation system is tested for data. The results show that: the simulation system WITHNESS model constructed in this paper has an average time of 20.34 min for external collector trucks in the port dwell time, among which the number of vehicles with dwell time in [17/22] and [22/30] minutes is the majority accounting for a total of 60.7% of the total. Furthermore, the comparison of yard area reduction shows that the dwell time is 72.6%, 70.9%, and 87.5%, respectively, for yard area at different times. It can be seen that the simulation system WITHNESS model constructed in this paper helps to promote the development of port loading and unloading and can improve the effectiveness of loading and unloading work.</p>
</abstract>

In order to improve the efficiency of the intelligent control system of the port tipping line, this paper builds a port tipping line simulation intelligent control system based on WITHNESS software. Firstly, through ARTG (Konecranes Automation System) control switch, the simulation model of single-vessel loading and unloading transportation of the road network from the port front to the yard is established. Secondly, the Kalman filter algorithm and genetic algorithm are used to informally manage the port loading and unloading truck entry and exit data, and the assembly balance in the genetic algorithm is used to improve the data mining efficiency, and finally, the simulation system is tested for data. The results show that: the simulation system WITHNESS model constructed in this paper has an average time of 20.34 min for external collector trucks in the port dwell time, among which the number of vehicles with dwell time in [17/22] and [22/30] minutes is the majority accounting for a total of 60.7% of the total. Furthermore, the comparison of yard area reduction shows that the dwell time is 72.6%, 70.9%, and 87.5%, respectively, for yard area at different times. It can be seen that the simulation system WITHNESS model constructed in this paper helps to promote the development of port loading and unloading and can improve the effectiveness of loading and unloading work.

Intelligent control system of port turning line based on WITNESS software

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Intelligent control system of port turning line based on WITNESS software"}

In order to improve the efficiency of the intelligent control system of the port tipping line, this paper builds a port tipping line simulation intelligent...

Intelligent control system of port turning line based on WITNESS software

Publicado en línea: 07 jun 2023

Páginas: -

Recibido: 09 ago 2022

Aceptado: 13 dic 2022

DOI: https://doi.org/10.2478/amns.2023.1.00374

Palabras clave
WITNESS model, Kalman filtering algorithm, Genetic algorithm, Intelligent control system, ARTG control switch

© 2023 Hongjun Li, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Intelligent control system of port turning line based on WITNESS software

Publicado en línea: 07 jun 2023

Páginas: -

Recibido: 09 ago 2022

Aceptado: 13 dic 2022

DOI: https://doi.org/10.2478/amns.2023.1.00374

Palabras claveWITNESS model, Kalman filtering algorithm, Genetic algorithm, Intelligent control system, ARTG control switch

© 2023 Hongjun Li, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Palabras clave
WITNESS model, Kalman filtering algorithm, Genetic algorithm, Intelligent control system, ARTG control switch