C4.5 Decision Tree Machine Learning Algorithm Based GIS Route Identification

Dalela, Pankaj Kumar; Bansal, Prashant; Yadav, Arun Kumar; Majumdar, Sabyasachi; Yadav, Anurag; Tyagi, Vipin

doi:10.1109/icufn.2018.8436994

Cited by 1 publication

(1 citation statement)

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“…Because it is visualized throughout the earth, it is effortless for interpreting and understanding. Therefore, numerous organizations over the world intend to display information using GIS 2 .…”

Section: Introductionmentioning

confidence: 99%

Advanced GIS-based Multi-Function Support System for Identifying the Best Route

Zeki

2022

Baghdad Sci.J

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Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support systems that significantly reduce the cost involved when moving between two locations. Therefore, in this paper, an advanced decision support system is built for identifying the best route between two locations according to various criteria such as distance, travel time, the safety of the road, and other features. The proposed model includes several stages; Google Maps downloading, preprocessing, integrating with the database, and identifying the best route by utilizing advanced algorithms of artificial intelligence. Furthermore, the Open Street Maps (OSM) database is utilized in this model and implemented using the Quantum Geographic Information Systems (QGIS) platform. One of the main merits of this model is to be faster by removing the influence of non-processed data like null values and unlinked roads on offline google maps levels. The outcomes of this proposed model display the best route which connects the source with the destination, and a table including the entire information for this route.

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Section: Introductionmentioning

confidence: 99%

Advanced GIS-based Multi-Function Support System for Identifying the Best Route

Zeki

2022

Baghdad Sci.J

View full text Add to dashboard Cite

show abstract

C4.5 Decision Tree Machine Learning Algorithm Based GIS Route Identification

Cited by 1 publication

References 3 publications

Advanced GIS-based Multi-Function Support System for Identifying the Best Route

Advanced GIS-based Multi-Function Support System for Identifying the Best Route

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