Design and Research on the Intelligent System of Urban Rail Transit Project based on BIM+GIS

Liu, Yan; Shah, Mohd Asif; Pljonkin, Anton; Ikbal, Mohammad Asif; Shabaz, Mohammad

doi:10.12694/scpe.v22i2.1875

Cited by 6 publications

(4 citation statements)

References 25 publications

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“…Te proposal of AlexNet in 2012 made the deep convolutional neural network (CNN) more widely used in image recognition [7,8]. [9] used transfer learning to adjust VGG-16 and realized the disease identifcation of Camellia oleifera. [10] proposed an ARNet combining attention mechanism and residual to learn tomato disease identifcation.…”

Section: Introductionmentioning

confidence: 99%

Multidimensional Attention-Based CNN Model for Identifying Apple Leaf Disease

Perveen

Kumar

Kansal³

et al. 2023

Journal of Food Quality

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To prevent the spread of illnesses and guarantee the steady and healthy growth of the apple sector, the proper diagnosis of apple leaf diseases is of utmost importance. The subtle interclass variations and enormous intraclass variances among apple leaf disease features, together with the uniformity of disease spots and the complicated background environment, make apple leaf disease diagnosis extremely challenging. A unique dual-branch apple leaf disease diagnosis system (DBNet) was put out to address the aforementioned issues. An attention branch with many dimensions and a multiscale joint branch (MS) make up the dual-branch network topology of the DBNet (DA). In this study, the MS branch and the DA branch are combined to create a DBNet, which successfully improves recognition accuracy while mitigating the negative impacts of complicated backdrop environments and lesion similarities. The accuracy of the DBNet network increases by 0.02843, 0.02412, 0.0144, and 0.0125, respectively, when compared to previous leaf disease detection models. This makes it evident that the suggested DBNet model has certain benefits over others in terms of identifying apple leaf disease.

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Section: Introductionmentioning

confidence: 99%

Multidimensional Attention-Based CNN Model for Identifying Apple Leaf Disease

Perveen

Kumar

Kansal³

et al. 2023

Journal of Food Quality

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“…Usually, servo systems require a controller in addition to speed control, which again is frequently handled by cascading or series linking a position loop and a speed loop. A single PID position loop is occasionally used to provide position and speed control in the absence of an explicit velocity loop [2,3]. At present, the general motion servo control is still a widely used classical PID control method, and its advantage is a simple algorithm and easy to implement.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristics Based Modeling and Simulation Analysis of New Integrated Mechanized Operation Solution and Position Servo System

Gao

Oleiwi

Jawarneh³

et al. 2022

Mathematical Problems in Engineering

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Inadequate environmental protection is a problem, and to address it, the efficiency and quality grade of mechanical operations should be improved. A new comprehensive mechanized operation solution is proposed. The position control of a servo motor utilizing a PID (proportional, integral, derivative) controller and soft computing optimization approaches is explored in this paper. The essential technological realization techniques are reviewed and assessed, which serves as a reference for comprehensive mechanization solutions. The simulation model may be used to examine system features and explore control strategy by reflecting the characteristics of the actual system. A PID controller is designed by establishing a mathematical model based on the position servo system. It is verified that the PID control link is added to the pneumatic position servo control system. Through the comparison of the PID control experiment and PID control simulation data, the system can achieve high-precision position control, and the error is less than ±20 mm, meeting the requirements of rust removal and spraying design, and showing that the control system works stably and reliably to achieve high-precision simulation of the pneumatic position servo system.

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“…In addition, in terms of traffic safety monitoring, according to the existing foundation pit excavation construction plan and the situation of the subway tunnel structure, a three-dimensional, large-scale numerical calculation model was established to calculate the internal force and deformation changes of the tunnel structure during the foundation pit excavation preparation stage law. The model can guide the construction process and provide a reference for the corresponding safety monitoring program [44]. In the field of smart security, 3D reconstruction and remote sensing technology combined with artificial intelligence algorithms can be used for real-time monitoring and early warning of the security situation in an area.…”

Section: Applications Of 3d Reconstruction and Extraction And Rs Ai A...mentioning

confidence: 99%

A Single Data Extraction Algorithm for Oblique Photographic Data Based on the U-Net

Wang,

Li,

Lin

et al. 2024

Remote Sensing

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In the automated modeling generated by oblique photography, various terrains cannot be physically distinguished individually within the triangulated irregular network (TIN). To utilize the data representing individual features, such as a single building, a process of building monomer construction is required to identify and extract these distinct parts. This approach aids subsequent analyses by focusing on specific entities, mitigating interference from complex scenes. A deep convolutional neural network is constructed, combining U-Net and ResNeXt architectures. The network takes as input both digital orthophoto map (DOM) and oblique photography data, effectively extracting the polygonal footprints of buildings. Extraction accuracy among different algorithms is compared, with results indicating that the ResNeXt-based network achieves the highest intersection over union (IOU) for building segmentation, reaching 0.8255. The proposed “dynamic virtual monomer” technique binds the extracted vector footprints dynamically to the original oblique photography surface through rendering. This enables the selective representation and querying of individual buildings. Empirical evidence demonstrates the effectiveness of this technique in interactive queries and spatial analysis. The high level of automation and excellent accuracy of this method can further advance the application of oblique photography data in 3D urban modeling and geographic information system (GIS) analysis.

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Design and Research on the Intelligent System of Urban Rail Transit Project based on BIM+GIS

Cited by 6 publications

References 25 publications

Multidimensional Attention-Based CNN Model for Identifying Apple Leaf Disease

Multidimensional Attention-Based CNN Model for Identifying Apple Leaf Disease

Metaheuristics Based Modeling and Simulation Analysis of New Integrated Mechanized Operation Solution and Position Servo System

A Single Data Extraction Algorithm for Oblique Photographic Data Based on the U-Net

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