Deformation characterization of oil and gas pipeline by ACM technique based on SSA-BP neural network model

Xin, Jiaxing; Chen, Jinzhong; Li, Chunyu; Lu, Run-kun; Li, Xiaolong; Wang, Cynthia; Zhu, Hongwu; He, Ren

doi:10.1016/j.measurement.2021.110654

Cited by 28 publications

(13 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…BPNN is divided into the input, hidden, and output layers. e BP learning algorithm mainly uses signal forward propagation and error backpropagation [18]. e two propagation processes are specified in Figure 2.…”

Section: Bpnn-based Ece Modelmentioning

confidence: 99%

Reforming the Teaching of Engineering Cost Budgeting Majors by Integrating VR and BIM Technology under the Internet of Things

Zhang

Mo²

2022

Security and Communication Networks

View full text Add to dashboard Cite

With the continuous development of digital technology and the Internet of Things (IoT), the teaching methods for architecture major in higher vocational colleges have also undergone major changes. New technologies and instruction methods in Engineering Cost Budgeting teaching can stimulate students’ learning interest and improve education quality and students’ comprehensive learning ability. In order to improve the teaching level of engineering cost budgeting major and stimulate students’ interest in learning, this work first introduces backpropagation neural network (BPNN) into engineering cost estimation (ECE). Then, the BPNN-based ECE model is trained by the sample data to estimate the project’s total quotation and comprehensive unit price. The error between the real and predicted values is analyzed. Second, the building information modeling (BIM) technology and virtual reality (VR) technologies are integrated into teaching engineering cost budgeting. The investigation, research, and analysis are conducted before and after applying BIM and VR technology in practical teaching. The results show that the proposed BPNN-based ECE model-estimated total quotation and comprehensive unit price fit well the sample values. The BPNN-based ECE model can be applied to teaching engineering cost budgeting. It can improve the calculation accuracy, and the relative error can be controlled within a certain range and has a certain potential to replace manual budgeting. It can provide some reference for the research of engineering cost technology. Classroom teaching under the integration of BIM and VR technologies can improve the students’ homework quality, academic performance, and teaching quality to a certain extent. Integrating BIM and VR technology in classroom teaching can enhance students’ communication, cooperation ability, oral defense scores, comprehensive scores, and professional skills.

show abstract

Section: Bpnn-based Ece Modelmentioning

confidence: 99%

Reforming the Teaching of Engineering Cost Budgeting Majors by Integrating VR and BIM Technology under the Internet of Things

Zhang

Mo²

2022

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…BP network has strong local optimization seeking ability, but is easily influenced by the initial weights and thresholds and therefore falls into local optimality, resulting in poor recognition accuracy and stability of the model. Therefore, SSA [35][36][37] is used to optimize the initial weights and thresholds of BP neural network to improve the prediction accuracy of the model, compared with other optimization algorithms such as genetic algorithm (GA) [38], whale optimization algorithm (WOA) [39] and particle swarm optimization (PSO) [40], this algorithm outperforms GA, WOA and PSO in terms of accuracy, convergence speed, stability and robustness.…”

Section: Classification and Identification Of Mixed Gases Based On Pc...mentioning

confidence: 99%

Classification and identification of mixed gases based on the combination of semiconductor sensor array with SSA-BP neural network

Li¹,

Gu²,

Ge³

et al. 2023

Meas. Sci. Technol.

View full text Add to dashboard Cite

In this paper, pure "Sn" "O" _2, "Cu/Sn" "O" _2, ZnO and Cu/ZnO gas sensitive materials were synthesized by a simple hydrothermal reaction and used to prepare a gas sensor array. The morphological structure and composition of the synthesized materials were characterized using SEM and XRD, respectively. The sensor array was combined with the BP neural network algorithm optimized by the Sparrow Search algorithm (SSA-BPNN) and applied to effectively identify the types of mixed toxic gases in the room, including formaldehyde, ammonia and xylene. The combination of sensor array with optimized neural network algorithms achieved a good classification result for gas mixture and the classification accuracy can reach 93.45% for different classes of mixtures composed of three gases (formaldehyde, ammonia, and xylene). Therefore, the sensor array combined with the SSA-BP algorithm in this study has done a good work in the qualitative identification of ternary gas mixtures and has some application potential.

show abstract

“…It has the advantages of higher accuracy, strong global optimization ability and fast convergence speed. [55][56][57] Sparrow populations can be divided into discoverers and followers. The finder has a strong search ability and is responsible for finding food for the sparrow population.…”

Section: Ssa Optimized Bp Neural Networkmentioning

confidence: 99%

Quantitative prediction of ternary mixed gases based on an SnO₂ sensor array and an SSA-BP neural network model

Zhang

et al. 2023

Phys. Chem. Chem. Phys.

View full text Add to dashboard Cite

show abstract

Deformation characterization of oil and gas pipeline by ACM technique based on SSA-BP neural network model

Cited by 28 publications

References 33 publications

Reforming the Teaching of Engineering Cost Budgeting Majors by Integrating VR and BIM Technology under the Internet of Things

Reforming the Teaching of Engineering Cost Budgeting Majors by Integrating VR and BIM Technology under the Internet of Things

Classification and identification of mixed gases based on the combination of semiconductor sensor array with SSA-BP neural network

Quantitative prediction of ternary mixed gases based on an SnO₂ sensor array and an SSA-BP neural network model

Contact Info

Product

Resources

About

Deformation characterization of oil and gas pipeline by ACM technique based on SSA-BP neural network model

Cited by 28 publications

References 33 publications

Reforming the Teaching of Engineering Cost Budgeting Majors by Integrating VR and BIM Technology under the Internet of Things

Reforming the Teaching of Engineering Cost Budgeting Majors by Integrating VR and BIM Technology under the Internet of Things

Classification and identification of mixed gases based on the combination of semiconductor sensor array with SSA-BP neural network

Quantitative prediction of ternary mixed gases based on an SnO2 sensor array and an SSA-BP neural network model

Contact Info

Product

Resources

About

Quantitative prediction of ternary mixed gases based on an SnO₂ sensor array and an SSA-BP neural network model