Compaction Density Evaluation Model of Sand-Gravel Dam Based on Elman Neural Network With Modified Particle Swarm Optimization

Liu, Biao; Zhao, Yufei; Wang, Wenbo; Liu, Biwang

doi:10.3389/fphy.2021.806231

Cited by 12 publications

(8 citation statements)

References 36 publications

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“…Since QC/QA of earthwork are closely related to compaction parameters and compaction quality, the research of digital rolling compaction methods mainly focuses on monitoring compaction parameters and compaction quality (see Figure 6 ). Combined with the cluster analysis results in Figure 1 , digital rolling compaction methods are the current research hotspot in the QC/QA methods of earthwork and have been widely used in the construction of roads [ 11 , 23 , 32 ], railways [ 34 , 95 ], airports [ 8 , 35 ], and dams [ 24 , 36 , 96 ].…”

Section: Digital Rolling Compaction Methodsmentioning

confidence: 99%

A Review on Roller Compaction Quality Control and Assurance Methods for Earthwork in Five Application Scenarios

Zhang

Huangfu³

et al. 2022

Materials

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Successful quality control and quality assurance (QC/QA) of earthwork compaction is critical to the long-term performance of roads, railways, airports, dams, and embankments. The purpose of this paper is to provide insights into the current practice, existing problems, challenges, and future development trends of QC/QA methods from the perspective of bibliometrics and the development stage. A bibliometric analysis is presented. Through quantitative analysis of literature and qualitative analysis of the development stage, insights into the current research practices and future directions of QC/QA methods have been derived from the perspectives of literature, cluster analysis, classification, different types of QC/QA methods, conclusions, and recommendations. It is found that the current QC/QA methods can be roughly divided into conventional compaction, digital rolling compaction, automatic rolling compaction, and intelligent control compaction. Currently, QC/QA methods are mainly confronted with the issues of accurate detection of compaction quality, autonomous optimization and intelligent decision-making of compaction process, multi-machine coordination, QC/QA-related specification formulation, and process standardization. To address these issues, several critical potential research directions are further identified: comprehensive CCI measurement system; simple and realistic mathematical representation of the complex compaction dynamics; parallel computing and distributed management of multi-source heterogeneous data; standardized application workflow and the cost–benefit assessment in the context of the full life cycle; intelligent control theories, methods, and technologies of earthwork compaction based on multidisciplinary integration. The paper enables researchers to obtain a comprehensive understanding of QC/QA methods for earthwork compaction as well as the suggested solutions for future work.

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Section: Digital Rolling Compaction Methodsmentioning

confidence: 99%

A Review on Roller Compaction Quality Control and Assurance Methods for Earthwork in Five Application Scenarios

Zhang

Huangfu³

et al. 2022

Materials

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“…Each stage has several tasks. This approach helps to improve the reliability of the evaluation and the reliability of the evaluation results [22].…”

Section: The Shortcomings Of Traditional Physical Education Teaching ...mentioning

confidence: 99%

Construction of Physical Education Evaluation System Based on Fuzzy Neural Network Modeling

Wang

2024

Preprint

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As a frontier concept of current basic education, subject literacy indicates that our country has established the direction of curriculum reform aiming at developing students' core literacy. The core subject literacy is not only the basic subject literacy gradually developed by students in the course of subject learning, but also the comprehensive factors such as character and ability gradually formed by students in extracurricular social practice activities, which is an important indicator of the new curriculum education reform. In view of the fact that the special teaching connotation of high school physical education still needs to be clarified, the evaluation methods of teaching effect still need to be enriched, and the teaching reform theory needs to be further improved. Focus on cultivating college students' lifelong sports awareness, mastering sports knowledge and skills, and developing their physical fitness, good sports behavior and sports moral quality healthily. According to the characteristics of physical education learning evaluation, the fuzzy neural network is selected to model, and the physical education teaching evaluation system is constructed. The adaptive fuzzy neural system is used to process the data, thus realizing the intelligence and automation of physical education teaching evaluation. Finally, the artificial neural network and adaptive fuzzy neural system are used in the evaluation and modeling of physical education teaching, and the experimental simulation comparison and performance analysis of the two models show that the model has good evaluation ability.

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“…Subsequently, our research on the Qarqan River revealed that the new Dashimen Water Conservancy Hub Project, constructed upstream, offers comprehensive benefits such as flood control, power generation, irrigation, and water supply. This project has effectively alleviated the seasonal water shortage in the irrigation area and has significantly contributed to local economic and social development [38,39]. The project began lowering and storing water on 20 September 2021 and was first put into spring production in 2022; prior to storage, this area was essentially dry.…”

Section: Analysis Of the Causes Of Changes In Water Area Of Taitma Lakementioning

confidence: 99%

Changes in the Water Area of an Inland River Terminal Lake (Taitma Lake) Driven by Climate Change and Human Activities, 2017–2022

Zi,

Wang,

et al. 2024

Remote Sensing

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Constructed from a dataset capturing the seasonal and annual water body distribution of the lower Qarqan River in the Taitma Lake area from 2017 to 2022, and combined with the meteorological and hydraulic engineering data, the spatial and temporal change patterns of the Taitma Lake watershed area were determined. Analyses were conducted using Planetscope (PS) satellite images and a deep learning model. The results revealed the following: ① Deep learning-based water body extraction provides significantly greater accuracy than the conventional water body index approach. With an impressive accuracy of up to 96.0%, UPerNet was found to provide the most effective extraction results among the three convolutional neural networks (U-Net, DeeplabV3+, and UPerNet) used for semantic segmentation; ② Between 2017 and 2022, Taitma Lake’s water area experienced a rapid decrease, with the distribution of water predominantly shifting towards the east–west direction more than the north–south. The shifts between 2017 and 2020 and between 2020 and 2022 were clearly discernible, with the latter stage (2020–2022) being more significant than the former (2017–2020); ③ According to observations, Taitma Lake’s changing water area has been primarily influenced by human activity over the last six years. Based on the research findings of this paper, it was observed that this study provides a valuable scientific basis for water resource allocation aiming to balance the development of water resources in the middle and upper reaches of the Tarim and Qarqan Rivers, as well as for the ecological protection of the downstream Taitma Lake.

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Compaction Density Evaluation Model of Sand-Gravel Dam Based on Elman Neural Network With Modified Particle Swarm Optimization

Cited by 12 publications

References 36 publications

A Review on Roller Compaction Quality Control and Assurance Methods for Earthwork in Five Application Scenarios

A Review on Roller Compaction Quality Control and Assurance Methods for Earthwork in Five Application Scenarios

Construction of Physical Education Evaluation System Based on Fuzzy Neural Network Modeling

Changes in the Water Area of an Inland River Terminal Lake (Taitma Lake) Driven by Climate Change and Human Activities, 2017–2022

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