2011
DOI: 10.1007/s11431-011-4616-5
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Research on analysis method for temperature control information of high arch dam construction

Abstract: Temperature control, which is directly responsible for the project quality and progress, plays an important role in high arch dam construction. How to discover the rules from a large amount of temperature control information collected in order to guide the adjustment of temperature control measures to prevent cracks on site is the key scientific problem. In this paper, a mathematic logical model was built firstly by means of a coupling analysis of temperature control system decomposition and coordination for h… Show more

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Cited by 3 publications
(3 citation statements)
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“…The study's findings indicate a positive relationship between R&D spending and sustainable corporate performance. A research on innovation performance and sustainable business performance in Shanghai, China's high-tech firms was carried out by Zhong & Ren in 2021 [6]. The findings demonstrate how investing in science and technology by businesses enhances their long-term financial performance.…”
Section: Review Of Literaturementioning
confidence: 99%
“…The study's findings indicate a positive relationship between R&D spending and sustainable corporate performance. A research on innovation performance and sustainable business performance in Shanghai, China's high-tech firms was carried out by Zhong & Ren in 2021 [6]. The findings demonstrate how investing in science and technology by businesses enhances their long-term financial performance.…”
Section: Review Of Literaturementioning
confidence: 99%
“…Zhong et al [140][141][142] conducted some research on the order of pour by pour and the temperature control scheme of dam concrete to predict the maximum temperature during the pouring process. The obtained achievements have been used in practice.…”
Section: Preventive Measures Of Local Damagementioning
confidence: 99%
“…Generally, the prediction models are mainly divided into point prediction and interval prediction according to different prediction forms. These point prediction methods have been applied in the field of temperature prediction, including back-propagation neural network [19,20], artificial neural network [21], gray model [22], genetic algorithm [23,24], and support vector machine [25,26]. However, point prediction only provides one prediction result at each target point, which lacks uncertainty estimation [27,28].…”
Section: Introductionmentioning
confidence: 99%