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排序方式: 共有352条查询结果,搜索用时 31 毫秒
1.
潮滩沉积物水分的分布在空间和时间上会有很大的变化,含水量的变化会导致沉积物中生源要素含量的变化。因此,实时、准确、快速的监测潮滩沉积物含水量,对了解潮滩的各种特性,掌握潮滩生源要素信息,潮滩资源的开发有着重要意义。采集青岛市东大洋村潮间带的沉积物115份,分别测定新鲜样品、风干4周、风干8周样品的可见近红外光谱和含水量。以db10小波基和sym6小波基对原始光谱进行小波变换,采用偏最小二乘回归建立潮滩沉积物含水量模型。通过10阶小波变换获取原始光谱的低频信息An和高频信息Dn(n=1, 2, …,10),通过原始光谱S分别与高频信息Dn做差值,得到S-Dn,对An,Dn和S-Dn建立潮滩沉积物含水量模型,并对模型结果进行分析。原始光谱建立模型的R2p为0.841,RMSEP为2.767,RPD值为2.481。通过对db10小波基变换后的低频和高频信息分析,无用信息主要集中在D3和D4,去除D3和D4建立的含水量模型,相比于原始光谱模型精度有明显提高,R2p为0.878,RMSEP为2.501,RPD值为2.749;通过sym6小波基变换后进行分析,无用信息主要集中在D5和D9,去除D5和D9建立含水量模型与原始光谱模型相比,精度也有一定提高,R2p为0.87,RMSEP为2.475,RPD值为2.768。因此通过小波变换对原始光谱划分低频信息和高频信息进行分析,能够有效找到潮滩沉积物含水量的干扰信息,实现特征信息提取,从而建立准确度更高的潮滩沉积物含水量模型,为潮滩沉积物含水量实时、动态监测提供理论基础。 相似文献
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基于光谱技术建立的多元校正模型通常条件下只适用于同一台仪器、相同的测试条件及同批次或同类别的样品。在仪器、测试环境、样品发生变化后,已建光谱模型不再适配,需要进行模型转移。模型转移是限制光谱技术推广应用的关键技术瓶颈,模型转移是否成功直接影响到可见-近红外光谱技术的推广应用,为此,综述了其研究现状,并探讨了其未来发展方向。首先,将模型转移问题分成了两类:第一类是相同样品在不同仪器或不同测试环境(不同温度/不同湿度)等条件下产生的模型不适配问题;第二类是不同批次、不同物理形态、不同种类间产生的模型不适配问题。这两类问题性质不同,解决第一类模型转移,能够保证同源样品的准确性和稳定性;解决第二类,能够实现光谱模型在不同样品间的自动传递和匹配应用。然后,梳理了常用的模型转移算法并进行了分类,包括模型更新、基于光谱校正算法、基于结果校正算法等,并列举了每个类别的模型转移算法的应用。模型更新是一种重新计算模型系数最直接的方法,通过扩展和调整模型来满足新的变化;基于光谱校正算法是通过算法计算转移矩阵,实现对光谱的校正;基于结果校正算法是通过算法计算预测结果和实际结果系数,从而实现预测结果的校正。最后,指出未来应着重研究第二类模型转移问题,并且要寻找能够实现机器自动校正的模型转移,从根本上解决模型转移这一限制光谱速测应用的主要技术瓶颈。 相似文献
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礁灰岩的溶蚀对海洋工程和岛礁工程的稳定性有明显的影响.孔隙型溶蚀是礁灰岩常见的溶蚀方式.本文通过构建随机溶蚀孔洞的离散元模型,模拟孔洞型溶蚀礁灰岩的细观变形破坏特征,分析其变形破坏规律与裂隙演化特征.结果 表明,基于随机聚类算法构建的溶蚀礁灰岩离散元模型能够很好地模拟孔洞型溶蚀作用,且其变形破坏特征具有明显的规律;随着溶蚀率的增加,溶蚀礁灰岩单轴应力应变曲线由单峰型逐渐转变为双峰型或多峰型,破坏特征由脆性破坏逐渐转变为塑性破坏;随着溶蚀率的增加,礁灰岩单轴抗压强度和弹性模量都逐渐减小,抗压强度呈指数函数下降,弹性模量呈线性函数下降,而泊松比则表现为先增后降,说明试样在高溶蚀率时主要发生结构性破坏;随着溶蚀率增加,礁灰岩的宏观破裂面逐渐消失,由于溶蚀孔洞的相互作用,导致了起源于孔洞周围的裂隙开始萌生,并逐渐贯通,最终导致试样发生整体宏观破坏.本研究成果可为深入认识海洋工程和岛礁工程中溶蚀礁灰岩的变形破坏特征提供理论参考. 相似文献
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Nonlinear Dynamics - Under investigation in this work is a newly proposed nonlocal long-wave–short-wave resonance interaction (LSRI) equation with the self-induced parity-time (PT) symmetric... 相似文献
6.
Xiaofeng Zheng Xinyu Zhao Jie Huang Hao Yang Qinghui Wang Yuhang Liu Peiwei Gong Laijin Tian Hongping Xiao Zhe Liu 《应用有机金属化学》2020,34(12):e5981
The low-cost, high specific surface area and porosity, controlled pore size, and chemical properties of metal–organic framework (MOF) materials have attracted much attention in the exploration of proton conduction. The method of chemically modifying MOF structures or introducing conductive medium into the holes can effectively improve the proton conductivities of the materials. Here, the structural tunability of ionic liquid (IL) and flexible MOF (fle-MOF) materials are matched to give full play to the conductivity of IL, the framework support, and the microporous effect of MOFs, which achieves the synergistic effect of performance and expands the temperature range of proton transfer. Three kinds of CS/IL@fle-MOF membranes were prepared by combining three fle-MOFs with 1-carboxymethyl-3-methylimidazole (CMMIM) in different proportions to obtain 15 pieces of membranes. The comparative analyses show that CS/IL@fle-MOF membranes have excellent proton conduction performance at a wider temperature range (263–353 K) and lower relative humidity (75% RH). Among them, the proton conductivities of CS/CMMIM@MIL-88A-25% and CS/CMMIM@MIL-88B-125% are up to 1.33 and 1.42 S cm−1 at 75% RH and 353 K, respectively; whereas those of CS/CMMIM@MIL-53(Fe)-75% and CS/CMMIM@MIL-88B-125% reach up to 2.1 × 10−3 and 1.28 × 10−3 S cm−1 at 75% RH and 263 K, respectively. The Ea of CS/CMMIM@fle-MOFs is in the range of 0.1–0.5 eV, suggesting that the proton transport follows predominantly the typical Grotthuss transfer mechanism. The results of this study indicate that the CS/CMMIM@fle-MOF membranes combinations offer great potential for the design of composite porous proton-conducting materials. 相似文献
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Aiming at identifying nonlinear systems, one of the most challenging problems in system identification, a class of data-driven recursive least squares algorithms are presented in this work. First, a full form dynamic linearization based linear data model for nonlinear systems is derived. Consequently, a full form dynamic linearization-based data-driven recursive least squares identification method for estimating the unknown parameter of the obtained linear data model is proposed along with convergence analysis and prediction of the outputs subject to stochastic noises. Furthermore, a partial form dynamic linearization-based data-driven recursive least squares identification algorithm is also developed as a special case of the full form dynamic linearization based algorithm. The proposed two identification algorithms for the nonlinear nonaffine discrete-time systems are flexible in applications without relying on any explicit mechanism model information of the systems. Additionally, the number of the parameters in the obtained linear data model can be tuned flexibly to reduce computation complexity. The validity of the two identification algorithms is verified by rigorous theoretical analysis and simulation studies. 相似文献
9.
Zhang Yingying Bi Haijie Wu Bingwei Yuan Da Shi Yan Feng Xiandong 《Journal of Radioanalytical and Nuclear Chemistry》2022,331(9):3723-3733
The NaI(Tl) detector has been an important research topic and application in the field of in situ marine radioactive automatic monitoring because of its advantages of low power consumption, low cost, and good efficiency. However, its energy resolution is not high enough. This paper investigated an analytical method: spectrum de-noising, background correction based on the SNIP operator, peak search based on the top-hat transform and peak fitting using Gaussian distribution. Simulation and gamma spectra measured from seawater showed that the established energy spectrum analysis method presents satisfactory automatic analytical ability for identification and quantitatively analysis.
相似文献10.