Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Variations of Kuroshio geostrophic transport south of Japan estimated from long-term IES observations

Two inverted echo sounders were maintained on coastal and offshore sides of the Kuroshio south of Japan from October 1993 to July 2004. Applying the gravest empirical mode method, we obtained a time series of geostrophic transport. Estimated transports generally agree well with geostrophic transports estimated from hydrography. Their agreement with the hydrographic transports is better than that of transports estimated from satellite altimetry data. The geostrophic transport is expressed as the surface transport per unit depth multiplied by the equivalent depth. The geostrophic transport varies mostly with the surface transport and fractionally with the equivalent depth. Seasonal variation of the geostrophic transport has a minimum in March and a maximum in September, with a range of about one fifth of the total transport.     

基于NS2的TCPW性能改进算法研究

TCP Westwood(TCPW)和Vegas都是基于测量的TCP New-Reno增强算法。TCPW针对ACK流直接估算可用带宽,在慢启动和线性递增部分依然采用传统Reno的盲目递增的机制,导致发送端较为频繁的重传。对这几种算法原理进行分析阐述,并提出1种改进方法,更精确的测量估计带宽,通过网络仿真工具NS2进行验证,明显去除TCP全局同步现象,增强网络性能。     

高频电力线信息传输的电机模型与仿真

研究在电机驱动系统中,电力线通信的建模问题,着重讨论在高频时电机输入阻抗的特性下,电机模型的建立.通过实验测量得到电机和电力线在频率100 kHz～40 MHz的输入阻抗特性曲线,并分析高频输入阻抗的谐振特点.在Matlab中,提出基于阻抗公式的分析法、最小均方值误差估计法以及最优化方法进行模型的参数识别,将得到的参数代入模型中可以得到电机的阻抗模型.电机模型的精确度可以通过仿真曲线和测量曲线的逼近程度看出,从结果看仿真得到的阻抗曲线跟实际测量的阻抗曲线走向基本一致.     

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模糊神经网络在GPS高程转换中的应用

介绍了T-S模糊神经网络的基本原理以及如何确定GPS高程转换的模糊神经网络模型,并采用该模型对实测数据进行了计算分析。结果表明,模糊神经网络能够对小区域GPS高程做出比较准确定的拟合,从而能够为GPS高程转换提供一种较好的方法,能够满足实际工程需要。     

高程基面问题浅议

介绍国内现存的几种高程基面,分析工程中使用高程基面时存在的问题,提出测量系统规范化、标准化的紧迫性和必要性。     

基于庄河市空间大地全面控制网谈似大地水准面的确定及精度分析

介绍了通过布设足够密度且分布均匀的GPS水准联测点,建立庄河市辖区4086 km2的高精度、高分辨率的似大地水准面数学模型的原理和方法.