关于改进的Encke方法中参考轨道的选择和校正

对于改进的Ｅｎｃｋｅ方法，选择适当的参考轨道是一个关键．然而，对于人造地球卫星长弧轨道计算，目前所给出的几种参考轨道均需要逐段校正，这将给定轨问题带来附加的复杂性．本文将仔细探讨如何选择参考轨道和减少校正次数．     

Exurbia from the bottom-up: Confronting empirical challenges to characterizing a complex system

We describe empirical results from a multi-disciplinary project that support modeling complex processes of land-use and land-cover change in exurban parts of Southeastern Michigan. Based on two different conceptual models, one describing the evolution of urban form as a consequence of residential preferences and the other describing land-cover changes in an exurban township as a consequence of residential preferences, local policies, and a diversity of development types, we describe a variety of empirical data collected to support the mechanisms that we encoded in computational agent-based models. We used multiple methods, including social surveys, remote sensing, and statistical analysis of spatial data, to collect data that could be used to validate the structure of our models, calibrate their specific parameters, and evaluate their output. The data were used to investigate this system in the context of several themes from complexity science, including have (a) macro-level patterns; (b) autonomous decision making entities (i.e., agents); (c) heterogeneity among those entities; (d) social and spatial interactions that operate across multiple scales and (e) nonlinear feedback mechanisms. The results point to the importance of collecting data on agents and their interactions when producing agent-based models, the general validity of our conceptual models, and some changes that we needed to make to these models following data analysis. The calibrated models have been and are being used to evaluate landscape dynamics and the effects of various policy interventions on urban land-cover patterns.     

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.     

胶州湾东北部岸滩改造方案的讨论

本文根据胶州湾东北部岸滩目前污染严重、脏乱不堪的现状及城市总体规划的要求.提出了胶州湾东北部岸滩的改造意见.着重从海洋动力、生态、水量平衡的角度论证了改造工程的必要性和可行性。     

Genetic Diversity in Marine Molluscs: A Test of the Niche-Width Variation Hypothesis

Abstract. A test of the niche width variation hypothesis was conducted in the three Mediterranean littoral species of the family Trochidae: Monodonta turbinata, M. turbiformis and Gibbula richardi. Allozymic variation encoded by 26 gene loci was analyzed, and the levels of polymorphism (P), heterozygosity (H) and allele diversity per locus (A) were estimated and appear to support the niche-width variation hypothesis. The broad-niche species, M. turbiformis and G. richardi are more polymorphic and heterozygous than the relatively narrow-niche M. turbinata (P = 0.571; 0.731 and 0.417; H = 0.108; 0.116 and 0.078; A = 2.025; 2.489 and 1.965, respectively).     

Investigation and sensitivity analysis of a mechanistic phytoplankton model implemented in a new modular numerical tool (Eco3M) dedicated to biogeochemical modelling

A new class of phytoplankton models with a mechanistic basis has been presented in a companion paper (Baklouti, M., Diaz, F., Pinazo, C., Faure, V., Queguiner, B., 2006. Investigation of mechanistic formulations depicting phytoplankton dynamics for models of marine pelagic ecosystems. Progress in Oceanography). It is the default class of models implemented in our new numerical tool Eco3M, which is dedicated to Ecological, Mechanistic and Modular Modelling. A brief overview of its main features is given in Section 2 of the present paper. In the next sections, a particular phytoplankton model among the aforementioned class has been tested with special emphasis on the mechanistic photosynthesis component relating the photosynthetic rate to the proportion of open photosystems II. The present study encompasses several essential steps that are inherent to any modelling, including model reduction, model sensitivity analysis and comparison of model outputs with experiments. The global sensitivity analysis of the plankton model for one-at-a-time parameter perturbations revealed a restricted set of parameters having major influence on the model outputs. Sensitivity tests involving simultaneous parameter perturbations within the range actually encountered in the literature provided a confidence interval for the outputs. Chemostat experiments performed on nitrate-limited diatoms grown under low (LL) and high-light (HL) conditions have been used for comparison with model outputs. The good fit between measured data and model outputs using the same parameter values in both the LL and HL cases demonstrates the ability of our model to represent the main features of phytoplankton dynamics including photoacclimation. Finally, Eco3M is ultimately intended to include explicit bacterial and zooplankton compartments, as well as to be coupled with ocean circulation models, but the intrinsic behavior of the phytoplankton model has been investigated first, independently of physical forcing.     

Inverse reconstructions of ecosystem flows in investigating regime shifts: impact of the choice of objective function

Inverse analysis is increasingly used in ecosystem modelling to objectively reconstruct a large number of unknown flows or interactions from a small number of observations. This type of analysis may be useful in relating observed regime shifts in ecosystem structure to underlying processes. Inversions of ecosystem flow networks currently use a constrained least-squares solution which at the same time minimizes the squared norm (the sum of squares) of the reconstructed flows. This minimum norm (MN) inversion is thought to be a parsimonious solution to the ecosystem flow inverse problem, but it may well not reflect how ecosystems are organised. It has been proposed instead that ecosystems evolve to maximize energy/mass flows or that they maximize the information content of the network weighted by ecosystem flows (ascendancy). We used simulated inverse experiments, where inverse analyses are applied to simulations of flow networks, to explore objective functions different than the MN generally used. We could not compute inverse solutions that maximize ascendancy because the objective function is unbounded. We could calculate inversions that maximize flows; however, these generally overestimated the simulated flows, even though the simulations were designed to maximize flows. It appears that the ecosystem flow inverse problem is too under-determined (too few data relative to the number of unknowns) to allow the use of these maximizing goal functions. We introduce a new minimization that simultaneously minimizes the squared flows and the squared differences between flows. This smoothing minimization makes the inverse flows as even as possible and it helps with some technical issues with MN inversions. The simulated inverse experiments indicated that this smoothed norm (SM) is the most robust in comparative analyses of contrasting ecosystem states, such as those that can be associated with regime shifts. Like the MN inversion, the SM inversion has no ecological basis. However, it is a conservative norm that is less likely to produce false differences between the dynamics of regimes.     

Sea-level fluctuations in a coastal lagoon

Sea-level observations made during December, 1979, at six stations in Great South Bay (which is a coastal lagoon on the south shore of Long Island, New York) reveal that there were significant subtidal fluctuations in addition to the tidal oscillations. Harmonic analysis of the tidal oscillations of sea level indicates that M₂ is the dominant tidal constituent. The M₂ amplitude, however, suffered a more than 50% reduction in the interior of the Bay due largely to the narrow inlet. The subtidal sea level fluctuations within the Bay were forced primarily by the low-frequency fluctuations of the adjacent shelf water. The active subtidal exchange induced by this Bay-shelf coupling appeared to have suffered only minor attenuation within the Bay. As a consequence, the variance associated with subtidal sea level fluctuations was greater than that associated with the tidal oscillations over most of Great South Bay.     

Numerical modeling of long waves in shallow water using Incremental Differential Quadrature Method

Incremental Differential Quadrature Method (IDQM) as a rapid and accurate method for numerical simulation of Nonlinear Shallow Water (NLSW) waves is employed. To the best of authors’ knowledge, this is the first endeavor to exploit DQM in coastal hydraulics. The one-dimensional NLSW equations and related boundary conditions are discretized in space and temporal directions by DQM rules and the resulting system of equations are used to compute the state variables in the entire computational domain. It was found that the splitting of total simulation time into a number of smaller time increments, could significantly enhance the performance of the proposed method. Furthermore, results of this study show two main advantages for IDQM compared with other conventional methods, namely; unconditional stability and minimal computational effort. Indeed, using IDQM, one can use a few grid points (in spatial or time direction) without imposing any stability condition on the time step to obtain an accurate convergent solution.     

A phase-averaged Boussinesq model with effective description of carrier wave group and associated long wave evolution

From the phase-resolving improved Boussinesq equations (Beji and Nadaoka, Ocean Engineering 23 (1996) 691), a phase-averaged Boussinesq model for water waves is derived by more effectively describing carrier wave groups and accompanying long wave evolution with less CPU time. Linear shoaling characteristics of carrier wave equations are investigated and found to agree exactly with the analytical expression obtained from the constancy of energy flux for the improved Boussinesq equations themselves, showing that the present model equations are the results of a consistent derivation procedure regarding energy considerations. Numerical simulations of the derived equations for the single wave group and narrow-banded random waves show the validity of the present model and its high performance, especially on the CPU time.