Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.     

Automatic Determination of Stellar Atmospheric Parameters Using Neural Networks and Instance-Based Machine Learning

In this article we show how machine learning methods can beeffectively applied to the problem of automatically predictingstellar atmospheric parameters from spectral information, a veryimportant problem in stellar astronomy. We apply feedforwardneural networks, Kohonen's self-organizing maps andlocally-weighted regression to predict the stellar atmosphericparameters effective temperature, surface gravity and metallicityfrom spectral indices. Our experimental results show that thethree methods are capable of predicting the parameters with verygood accuracy. Locally weighted regression gives slightly betterresults than the other methods using the original dataset asinput, while self-organizing maps outperform the other methods when significant amounts of noise are added. We also implemented a heterogeneous ensemble of predictors, combining the results given by the three algorithms. This ensemble yields better results than any of the three algorithms alone, using both the original and the noisy data.     

Reliability assessment of serviceability performance of braced retaining walls using a neural network approach

In urban environments, one major concern with deep excavations in soft clay is the potentially large ground deformations in and around the excavation. Excessive movements can damage adjacent buildings and utilities. There are many uncertainties associated with the calculation of the ultimate or serviceability performance of a braced excavation system. These include the variabilities of the loadings, geotechnical soil properties, and engineering and geometrical properties of the wall. A risk‐based approach to serviceability performance failure is necessary to incorporate systematically the uncertainties associated with the various design parameters. This paper demonstrates the use of an integrated neural network–reliability method to assess the risk of serviceability failure through the calculation of the reliability index. By first performing a series of parametric studies using the finite element method and then approximating the non‐linear limit state surface (the boundary separating the safe and ‘failure’ domains) through a neural network model, the reliability index can be determined with the aid of a spreadsheet. Two illustrative examples are presented to show how the serviceability performance for braced excavation problems can be assessed using the reliability index. Copyright © 2005 John Wiley & Sons, Ltd.     

U–Pb SHRIMP zircon geochronology and T–t–d history of the Kampa Dome, southern Tibet

Structural, petrographic and geochronologic studies of the Kampa Dome provide insights into the tectonothermal evolution of orogenic crust exposed in the North Himalayan gneiss domes of southern Tibet. U–Pb ion microprobe dating of zircons from granite gneiss exposed at the deepest levels within the dome yields concordia ²⁰⁶Pb/²³⁸U age populations of 506 ± 3 Ma and 527 ± 6 Ma, with no evidence of new zircon growth during Himalayan orogenesis. However, the granite contains penetrative deformation fabrics that are also preserved in the overlying Paleozoic strata, implying that the Kampa granite is a Cambrian pluton that was strongly deformed and metamorphosed during Himalayan orogenesis. Zircons from deformed leucogranite sills that cross-cut Paleozoic metasedimentary rocks yield concordant Cambrian ages from oscillatory zoned cores and discordant ages ranging from ca. 491–32 Ma in metamict grains. Since these leucogranites clearly post-date the metasedimentary rocks they intrude, the zircons are interpreted as xenocrysts that are probably derived from the Kampa granite. The Kampa Dome formed via a series of progressive orogenic events including regional ~ N–S contraction and related crustal thickening (D₁), predominately top-to-N ductile shearing and crustal extension (D₂), top-to-N brittle–ductile faulting and related folding on the north limb of the dome, localized top-to-S faulting on the southern limb of the dome, and crustal doming (D₃), and continued N–S contraction, E–W extension and doming (D₄). Structural and geochronologic variability amongst adjacent North Himalayan gneiss domes may reflect changes in the magnitude of crustal exhumation along the North Himalayan antiform, possibly relating to differences in the mid-crustal geometry of the exhuming fault systems.     

Water and power networks and urban fragmentation in Los Angeles: Rethinking assumed mechanisms

Los Angeles is often described as the epitome of urban fragmentation, a notion which in this context is frequently connected to, or even conflated with urban sprawl. At the same time, the city features integrated water and power networks which have been under public ownership for over 70 years. We thus have an apparent paradox in the context of the debate on ‘splintering urbanism’, between socio-spatial fragmentation and the integration of networks. In discussing the idea that deregulation of infrastructural networks exacerbates urban fragmentation, the authors use the case of Los Angeles in order to highlight the central role of private interests in management decisions concerning infrastructure networks. The authors carry out their analysis in an historical perspective, revealing that network integration and universal access can often serve private interests more than the public good. Urban fragmentation in Los Angeles, they conclude, is the result of a complex process of instrumentalisation of network development and management.     

Church-based social capital, networks and geographical scale: Katrina evacuation, relocation, and recovery in a New Orleans Vietnamese American community

This research examines the role of social capital and networks to explain the evacuation, relocation, and recovery experiences of a Vietnamese American community in New Orleans, Louisiana in the aftermath of Hurricane Katrina. As the single largest community institution, the parish church’s complex bonding and bridging social capital and networks proved particularly critical in part because of its historically based ontological security. The process of evacuation, but especially relocation and recovery, was dependent on deploying co-ethnic social capital and networks at a variety of geographical scales. Beyond the local or community scale, extra-local, regional, and national scales of social capital and networks reproduced a spatially redefined Vietnamese American community. Part of the recovery process included constructing discursive place-based collective-action frames to successfully contest a nearby landfill that in turn engendered social capital and networks crossing ethnic boundaries to include the extra-local African American community. Engaging social capital and networks beyond the local geographical scale cultivated a Vietnamese American community with an emergent post-Katrina cultural and political identity.     

Identifying China’s leading world city: a network approach

This paper reports our research on China’s world cities. Formal network analysis of air passenger linkages for recent years among China’s most populous cities and among many of the world’s largest cities allows us to identify the country’s leading world city from among the leading Mainland candidates, Beijing, Shanghai and Guangzhou. We theorize our findings about China’s world cities in relation to both global forces (and China’s increasing entanglement with them) and the policies and actions of the national state. We examine the national and global urban network through a longitudinal, two-level analysis of airline passenger travel for four time points between about 1990 and 2005. We show that Beijing was China’s leading world city at the beginning of the time period, a status it lost nationally in as early as 1995, and then globally 10 years later. On the other hand Shanghai became China’s leading world city, and it acquired this status first nationally in 2000, and then globally in 2005. The changing status of the Chinese capital corresponds to the country’s increasing involvement with the capitalist world economy. Shanghai’s ascendance as the leading world city in China may indicate that global forces have come to play an increasingly important role relative to that of the developmental state.

PSO-RBFNN模型及其在岩土工程非线性时间序列预测中的应用

岩土工程受力变形演化是一个典型的非线性问题,其演化的高度非线性和复杂性,很难用简单的力学、数学模型描述,但可用粒子群优化径向基神经网络对岩土工程应力、位移非线性时间序列进行动态实时预测。网络径向基层的单元数通过均值聚类法确定后,所有其它参数：中心位置、形状参数、网络权值,均通过粒子群优化算法在全局空间优化确定。工程实例应用表明,该模型预测结果准确、精度高,有良好的应用前景。     

台湾海峡纽形动物初报

首次报道台湾海峡产的纽形动物，包括沙栖原细首纽虫、浮游拟脑纽虫、椒状岩田纽虫、中华平裂纽虫和马顿氏潘丁纽虫，共５种。除椒状岩田纽虫在琉球群岛有报道外，均为东海新记录。     

Images of the seabed in the Faroe-Shetland Channel from commercial 3D seismic data

A large number of 3D deep seismic surveys in the Faroe-Shetland Channel gives continuous coverage over most of the region. These surveys were designed primarily to image depths in excess of 4 km, use low frequency sources and are recorded at low temporal sample rates. However, commercial 3D data can generate highly detailed images of the seabed due to the high spatial sample rate, typically 12.5 m. This is particularly true in waters below 200 m. Despite geophysical artefacts, the images reveal that there are a number of sedimentary processes at work adjacent to and within this channel. On the West Shetland Shelf, iceberg scouring and moraines reflect the impact of glaciation. On the West Shetland slope there is clear evidence for down-slope processes, such as debris flows, linear erosion channels, basal fans and (one case) slope failure. Along-slope processes are also active as indicated by the presence of sediment waves and contourite mounds. On the floor of the basin, polygonal cracking can be observed. The most spectacular feature appears to be the Judd Deeps, a system of cliffs approximately 200 m high and 40 km across. Traditionally, seabed investigation has been performed using high-resolution surveys. This study shows that deep exploration data can also provide useful images of the seafloor.