Neural network and wavelet conjunction model for modelling monthly level fluctuations in Turkey

This paper proposes the application of a conjunction model (neuro‐wavelet) for forecasting monthly lake levels. The neuro‐wavelet (NW) conjunction model is improved combining two methods, discrete wavelet transform and artificial neural networks. The application of the methodology is presented for the Lake Van, which is the biggest lake in Turkey, and Lake Egirdir. The accuracy of the NW model is investigated for 1‐ and 6‐month‐ahead lake level forecasting. The root mean square errors, mean absolute relative errors and determination coefficient statistics are used for evaluating the accuracy of NW models. The results of the proposed models are compared with those of the neural networks. In the 1‐month‐ahead lake level forecasting, the NW conjunction model reduced the root mean square errors and mean absolute relative errors by 87–34% and 86–31% for the Van and Egirdir lakes, respectively. In the 6‐month‐ahead lake level forecasting, the NW conjunction model reduced the root mean square errors and mean absolute relative errors by 34–48% and 30‐46% for the Van and Egirdir lakes, respectively. The comparison results indicate that the suggested model could significantly increase the short‐ and long‐term forecast accuracy. Copyright © 2009 John Wiley & Sons, Ltd.     

Resource Flows of Villages with Contrasting Lifestyles in Nanda Devi Biosphere Reserve, Central Himalaya, India

Resource use efficiency analyses of village ecosystem are necessary for effective and efficient planning of resource utilization. This paper deals with economic and energy input-output analyses of different components of village ecosystem in representative buffer zone villages, which are practicing transhumance and settled way of lifestyles in Nanda Devi Biosphere Reserve （NDBR） of Garhwal Himalaya. While the villages practicing transhumance used various natural resources spatially segregated,the villages practicing settled way of lifestyle have to manage resources from a limited spatial area through rotation and varied extraction intensities. Forests subsidized the production activity in both type of villages and the per capita resource extractions were found to be greater in tran~humance village than settled village. Though crops provided maximum energy, in terms of economic criteria, animal husbandry played important role in both settled and transhumance villages. As villages representing both the situations showed different ways of adjustments to the conservation oriented land use changes, management authority needs to address the eco-development plans fulfilling the aspirations of all people traditionally using the resources of the Reserve to reduce the conflicts and encourage their participation in the conservation of the area.     

GPS掩星技术和电离层反演

系统地介绍了GPS无线电掩星技术的发展现状、系统组成和一些关键技术；论述了利用GPS掩星数据进行电离层反演的理论、模型及相应的计算流程．并结合GPS／MET和CHAMP卫星的实测资料，计算了电子密度剖面，与用其他方法所得结果的对比表明．GPS掩星电离层观测具有精度高、覆盖范围大等特点；最后讨论了GPS掩星技术应用于地震前兆监测的机理和前景。     

Analysis of ERS-2 scatterometer winds and wind-wave calculation for eastern China seas

The wind system over the China seas plays an important role in climate variation there. In this paper, ERS-2 scatterometer winds covering the period of 1998 and the area of 25-41°N, 117-130°E were analyzed and compared to NCEP winds and buoy winds in the same period and location, to assess how well the ERS-2 data reflect the real wind regime, at least for this area. The results indicated that ERS-2 scatterometer winds are closer to buoy observations than NCEP winds. In addition, a new wind-wave growth relation was applied to calculate wave parameters.     

应用灰色聚类分析部署地质找矿工作

本文以汝阳南部铅锌矿成矿预测勘查过程中预测出的３２个含矿单元为例，阐述了如何用灰色系统理论中的灰色聚类分析方法定量地划分预测靶区类别，合理、客观地部署铅锌矿地质找矿工作，取得了令人满意的结果。     

The delesse relation in a concentrically zoned sphere. I. The section-number bias

Zonal areas of a randomly chosen section through a concentrically zoned sphere yield an estimate of the (volumetric) amount of the outer zone which is subject to a large positive bias that decreases rapidly with increase in the number of sections on which the estimate is based. It will not exceed 3% of the amount present if an analysis is based on as many as 8 sections and will be less than 1% if 32 sections are used.     

论网络生产力的结构层次

网络生产力是一个复杂的系统，它包括构成要素层次，渗透性因素层次与组合性因素层次而有别于一般生产力的新质。     

The physical framework of the dependence between channel flow hydrographs and drainage network morphometry

The physical basis of the linkage between magnitude and timing of channel flow hydrographs and drainage network morphometry is reviewed. Small Hortonian and structurally Hortonian networks are analysed using numerical runoff simulation. For Hortonian networks the variability of the geometry of individual channels and subcatchments within each Strahler order has generally little effect upon the overall character of the hydrograph in channels of higher order. If the network is also structurally Hortonian, the analysis of the simultaneous formation, travel, and concentration of the hydrographs in all channels of the network can be simplified to a sequence of one representative hydrograph per channel order. This approach is used in this study. Three major runoff processes control the flow hydrograph characteristics: the overland flow process which determines the water supply to the drainage network; the channel flow process which translates the hydrograph in space and time; and the drainage network process which concentrates and magnifies the flow at the junctions of the drainage network. Functional relations for the hydrograph peak, timing, and flow velocity are presented. For a given uniform rainfall and infiltration rate, the peak of the channel flow hydrograph is shown to increase geometrically with channel order, and its magnitude is directly related to the bifurcation ratio. The travel time of the peak also increases geometrically with channel order, and it is directly related to the channel length ratio over velocity ratio. The flow velocity of the peak changes in a downstream direction as a function of the bifurcation and slope ratio. It was also found that for negligible channel storage the channel flow and drainage network processes do not contribute significantly to the observed nonlinear response of a watershed to precipitation.     

SOFTWARE REVIEWS

software reviews are in this article MACATLAS . Number Cruncher Statistical System (NCSS) TRANSPRO FIRE-ROUTER     

A hybrid Bayesian back‐propagation neural network approach to multivariate modelling

There is growing interest in the use of back‐propagation neural networks to model non‐linear multivariate problems in geotehnical engineering. To overcome the shortcomings of the conventional back‐propagation neural network, such as overfitting, where the neural network learns the spurious details and noise in the training examples, a hybrid back‐propagation algorithm has been developed. The method utilizes the genetic algorithms search technique and the Bayesian neural network methodology. The genetic algorithms enhance the stochastic search to locate the global minima for the neural network model. The Bayesian inference procedures essentially provide better generalization and a statistical approach to deal with data uncertainty in comparison with the conventional back‐propagation. The uncertainty of data can be indicated using error bars. Two examples are presented to demonstrate the convergence and generalization capabilities of this hybrid algorithm. Copyright © 2003 John Wiley & Sons, Ltd.