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151.
The estimation of sediment yield is important in design, planning and management of river systems. Unfortunately, its accurate estimation using traditional methods is difficult as it involves various complex processes and variables. This investigation deals with a hybrid approach which comprises genetic algorithm-based artificial intelligence (GA-AI) models for the prediction of sediment yield in the Mahanadi River basin, India. Artificial neural network (ANN) and support vector machine (SVM) models are developed for sediment yield prediction, where all parameters associated with the models are optimized using genetic algorithms simultaneously. Water discharge, rainfall and temperature are used as input to develop the GA-AI models. The performance of the GA-AI models is compared to that of traditional AI models (ANN and SVM), multiple linear regression (MLR) and sediment rating curve (SRC) method for evaluating the predictive capability of the models. The results suggest that GA-AI models exhibit better performance than other models.  相似文献   
152.
One of the major aspects of rock-physics forward modelling is to predict seismic behaviour at an undrilled location using drilled well data. It is important to model the rock and fluid properties away from drilled wells to characterize the reservoir and investigate the root causes of different seismic responses. Using the forward modelling technique, it is possible to explain the amplitude responses of present seismic data in terms of probable rock and reservoir properties. In this context, rock-physics modelling adds significant values in the prospect maturation process by reducing the risk of reservoir presence in exploration and appraisal phases. The synthetic amplitude variation with offset gathers from the forward model is compared with real seismic gathers to ensure the fidelity of the existing geological model. ‘Prospect A’ in the study area has been identified from seismic interpretation, which was deposited as slope fan sediments in Mahanadi basin, East Coast of India. The mapped prospect has shown class-I amplitude variation with offset response in seismic without any direct hydrocarbon indicator support. The existing geological model suggests the presence of an excellent gas reservoir with proven charge access from the fetch area, moderate porosity and type of lithology within this fan prospect. But, whether the seismic response from this geological model will exhibit a class-I amplitude variation with offset behaviour or ‘dim spot’ will be visible; the objective of the present study is to investigate these queries. A rock-physics depth trend analysis has been done to envisage the possibilities of class-I reservoir in ‘Prospect A’. Forward modelling, using a combination of mechanical and chemical compaction, shows the synthetic gas gathers at ‘Prospect A’, which are class I in nature. The study has also depicted 2D forward modelling using lithology and fluid properties of discovery well within similar stratigraphy to predict whether ‘dim spot’ will be seen in seismic. The estimated change in synthetic amplitude response has been observed as ∼5% at contact, which suggests that the changes will not be visible in seismic. The study connects the existing geological model with a top-down seismic interpretation using rock-physics forward modelling technique to mature a deep-water exploratory prospect.  相似文献   
153.
Ocean Dynamics - The structure and variability of undercurrents in the East India Coastal Current (EICC), which is the western boundary current system in the Bay of Bengal (BoB), and the mechanisms...  相似文献   
154.
Experiments are conducted in a laboratory flume on the propagation of a surface wave against unidirectional flow with a sediment bed. This article presents the spatial variation of bedforms induced by the wave-blocking phenomenon by a suitably tuned uniform fluid flow and a counter-propagating wave. The occurrence of wave-blocking is confirmed by finding a critical wave frequency in a particular flow discharge in which the waves are effectively blocked and is established using the linear dispersion relation. The purpose of this work is to identify wave-blocking and its influence on the development of bedforms over the sediment bed. Interestingly bedform signatures are observed at a transition of bedforms in three zones, with asymmetric ripples having a steeper slope downstream face induced by the incoming current, followed by flat sand bars beneath the wave-blocking zone and more symmetric ripples below the wave-dominated region at the downstream. This phenomenon suggests that the sediment bed is segmented into three different regions of bed geometry along the flow. The deviations of mean flows, Reynolds stresses, turbulent kinetic energy, and power spectral density due to the wave-blocking phenomenon are presented along the non-uniform flow over sediment bed. The bottom shear stress, bed roughness and stochastic nature of the bedform features are also discussed. The results are of relevance to engineers and geoscientists concerned with contemporary process as well as those interested in the interpretation of palaeoenvironmental conditions from fossil bedforms. © 2019 John Wiley & Sons, Ltd.  相似文献   
155.
The extraction of urban built-up areas is an important aspect of urban planning and understanding the complex drivers and biophysical mechanism of urban climate processes. However, built-up area extraction using Landsat data is a challenging task due to spatio-temporal dynamics and spatially intermixed nature of Land Use and Land Cover (LULC) in the cities of the developing countries, particularly in tropics. In the light of advantages and drawbacks of the Normalized Difference Built-up Index (NDBI) and Built-up Area Extraction Method (BAEM), a new and simple method i.e. Step-wise Land-class Elimination Approach (SLEA) is proposed for rapid and accurate mapping of urban built-up areas without depending exclusively on the band specific normalized indices, in order to pursue a more generalized approach. It combines the use of a single band layer, Normalized Difference Vegetation Index (NDVI) image and another binary image obtained through Logit model. Based on the spectral designation of the satellite image in use, a particular band is chosen for identification of water pixels. The Double-window Flexible Pace Search (DFPS) approach is employed for finding the optimum threshold value that segments the selected band image into water and non-water categories. The water pixels are then eliminated from the original image. The vegetation pixels are similarly identified using the NDVI image and eliminated. The residual pixels left after elimination of water and vegetation categories belong either to the built-up areas or to bare land categories. Logit model is used for separation of the built-up areas from bare lands. The effectiveness of this method was tested through the mapping of built-up areas of the Kolkata Metropolitan Area (KMA), India from Thematic Mapper (TM) images of 2000, 2005 and 2010, and Operational Land Imager (OLI) image of 2015. Results of the proposed SLEA were 95.33% accurate on the whole, while those derived by the NDBI and BAEM approaches returned an overall accuracy of 83.67% and 89.33%, respectively. Comparisons of the results obtained using this method with those obtained from NDBI and BAEM approaches demonstrate that the proposed approach is quite reliable. The SLEA generates new patterns of evidence and hypotheses for built-up areas extraction research, providing an integral link with statistical science and encouraging trans-disciplinary collaborations to build robust knowledge and problem solving capacity in urban areas. It also brings landscape architecture, urban and regional planning, landscape and ecological engineering, and other practice-oriented fields to bear together in processes for identifying problems and analyzing, synthesizng, and evaluating desirable alternatives for urban change. This method produced very accurate results in a more efficient manner compared to the earlier built-up area extraction approaches for the landscape and urban planning.  相似文献   
156.
157.
Chatterjee  T.N. 《Solar physics》1999,186(1-2):421-429
A mixture of periodic and chaotic components makes the detection of chaos difficult. The periodic components are sought in the solar UV time series by the Maximum Entropy Method and are removed by a digital notch filter. The filtered output is subjected to investigation for chaotic behavior by three different techniques. (1) Fixed-size method for attractor dimension determination; (2) sensitive initial dependence via prediction error; (3) trajectory direction estimation. All the investigation points to the existence of a chaotic attractor of fractional dimension.  相似文献   
158.
159.
An extensive aerosol sampling program was conducted during January-December 2006 over Kolkata (22o33?? N and 88o20?? E), a mega-city in eastern India in order to understand the sources, distributions and properties of atmospheric fine mode aerosol (PM2.5). The primary focus of this study is to determine the relative contribution of natural and anthropogenic as well as local and transported components to the total fine mode aerosol loading and their seasonal distributions over the metropolis. The average concentrations of fine mode aerosol was found to be 71.2?±?25.2???gm-3 varying between 34.5???gm-3 in monsoon and 112.6???gm-3 in winter. The formation pathways of major secondary aerosol components like nitrate and sulphate in different seasons are discussed. A long range transport of dust aerosol from arid and semi-arid regions of western India and beyond was observed during pre-monsoon which significantly enriched the total aerosol concentration. Vehicular emissions, biomass burning and transported dust particles were the major sources of PM2.5 from local and continental regions whereas sea-salt aerosol was the major source of PM2.5 from marine source regions.  相似文献   
160.
Scheelite and rutile from several metaturbidite-hosted gold-bearing quartz vein deposits of the Meguma Terrane of Nova Scotia were analyzed for trace elements including rare earth elements, niobium and tantalum. Scheelites have high concentrations of Sr, Nb, Y and rare earth elements (REE) with bell-shaped chondrite-normalized REE patterns accompanied by both positive and negative Eu anomalies. They also have high Nb/Ta ratios (80–300). Three distinct trace element types of the scheelites are interpreted to reflect chemical differences in the pulses of hydrothermal fluids. Hydrothermal rutiles have high contents of W (up to 4.2 wt.% WO3), are rich in Ta compared to Nb and have a very low Nb/Ta ratio (~0.3). Hydrothermal fluids which produced both scheelite with a high Nb/Ta and rutile with a low Nb/Ta ratio are an efficient medium for fractionation of this ratio although these two minerals play an important role during the process.  相似文献   
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