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1.
Prediction of Stellar Atmospheric Parameters using Instance-Based Machine Learning and Genetic Algorithms 总被引：1，自引：0，他引：1
In this article we present a method for the automated prediction of stellar atmospheric parameters from spectral indices.
This method uses a genetic algorithm (GA) for the selection of relevant spectral indices and prototypical stars and predicts
their properties, using the k-nearest neighbors method (KNN). We have applied the method to predict the effective temperature,
surface gravity, metallicity, luminosity class and spectral class of stars from spectral indices. Our experimental results
show that the feature selection performed by the genetic algorithm reduces the running time of KNN up to 92%, and the predictive
accuracy error up to 35%.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
2.
Artificial neural network and liquefaction susceptibility assessment: a case study using the 2001 Bhuj earthquake data,Gujarat, India 总被引：2，自引：0，他引：2
D. Ramakrishnan T. N. Singh N. Purwar K. S. Barde Akshay. Gulati S. Gupta 《Computational Geosciences》2008,12(4):491-501
This study pertains to prediction of liquefaction susceptibility of unconsolidated sediments using artificial neural network
(ANN) as a prediction model. The backpropagation neural network was trained, tested, and validated with 23 datasets comprising
parameters such as cyclic resistance ratio (CRR), cyclic stress ratio (CSR), liquefaction severity index (LSI), and liquefaction
sensitivity index (LSeI). The network was also trained to predict the CRR values from LSI, LSeI, and CSR values. The predicted
results were comparable with the field data on CRR and liquefaction severity. Thus, this study indicates the potentiality
of the ANN technique in mapping the liquefaction susceptibility of the area. 相似文献
3.
Using average nutritive values of food actually consumed by individuals, this paper identifies regional concentration of hunger (food poverty) and its changes over time in rural India. There is clearly a heavy concentration of hunger in the coastal states of India, with few exceptions, which has persisted over time. Hunger has declined in about half the states of India but has increased in the remaining half. Unfortunately, it seems to have increased in the states that are relatively prosperous and are surplus producers of food. Hence, increased production of food, though important, does not necessarily reduce hunger. A redeeming conclusion of the study is that there has been a general improvement in the quality of food intake, particularly in the states where food poverty has declined. 相似文献
4.
We present here, for the O and B type stars in the Catalogue of Stellar Ultraviolet Fluxes, an approach which does not require
a precise knowledge of spectral type and luminosity class for derivingE(B-V) colour excesses. The method is based on the use of an UV-visual two-colour diagram; galactic variations in the interstellar
extinction law are analyzed and fully taken into account. Our results have been compared with those derived by using the differences
between observed and intrinsic colours for stars with known spectral classification. The very good agreement in a large number
of cases (94 per cent) demonstrates that our approach permits the derivation of reliable colour excess values for early type
stars even if only a rough spectral classification is available. 相似文献
5.
Evaluating cut slope failure by numerical analysis—a case study 总被引：3，自引：3，他引：0
Slope failure is very common phenomenon in hilly regions, especially in young techno active mountainous like Himalayas. It
is hazardous because of the accompanying progressive movement of the slope-forming material. In order to minimize the landslide
effects, slope failure analysis and stabilization requires in depth understanding of the process that governs the behavior
of the slope. The present article mainly deals with the analysis of the stability of road cut slopes of Rudraprayag Area,
Uttarakhand, India. The area experiences local as well as regional slides every year. Extensive field study was carried out
along the road cut slopes. Laboratory experiments were conducted to determine the various Physio-mechanical properties of
rock mass. These properties have been used as input parameters for the numerical simulation of slope using FLAC3D (Fast Lagrangian
Analysis of Continua) including geological discontinuities. The computed deformations and the stress distribution along the
failure surface are compared with the field observations. The study indicates that the overall slope is unstable except at
the location E where slope is critically stable. The effects of instability have been thoroughly considered and remedial measures
have been recommended. 相似文献
6.
Soma Mukherjee Ujjwal Bhattacharya S. K. Parui Ranjan Gupta Ravi K. Gulati 《Astrophysics and Space Science》1996,239(2):361-373
In this paper we present an application of an artificial neural network model based on a multi-layered backpropagation algorithm for spectral classification of UV data from the International Ultraviolet Explorer (IUE) low dispersion spectra reference atlas. The model used is similar to that of von Hippel et al. (1994), and is found to reduce the classification error as compared to the recently reported results on the same data set (Gulati et al. 1994b). The improved version of the network is much simpler in structure and the training time is reduced by a factor of almost 20. Such networks will prove very useful in efficient classification of large databases
Subject headings: neural networks, stellar spectra, classification 相似文献
7.
Natural Hazards - U. S. Military bases are especially vulnerable to tropical cyclones (TCs) because they concentrate extremely expensive equipment in a small area. A TC hit at a base can result in... 相似文献
8.
Using the Andersen (1991) data on the mass, absolute visual magnitude, the effective surface temperature and the bolometric corrections, new calibrations for the mass vs. absolute visual magnitude and for the bolometric correction vs. effective surface temperature have been derived. Comparison between the latest evolutionary models with the empirical data has been made to test the evolutionary models for the purpose of stellar population studies. 相似文献
9.
ABSTRACTA set of linked optimization models was used to evaluate planning and operation of the proposed Pamba-Achankovil-Vaippar (PAV) water transfer project in India. The shortage of water for irrigation in the Vaippar basin has led to the need for water import. The project consists of three reservoirs. The models were applied at three levels. At Level-1, the projections of water requirement for irrigation in the Vaippar basin at Reservoir-1 were estimated using an LP model. Level-2 was operated at three sub-levels: the first was the determination of the export requirements from the Pamba basin (Reservoir-2) to the Achankovil basin (Reservoir-1); the second was determining the capability of Reservoir-2 to export and sizing of the three reservoirs to meet the above targets was the third sub-level. Integrated reservoir operation and canal irrigation water distribution were done at Level-3. DP models were employed at levels-2 and 3. The linked LP, DP and simulation models were found effective for planning water transfers. 相似文献
10.
Stellar Spectral Classification using Principal Component Analysis and Artificial Neural Networks 总被引：1，自引：0，他引：1
Harinder P.Singh Ravi K.Gulati RanjanGupta 《Monthly notices of the Royal Astronomical Society》1998,295(2):312-318
A fast and robust method of classifying a library of optical stellar spectra for O to M type stars is presented. The method employs, as tools: (1) principal component analysis (PCA) for reducing the dimensionality of the data and (2) multilayer back propagation network (MBPN) based artificial neural network (ANN) scheme to automate the process of classification. We are able to reduce the dimensionality of the original spectral data to very few components by using PCA and are able to successfully reconstruct the original spectra. A number of NN architectures are used to classify the library of test spectra. Performance of ANN with this reduced dimension shows that the library can be classified to accuracies similar to those achieved by Gulati et al. but with less computational load. Furthermore, the data compression is so efficient that the NN scheme successfully classifies to the desired accuracy for a wide range of architectures. The procedure will greatly improve our capabilities in handling and analysing large spectral data bases of the future. 相似文献