Based on the meteorological data from 6 stations in Taiyuan, variation characteristics of precipitation, evaporation and temperature in recent 60 years were analyzed, and variation trends of the three meteorological e...
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Based on the meteorological data from 6 stations in Taiyuan, variation characteristics of precipitation, evaporation and temperature in recent 60 years were analyzed, and variation trends of the three meteorological elements in Taiyuan were detected with linear regression method and Mann-Kendall rank correlation method. The results indicate that annual precipitation in Taiyuan during 1951~2006 presented weak decreasing trend which has been obviously since 1990's with average decreasing rate of 13.03mm/10a;among four seasons, decreasing in autumn is the most significant for the rate of 6.13 mm/10a. Annual evaporation in Taiyuan showed obvious decreasing trend from 1970's, and the average rate is 16.28mm/10a, as for seasons, decreasing trend in summer to be the most significant as decreasing rate is 8.42 mm/10a. Annual average temperature presented evident increasing trend from 1980's with the warming rate of 0.38/10a, temperature increasing trend in winter to be more significant than in other seasons, and average rate is 0.61/10a.
In this paper artificial neural networks (ANN) are addressed in order the Greek long-term energy consumption to be predicted. The multilayer perceptron model (MLP) has been used for this purpose by testing several pos...
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In this paper artificial neural networks (ANN) are addressed in order the Greek long-term energy consumption to be predicted. The multilayer perceptron model (MLP) has been used for this purpose by testing several possible architectures in order to be selected the one with the best generalizing ability. Actual recorded input and output data that influence long-term energy consumption were used in the training, validation and testing process. The developed ANN model is used for the prediction of 2005-2008, 2010, 2012 and 2015 Greek energy consumption. The produced ANN results for years 2005-2008 were compared with the results produced by a linear regression method, a support vector machine method and with real energy consumption records showing a great accuracy. The proposed approach can be useful in the effective implementation of energy policies, since accurate predictions of energy consumption affect the capital investment, the environmental quality, the revenue analysis, the market research management, while conserve at the same time the supply security. Furthermore it constitutes an accurate tool for the Greek long-term energy consumption prediction problem, which up today has not been faced effectively. (C) 2009 Elsevier Ltd. All rights reserved.
Background: The replication rate (or fitness) between viral variants has been investigated in vivo and in vitro for human immunodeficiency virus (HIV). HIV fitness plays an important role in the development and persis...
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Background: The replication rate (or fitness) between viral variants has been investigated in vivo and in vitro for human immunodeficiency virus (HIV). HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness. Results: Based on a mathematical model and several statistical methods (least-squares approach and measurement error models), a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1). Conclusions: Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ***, and is publicly available on the Web at http://***/vFitness/.
Confidence intervals are constructed for an unknown correlation coefficient and mathematical expectation using 3s(1) and 2s(1) rules. The intervals make it possible to solve the problem of statistical analysis of the ...
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Confidence intervals are constructed for an unknown correlation coefficient and mathematical expectation using 3s(1) and 2s(1) rules. The intervals make it possible to solve the problem of statistical analysis of the dependence between different random variables. The results obtained are used to analyze the correlation between the content of homocysteine and various clinical indices.
The main purpose of this paper is to predict streamway transition with group method of data handling (GMDH). Therefore, the downstream stream-way transition according to the upstream conditions is forecasted by group ...
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ISBN:
(纸本)9780769536156
The main purpose of this paper is to predict streamway transition with group method of data handling (GMDH). Therefore, the downstream stream-way transition according to the upstream conditions is forecasted by group method of data handling. Five main factors may affect the stream-way transition include inflow position, inflow angle, slope, flow discharge, and sand content of suspended sediment. We selected some cross sections of Ta-Chia River in Taiwan as a case study. The results show that GMDH has better performance than the traditional linear regression method.
This paper studies the realizing progress of data mining in psychological evaluation. Based on the matrix of evaluation data and the actual evaluation work, we propose a kind of generalized linearregression model wit...
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ISBN:
(纸本)9780769534985
This paper studies the realizing progress of data mining in psychological evaluation. Based on the matrix of evaluation data and the actual evaluation work, we propose a kind of generalized linearregression model with convex constraint, named as Evaluation Model, in which the dependent variable and regression coefficients all are unknown. We analyze the algorithm of the model with linear regression method. Then the least square estimate of parameters using the iterative projection algorithm is presented. At last, we use this least square iterative method to work out the parameters of the evaluation model. Our work could be a useful guide for the further research of data mining in psychological evaluation.
We introduce a regressionmethod that fully exploits both global and local information about a set of points in search of a suitable function explaining their mutual relationships. The points are assumed to form a rep...
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TERRA MODIS band 31 was selected as the criterion for doing the radiometric cross-calibration of CBERS-02 IRMSS thermal band. From August to December, 2004, seven times day and night synchronous images of two sensors ...
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TERRA MODIS band 31 was selected as the criterion for doing the radiometric cross-calibration of CBERS-02 IRMSS thermal band. From August to December, 2004, seven times day and night synchronous images of two sensors passing through the Lake Qinghai and Lake Taihu were selected to obtain the cross-calibration data. TERRA MODIS band 31 data were used to conduct out the pupil radiance of CBERS-02 IRMSS band 9 based on the two sensors' spectrum matching, and then the DN values were picked-up from the IRMSS data in the same area. A new model to calculate the radiometric calibration coefficients was carried out in this study. The model is multi-points linear regression method with 7 times day and night synchronous images at different dates and locations. The radiometric cross-calibration coefficients are 8.0567 (gain, unit: DN/(W/m(2)/sr(1)/mu m(1))) and 47.892 (offset, unit: DN). Accuracy estimate of calibration coefficients was carried out. The results show that the calibration coefficients obtained from the linear regression method have a similar precision as TERRA MODIS band 31 ' s. The calibration coefficients can satisfy the quantitative applications of CBERS-02 IRMSS thermal data.
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