Application of Grey Correlation Degree Analysis in Broad Bean Strain Screening

[Objectives] The aim was to clarify the target and approach to purifying and selecting Baoshan Touxinlv broad bean. [Methods] In 2012,5 homozygous strains were selected successfully as the material,and completely randomized block arrangement was adopted with 3 repeated trials to analyze the effects of plant height,effective length of podding branches,branch number per plant,pod number per plant,grain number per pod and 100-grain weight on the yield of each plant in the system. [Results] The results showed that the effects of the various factors on the yield of Baoshan broad beans were in the order of grain number per pod 〉 effective length of podding branches 〉 100-grain weight 〉 pod number per plant 〉 branch number per plant 〉 plant height. [Conclusions]In breeding new strains of Baoshan broad beans,under the premise of ensuring the seed nature and quality of the original variety,priority should be given to the gain number per pod and the increment of effective length of podding branches,followed by the pod number per plant,branch number per plant,plant height,which is the best way to breed new strains of Baoshan Touxinlv broad beans.

Application of grey weighted related degree to the ambient air quality assessment

It is difficult to establish the integrated method to assess the ambient air quality because the atmospheric environmental system is composed of several environmental elements, which contains many contanination factors. In view of the typical grey system character of the monitored data in the ambient air, this paper introduces the weighted value to obtain related degree during applying the method of grey related degree analvsis to assess ambient air quality by each polluting factor producing different effects on the environment quality. This method could give more reasonable and reliable evaluating results. Taking the monitored data of Harbin, a provincial city of Heilongjiang, for example in this paper, the result of assessment by this method was coincide,It with the actual environmental quality of Harbin.

Identification of Time-Varying Modal Parameters for Thermo-Elastic Structure Subject to Unsteady Heating

A time-varying modal parameter identification method combined with Bayesian information criterion(BIC)and grey correlation analysis(GCA)is presented for a kind of thermo-elastic structures with sparse natural frequencies and subject to an unsteady temperature field.To demonstrate the method,the thermo-elastic structure to be identified is taken as a simply-supported beam with an axially movable boundary and subject to both random excitation and an unsteady temperature field,and the dynamic outputs of the beam are first simulated as the measured data for the identification.Then,an improved time-varying autoregressive(TVAR)model is generated from the simulated input and output of the system.The time-varying coefficients of the TVAR model are expanded as a finite set of time basis functions that facilitate the time-varying coefficients to be time-invariant.According to the BIC for preliminarily determining the scope of the order number,the grey system theory is introduced to determine the order of TVAR and the dimension of the basis functions simultaneously via the absolute grey correlation degree(AGCD).Finally,the time-varying instantaneous frequencies of the system are estimated by using the recursive least squares method.The identified results are capable of tracking the slow time-varying natural frequencies with high accuracy no matter for noise-free or noisy estimation.

Fusion and Classification of Beijing-1 Small Satellite Remote Sensing Image for Land Cover Monitoring in Mining Area

In order to promote the application of Beijing-1 small satellite(BJ-1) remote sensing data,the multispectral and panchromatic images captured by BJ-1 were used for land cover classification in Pangzhuang Coal Mining.An improved Intensity-Hue-Saturation(IHS) fusion algorithm is proposed to fuse panchromatic and multispectral images,in which intensity component and panchromatic image are combined using the weights determined by edge pixels in the panchromatic image identified by grey absolute correlation degree.This improved IHS fusion algorithm outper-forms traditional IHS fusion method to a certain extent,evidenced by its ability in preserving spectral information and enhancing spatial details.Dempster-Shafer(D-S) evidence theory was adopted to combine the outputs of three member classifiers to generate the final classification map with higher accuracy than that by any individual classifier.Based on this study,we conclude that Beijing-1 small satellite remote sensing images are useful to monitor and analyze land cover change and ecological environment degradation in mining areas,and the proposed fusion algorithms at data and decision levels can integrate the advantages of multi-resolution images and multiple classifiers,improve the overall accuracy and produce a more reliable land cover map.