A modified hydrometeor classification algorithm （HCA） is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based o...A modified hydrometeor classification algorithm （HCA） is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results---especially in the mixed rain-hail region--can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar- detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.展开更多
Supervised classification of hyperspectral images is a challenging task because of the higher dimensionality of a pixel signature. The conventional classifiers require large training data set;however, practically limi...Supervised classification of hyperspectral images is a challenging task because of the higher dimensionality of a pixel signature. The conventional classifiers require large training data set;however, practically limited numbers of labeled pixels are available due to complexity and cost involved in sample collection. It is essential to have a method that can reduce such higher dimensional data into lower dimensional feature space without the loss of useful information. For classification purpose, it will be useful if such a method takes into account the nature of the underlying signal when extracting lower dimensional feature vector. The lifting framework provides the required flexibility. This article proposes the adaptive lifting wavelet transform to extract the lower dimensional feature vectors for the classification of hyperspectral signatures. The proposed adaptive update step allows the decomposition filter to adapt to the input signal so as to retain the desired characteristics of the signal. A three-layer feed forward neural network is used as a supervised classifier to classify the extracted features. The effectiveness of the proposed method is tested on two hyperspectral data sets (HYDICE & ROSIS sensors). The performance of the proposed method is compared with first generation discrete wavelet transform (DWT) based feature extraction method and previous studies that use the same data. The indices used for measuring performance are overall classification accuracy and Kappa value. The experimental results show that the proposed adaptive lifting scheme (ALS) has excellent results with a small size training set.展开更多
Automatic web page classification has become inevitable for web directories due to the multitude of web pages in the World Wide Web. In this paper an improved Term Weighting technique is proposed for automatic and eff...Automatic web page classification has become inevitable for web directories due to the multitude of web pages in the World Wide Web. In this paper an improved Term Weighting technique is proposed for automatic and effective classification of web pages. The web documents are represented as set of features. The proposed method selects and extracts the most prominent features reducing the high dimensionality problem of classifier. The proper selection of features among the large set improves the performance of the classifier. The proposed algorithm is implemented and tested on a benchmarked dataset. The results show the better performance than most of the existing term weighting techniques.展开更多
In Dynamic Global Vegetation Models （DGVMs）, the establishment of woody vegetation refers to flowering, fertiliza- tion, seed production, germination, and the growth of tree seedlings. It determines not only the pop...In Dynamic Global Vegetation Models （DGVMs）, the establishment of woody vegetation refers to flowering, fertiliza- tion, seed production, germination, and the growth of tree seedlings. It determines not only the population densities but also other important ecosystem structural variables. In current DGVMs, establishments of woody plant functional types （PFTs） are assumed to be either the same in the same grid cell, or largely stochastic. We investigated the uncertainties in the competition of establishment among coexisting woody PFTs from three aspects： the dependence of PFT establishments on vegetation states; background establishment; and relative establishment potentials of different PFTs. Sensitivity experi- ments showed that the dependence of establishment rate on the fractional coverage of a PFT favored the dominant PFT by increasing its share in establishment. While a small background establishment rate had little impact on equilibrium states of the ecosystem, it did change the timescale required for the establishment of alien species in pre-existing forest due to their disadvantage in seed competition during the early stage of invasion. Meanwhile, establishment purely fiom background （the scheme commonly used in current DGVMs） led to inconsistent behavior in response to the change in PFT specification （e.g., number of PFTs and their specification）. Furthermore, the results also indicated that trade-off between irtdividual growth and reproduction/colonization has significant influences on the competition of establishment. Hence, further development of es- tablishment parameterization in DGVMs is essential in reducing the uncertainties in simulations of both ecosystem structures and successions.展开更多
基金jointly funded by the National Natural Science Foundation of China (Grant Nos. 41675023, 91337103, 91437101 and 41675029)the Scientific Research Projects of CAMS (Grant Nos. 2016Z005 and 2016LASW-B12)the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant Nos. KYCX17 0880)
文摘A modified hydrometeor classification algorithm （HCA） is developed in this study for Chinese polarimetric radars. This algorithm is based on the U.S. operational HCA. Meanwhile, the methodology of statistics-based optimization is proposed including calibration checking, datasets selection, membership functions modification, computation thresholds modification, and effect verification. Zhuhai radar, the first operational polarimetric radar in South China, applies these procedures. The systematic bias of calibration is corrected, the reliability of radar measurements deteriorates when the signal-to-noise ratio is low, and correlation coefficient within the melting layer is usually lower than that of the U.S. WSR-88D radar. Through modification based on statistical analysis of polarimetric variables, the localized HCA especially for Zhuhai is obtained, and it performs well over a one-month test through comparison with sounding and surface observations. The algorithm is then utilized for analysis of a squall line process on 11 May 2014 and is found to provide reasonable details with respect to horizontal and vertical structures, and the HCA results---especially in the mixed rain-hail region--can reflect the life cycle of the squall line. In addition, the kinematic and microphysical processes of cloud evolution and the differences between radar- detected hail and surface observations are also analyzed. The results of this study provide evidence for the improvement of this HCA developed specifically for China.
文摘Supervised classification of hyperspectral images is a challenging task because of the higher dimensionality of a pixel signature. The conventional classifiers require large training data set;however, practically limited numbers of labeled pixels are available due to complexity and cost involved in sample collection. It is essential to have a method that can reduce such higher dimensional data into lower dimensional feature space without the loss of useful information. For classification purpose, it will be useful if such a method takes into account the nature of the underlying signal when extracting lower dimensional feature vector. The lifting framework provides the required flexibility. This article proposes the adaptive lifting wavelet transform to extract the lower dimensional feature vectors for the classification of hyperspectral signatures. The proposed adaptive update step allows the decomposition filter to adapt to the input signal so as to retain the desired characteristics of the signal. A three-layer feed forward neural network is used as a supervised classifier to classify the extracted features. The effectiveness of the proposed method is tested on two hyperspectral data sets (HYDICE & ROSIS sensors). The performance of the proposed method is compared with first generation discrete wavelet transform (DWT) based feature extraction method and previous studies that use the same data. The indices used for measuring performance are overall classification accuracy and Kappa value. The experimental results show that the proposed adaptive lifting scheme (ALS) has excellent results with a small size training set.
文摘Automatic web page classification has become inevitable for web directories due to the multitude of web pages in the World Wide Web. In this paper an improved Term Weighting technique is proposed for automatic and effective classification of web pages. The web documents are represented as set of features. The proposed method selects and extracts the most prominent features reducing the high dimensionality problem of classifier. The proper selection of features among the large set improves the performance of the classifier. The proposed algorithm is implemented and tested on a benchmarked dataset. The results show the better performance than most of the existing term weighting techniques.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA05110103)the State Key Project for Basic Research Program of China(Grant No.2010CB951801)the National High Technology Research and Development Program of China(863 Program)(Grant No.2009AA122105)
文摘In Dynamic Global Vegetation Models （DGVMs）, the establishment of woody vegetation refers to flowering, fertiliza- tion, seed production, germination, and the growth of tree seedlings. It determines not only the population densities but also other important ecosystem structural variables. In current DGVMs, establishments of woody plant functional types （PFTs） are assumed to be either the same in the same grid cell, or largely stochastic. We investigated the uncertainties in the competition of establishment among coexisting woody PFTs from three aspects： the dependence of PFT establishments on vegetation states; background establishment; and relative establishment potentials of different PFTs. Sensitivity experi- ments showed that the dependence of establishment rate on the fractional coverage of a PFT favored the dominant PFT by increasing its share in establishment. While a small background establishment rate had little impact on equilibrium states of the ecosystem, it did change the timescale required for the establishment of alien species in pre-existing forest due to their disadvantage in seed competition during the early stage of invasion. Meanwhile, establishment purely fiom background （the scheme commonly used in current DGVMs） led to inconsistent behavior in response to the change in PFT specification （e.g., number of PFTs and their specification）. Furthermore, the results also indicated that trade-off between irtdividual growth and reproduction/colonization has significant influences on the competition of establishment. Hence, further development of es- tablishment parameterization in DGVMs is essential in reducing the uncertainties in simulations of both ecosystem structures and successions.
