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Drought occurs frequently in the world and it has great influence on the crops. Satellite remote sensing has been widely used in drought monitoring because of its wide range, fast information and short cycle. Temperature vegetation dryness index based on NDVI-Ts space is widely used to assess drought conditions. In this study, LAI-Ts space, constructed from MODIS MOD15A2 and MOD11A2 products, was...
Compressed sensing can decrease the cost of information acquisition, storage, processing and transmission greatly by using sampling rate far lower than that in the sampling theorem limits to realize the accurate reconstruction of sparse or compressible signal. In this paper, we introduced the basic theory of compressed sensing, and then made an in-depth study of this theory from the angle of the sparsification...
Compressed sensing (CS) is the theory and practice of sub-Nyquist sampling of sparse signals of interest. Perfect reconstruction may then be possible with much fewer than the Nyquist required number of data. In this paper, we consider a distributed multi-view imaging system where each camera at a different location performs independent compressed sensing acquisition of the target scene. At the decoder,...
In applications such as target detection, domain knowledge of sensed data is often available. In this paper, we incorporate the available domain knowledge into clustering process and develop a knowledge-driven Mahalanobis distance-based ART (adaptive resonance theory) clustering algorithm. The strength of the knowledge-driven algorithm is that it can automatically determine the number of clusters...
In this paper, we present a knowledge-based evolving algorithm for data stream clustering. The basic idea of the new algorithm is to divide data stream into frames, and to incorporate knowledge learned in previous frames into clustering of the following ones. Experimental studies have demonstrated that the evolving learning mechanism leads to improved clustering results compared with conventional...
To study the influential degree of energy consumption influential factors impacting on energy consumption is the foundation of reducing energy consumption and saving energy. Energy consumption intensity influential factors decomposition is a class method of measuring the influential degree of energy consumption intensity influential factors impacting on energy consumption intensity. So the research...
Interpersonal communication is supported by many new technologies nowadays. It has important influence on information diffusion. To study the dynamics of interpersonal communication, an agent-based model is built. The model simulates the process that agents construct their global cognitive social network through communication with local neighbors. Agents communicate with each other through social...
Brain information processing is a movement process, and its movement characteristics directly control the behavior and action traits of human being. Firstly, the article introduces a kind of method that revealing brain information processing characteristics by the continuous numerical comparing based on computer. Secondly, ability feature on movement characteristics of brain information processing...
This paper integrates Grossman decomposition model with Logarithmic Mean Divisia Index (LMDI) Decomposition method to construct a new decomposition model concerning industrial pollution factors. We decompose the influencing factors with the constructed model which selects year 2005 to 2008 as analysis period and Chinese industries and SO2 emission of its internal industries as research object. For...
Multi-tenant SaaS software as one of the application pattern in Cloud Computing delivers software thourgh Web to the users by rhe service manner. So, it can reduce the cost of users, and reduce the cost of the maintainess and management by providers. The first problem that must be considered is how to provide the most appropriate tenant to the user according to the business request from the user in...
The traditional Chinese medicine industry is a field that has unique advantage and national characteristics in the industrial field of our country. The evaluation of the enterprise core competence plays an important role in the rapid development of the traditional Chinese medicine industry. In this paper, a comprehensive evaluation model of the Chinese medicine enterprise core competence is proposed...
Chinese medicine is a treasure of Chinese nation as well as a crystallization of Chinese working people's wisdom accumulated over thousands of years, Chinese medicine industry has always been a pivotal position in the pharmaceutical market in China. This paper uses the Gray correlation model based on the theory of information entropy, the method of entropy evaluation is to determine the weight. Using...
Output-input feedback (OIF) Elman neural network is a dynamic feedback network. An improved model is proposed based on the OIF Elman neural network by introducing direction profit factor in this paper. Moreover, the proposed model is applied to forecast the composite index of stock. In addition, some comparisons are also made when the stock exchange is performed using prediction results from OIF Elman...
In a rapidly changing economic environment, the action about the alliance of audit interests acted by certificated public accountant (CPA) and manager of the public company made a great loss for the Company owners, potential investors and the public. The credibility of Certified Public Accountants for the whole has been received unprecedented attention. And the action also brought new challenges for...
Selection of suppliers is the precondition and foundation of supply chain operation. It is an important aspect to choose the best supplier for supply chain management. This paper is aimed to present a fuzzy decision-making approach to deal with the supplier selection problem in supply chain system. In this paper, we can convert the decision matrix into a fuzzy decision matrix and then we use fuzzy...
This paper introduces support vector machine classifiers into entering tone recognition. Not every syllable needs recognition in a statistical way. The recognition accuracy of syllables which need recognition in the support vector machine approach is about 90%, which makes it possible to analyze poems' rhymes and translate Mandarin into many Chinese dialects. The experiments also check the influence...
Sentence similarity measures have taken an increasingly important role in a variety of applications of text knowledge presentation and discovery. Current methods utilize only semantic or syntactic information. We propose a novel method to calculate sentence similarity, which takes into account both semantic information and word order. The experimental results show that our method outperforms existing...
Evaluation index are long been thought as very accurately reflect stock price by people in China. In this paper, we build theory models to study the relationship between volume, P/B (Price-to-Book value Ratio), P/S (Price-to-Sale Ratio) and P/CF (Price-to-Cash Flow Ratio) and stock market volatility. In current China stock market, individual stock price volatility is a complicated function. The resulting...
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