几种大型中文商情数据库的对比分析

本文从基本情况、收录内容、检索功能、输出形式等几个方面对《中国财经报刊数据库》、《中国经济信息网—— (教育专版 )》、《中国资讯行数据库》、《国务院发展研究中心信息网》

Neural Network Nonlinear Predictive Control Based on Tent-map Chaos Optimization

With the unique erggdicity, i rregularity, and.special ability to avoid being trapped in local optima, chaos optimization has been a novel global optimization technique and has attracted considerable attention for application in various fields, such as nonlinear programming problems. In this article, a novel neural network nonlinear predic-tive control （NNPC） strategy baseed on the new Tent-map chaos optimization algorithm （TCOA） is presented. Thefeedforward neural network＇is used as the multi-step predictive model. In addition, the TCOA is applied to perform the nonlinear rolling optimization to enhance the convergence and accuracy in the NNPC. Simulation on a labora-tory-scale liquid-level system is given to illustrate the effectiveness of the proposed method.

Optimizing neural networks by genetic algorithms for predicting particulate matter concentration in summer in Beijing

We developed and tested an improved neural network to predict the average concentration of PM10(particulate matter with diameter smaller than 10 ?m) several hours in advance in summer in Beijing.A genetic algorithm optimization procedure for optimizing initial weights and thresholds of the neural network was also evaluated.This research was based upon the PM10 data from seven monitoring sites in Beijing urban region and meteorological observation data,which were recorded every 3 h during summer of 2002.Two neural network models were developed.Model I was built for predicting PM10 concentrations 3 h in advance while Model II for one day in advance.The predictions of both models were found to be consistent with observations.Percent errors in forecasting the numerical value were about 20.This brings us to the conclusion that short-term fluctuations of PM10 concentrations in Beijing urban region in summer are to a large extent driven by meteorological conditions.Moreover,the predicted results of Model II were compared with the ones provided by the Models-3 Community Multiscale Air Quality(CMAQ) modeling system.The mean relative errors of both models were 0.21 and 0.26,respectively.The performance of the neural network model was similar to numerical models,when applied to short-time prediction of PM10 concentration.

Modeling water and carbon fluxes above summer maize field in North China Plain with back-propagation neural networks

In this work, datasets of water and carbon fluxes measured with eddy covariance technique above a summer maize field in the North China Plain were simulated with artificial neural networks (ANNs) to explore the fluxes responses to local environmental variables. The results showed that photosynthetically active radiation (PAR), vapor pressure deficit (VPD), air temperature (T) and leaf area index (LAI) were primary factors regulating both water vapor and carbon dioxide fluxes. Three-layer back-propagation neural networks (BP) could be applied to model fluxes exchange between cropland surface and atmosphere without using detailed physiological information or specific parameters of the plant.

Assessment for Production and Operation Ability of Medium and Small-sized Enterprises Based on Neural Network

In order to improve production and operation ability of medium and small-sized enterprises, an assessment-index system of production and operation ability was proposed, and a corresponding assessment model was established based on BP neural network. The conjunction weights of the neural network were continuously modified from output layer to input layer in the process of neural network training to reduce the errors between the anticipated and actual outputs. The results from an example show that this method is reliable and feasible. The production and operation abilitv of an enterorise with assessed result of 0.833 is fairly oowerful, and that with assessed result of 0.644 is average.

How Chinese Financial Centers Integrate into Global Financial Center Networks:An Empirical Study Based on Overseas Expansion of Chinese Financial Service Firms

The increasing globalization of the Chinese economy has been enabled by both Chinese financial institutions operating globally as well as international firms operating within China. In geographical terms, this has been organized through a number of strategic cities serving as gateways for the exchange of financial functions, products and practices between China and the global economy. Drawing on location data of financial service firms in China listed on stock exchanges in Shenzhen, Shanghai and Hong Kong, this paper shows that Chinese financial firms are expanding globally and how Chinese financial centers are positioned and connected in the urban networks shaped by these financial service firms. It is found that Hong Kong, China, holds strategic positions in the integration of Chinese cities into global financial center networks, and that establishing a foothold in global financial centers such as New York and London has been a priority for Chinese financial institutions. The increasing capital flows directed by Chinese financial institutionssuggests a shifting global financial geography, with numerous Chinese cities playing increasingly important roles within global financial center networks.

Establishing and validating a spotted tongue recognition and extraction model based on multiscale convolutional neural network

Objective In tongue diagnosis,the location,color,and distribution of spots can be used to speculate on the viscera and severity of the heat evil.This work focuses on the image analysis method of artificial intelligence(AI)to study the spotted tongue recognition of traditional Chinese medicine(TCM).Methods A model of spotted tongue recognition and extraction is designed,which is based on the principle of image deep learning and instance segmentation.This model includes multiscale feature map generation,region proposal searching,and target region recognition.Firstly,deep convolution network is used to build multiscale low-and high-abstraction feature maps after which,target candidate box generation algorithm and selection strategy are used to select high-quality target candidate regions.Finally,classification network is used for classifying target regions and calculating target region pixels.As a result,the region segmentation of spotted tongue is obtained.Under non-standard illumination conditions,various tongue images were taken by mobile phones,and experiments were conducted.Results The spotted tongue recognition achieved an area under curve(AUC)of 92.40%,an accuracy of 84.30%with a sensitivity of 88.20%,a specificity of 94.19%,a recall of 88.20%,a regional pixel accuracy index pixel accuracy(PA)of 73.00%,a mean pixel accuracy(m PA)of73.00%,an intersection over union(Io U)of 60.00%,and a mean intersection over union(mIo U)of 56.00%.Conclusion The results of the study verify that the model is suitable for the application of the TCM tongue diagnosis system.Spotted tongue recognition via multiscale convolutional neural network(CNN)would help to improve spot classification and the accurate extraction of pixels of spot area as well as provide a practical method for intelligent tongue diagnosis of TCM.

Ecosystem Health Assessment of Honghu Lake Wetland of China Using Artificial Neural Network Approach

Honghu Lake,located in the southeast of Hubei Province,China,has suffered a severe disturbance during the past few decades.To restore the ecosystem,the Honghu Lake Wetland Protection and Restoration Demonstration Project(HLWPRDP) has been implemented since 2004.A back propagation(BP) artificial neural network(ANN) approach was applied to evaluatinig the ecosystem health of the Honghu Lake wetland.And the effectiveness of the HLWPRDP was also assessed by comparing the ecosystem health before and after the project.Particularly,12 ecosystem health indices were used as evaluation parameters to establish a set of three-layer BP ANNs.The output is one layer of ecosystem health index.After training and testing the BP ANNs,an optimal model of BP ANNs was selected to assess the ecosystem health of the Honghu Lake wetland.The result indicates that four stages can be identified based on the change of the ecosystem health from 1990 to 2008 and the ecosystem health index ranges from morbidity before the implementation of HLWPRDP(in 2002) to middle health after the implementation of the HLWPRDP(in 2005).It demonstrates that the HLWPRDP is effective and the BP ANN could be used as a tool for the assessment of ecosystem health.

Incentive allocation of shared property in transportation industries with network characteristics

Industries with network characteristics always have some special features, which differ from the ordinary business companies. Some scholars hold the theoretical viewpoint that these industries bear the characteristics of natural monopoly, externality, measurement difficulty, etc. However, all these theories can explain why the network industries, especially prominent in transportation industries, are confronted with many difficulties in their process of reform and reorganization. But, there is something deep-seated that can explain why network industries such as railway, highway, aviation, telecommunication, water, gas, etc. have the characteristics of natural monopoly. The paper holds that： （1） Shared property in transportation industries such as the network infrastructure, station and marshalling yard, dispatch and control right, serves more than two enterprises or even hundreds of relative enterprises. （2） Shared property makes it possible for great amount of product quantity to share the sunken cost. Therefore, economy of scale and economy of scope thus exist in transportation sectors, which is called network economy. （3） From the input and output relationships in transportation industries with network features, there exists a law of increasing returns to scale, which is opposite to the classic economy theory that diminishing returns to scale will appear finally. Why？ It is because of the existence of shared property. Not only production cost, but also the transaction cost among transportation enterprises can be reduced. （4） We establish a quantitative model to testify the theory. The implication is that, the lack of incentive allocation is, if not all, one reason causing the usage inefficiency of the rights concerned. The low efficiency manifests in two aspects： the first one is the organization boundary, that is, transportation enterprises are not real enterprises at present. The second one is the so-called mixed task equilibrium of railway affairs. We haven＇t separated the shared property from the private ones.

Application of Nonlinear Predictive Control Based on RBF Network Predictive Model in MCFC Plant

This paper described a nonlinear model predictive controller for regulating a molten carbonate fuel cell (MCFC). A detailed mechanism model of output voltage of a MCFC was presented at first. However, this model was too complicated to be used in a control system. Consequently, an off line radial basis function (RBF) network was introduced to build a nonlinear predictive model. And then, the optimal control sequences were obtained by applying golden mean method. The models and controller have been realized in the MATLAB environment. Simulation results indicate the proposed algorithm exhibits satisfying control effect even when the current densities vary largely.

Artificial neural network modeling of water quality of the Yangtze River system:a case study in reaches crossing the city of Chongqing

An effective approach for describing complicated water quality processes is very important for river water quality management. We built two artificial neural network(ANN) models,a feed-forward back-propagation(BP) model and a radial basis function(RBF) model,to simulate the water quality of the Yangtze and Jialing Rivers in reaches crossing the city of Chongqing,P. R. China. Our models used the historical monitoring data of biological oxygen demand,dissolved oxygen,ammonia,oil and volatile phenolic compounds. Comparison with the one-dimensional traditional water quality model suggest that both BP and RBF models are superior; their higher accuracy and better goodness-of-fit indicate that the ANN calculation of water quality agrees better with measurement. It is demonstrated that ANN modeling can be a tool for estimating the water quality of the Yangtze River. Of the two ANN models,the RBF model calculates with a smaller mean error,but a larger root mean square error. More effort to identify out the causes of these differences would help optimize the structures of neural network water-quality models.

Telecentres in Mountain Regions-A Peruvian Case Study of the Impact of Information and Communication Technologies on Remoteness and Exclusion

Communities in developing country mountain areas,in part due to their remoteness,find themselves excluded from social,political and economic systems; and excluded from access to resources. This paper aims to study the impact of information and communication technologies (ICTs) on remoteness and exclusion. It utilises two models - the resource movement framework,and the "information chain" - to analyse a telecentre in one district of mountainous Huancavelica,Peru's poorest region,set in the high Andes. It finds ICTs enabling new and positive resource flows for the two key user groups:teenaged school students and young farmers. These help to maintain social networks. They also support information searches that have improved agricultural practice where other information chain resources have been available. But non-use and ineffective use of the telecentre are found where information chain resources are lacking. ICTs have some impacts on intangible elements of remoteness. In this particular example,they also offer access to some previously-excluded resources. But they have not really addressed the systematic exclusions faced by mountain communities. And they so far appear to be a technology of inequality; favouring those residents who begin with better resource endowments.The paper concludes by offering some recommendations for mountain ICT project practice.

Research on the application of the data mining technology in the electronic commerce network marketing

With the rapid development of China＇s reform and opening up and the socialist market economy, the development of Internet technology has promoted the prosperity of e-commerce, and further promoted the rapid development of China＇s economy. Data mining technology is an advanced science and technology, which has important implications for the e-commerce data processing. Through the summary of the data mining technology, this article puts forward the application of data mining technology in electronic commerce, in order to better promote the development of electronic commerce.

Power-line Modem over the Low Voltage Grid Using Direct Sequence Spread Spectrum Techniques

Power-line networks are designed to deliver electricity. They reach most of the domiciles and other buildings nowadays, so most of the people have access to it. On the other hand the backbone for the communications networks is not available in all countries especially the developing ones. A high cost and changing the design for the networks may be needed to construct this backbone. If data can be transmitted over the power-line networks, a recognized cost and time save can be achieved. In Egypt, the infrastructure is not always available for constructing a communications network backbone due to the already designed buildings before the need for these backbones. In this paper, we overcome this problem by designing a reliable Power-line Modem that operates safely on the low voltage grid. The modem is based on the Direct Sequence Spread Spectrum technique. It uses the mains zero crossing as an efficient way for the synchronization between the transmitter and the receiver. The Modem takes into account the problems of the Power-line including noise, attenuation and impedance dismatching.

Eukaryotic Promoter Recognition Using Back propagation Neural Network

A new system is developed to recognize promoter sequences from non promoter sequences based on position weight matrix and backpropagation neural network in this paper. The system performs significantly better on the training set and the test set, the mean recognition rate is as high as 99% on the training set and 97% on the testing set. Experimental results demonstrate the effectiveness of the system to recognize the promoter sequences that have been trained and the promoter sequences that have not been seen previously.

A Neural Network Method for Monitoring Snowstorm: A Case Study in Southern China

It has been observed that low temperature, rainfall, snowfall, frost have never occurred over the past 50 years in the southern China, and weather in this area is very complex, so the monitoring equipments are few. Optical and thermal infrared remote sensing is influenced much by clouds, so the passive microwave Advanced Microwave Scanning Radiometer-Earth Observing System （AMSR-E） data are the best choice to monitor and analyze the development of disaster. In order to improve estimation accuracy, the dynamic learn- ing neural network was used to retrieve snow depth. The difference of brightness temperatures of TB18.7v and TB36.sv, TBI8.7H and TB36.sH, TB23,sv and TB89v, TBz3.8H and TB89H are made as four main input nodes and the snow depth is the only one output node of neural network. The mean and the standard deviation of retrieval errors are about 4.8 cm and 6.7 cm relative to the test data of ground measurements. The application analysis indicated that the neural network can be utilized to monitor the change of snow intensity distribution through passive microwave data in the complex weather of the southern China.

APPLICATION OF NOISE REDUCTION METHOD BASED ON CURVELET THRESHOLDING NEURAL NETWORK FOR POLAR ICE RADAR DATA PROCESSING

Due to the demand of data processing for polar ice radar in our laboratory, a Curvelet Thresholding Neural Network (TNN) noise reduction method is proposed, and a new threshold function with infinite-order continuous derivative is constructed. The method is based on TNN model. In the learning process of TNN, the gradient descent method is adopted to solve the adaptive optimal thresholds of different scales and directions in Curvelet domain, and to achieve an optimal mean square error performance. In this paper, the specific implementation steps are presented, and the superiority of this method is verified by simulation. Finally, the proposed method is used to process the ice radar data obtained during the 28th Chinese National Antarctic Research Expedition in the region of Zhongshan Station, Antarctica. Experimental results show that the proposed method can reduce the noise effectively, while preserving the edge of the ice layers.

An Empirical Study on Chinese City Network Pattern Based on Producer Services

Globalization and informatization have accelerated city networking process over the world, which makes research on city network a hot topic in the fields of urban geography and economic geography. With Chinese economic structure adjustment and city economic growth, producer services have begun to play an increasingly important role in city-region networking. This paper employs the methodology of world city network to analyze and explain the spatial development characteristics of China's urban network system based on the data of nationwide producer services enterprise network. The research result indicated that the distribution of producer services network has a positive effect on the development of Chinese city networks. City network connectivity is closely related to the significance of city in producer services development, and the former will gradually decline with the drop of the latter. Accordingly, the 64 cities can be divided into the national central cities, regional central cities, sub-regional central cities and local central cities in accordance with their position and role in the nationwide producer services network. It is concluded that high-grade cities with quality producer services dominate the pattern of Chinese city networks and there emerges three spatial agglomerations of producer services enterprises in Changjiang (Yangtze) River Delta, Zhujiang (Pearl) River Delta and Beijing-Tianjin-Tangshan Economical Region. Moreover, the distribution of different producer services industry varies from city to city, which also affects the characteristics of network development.

Study on Transnational Business Operation Strategy of China Xinhua News Network

The paper firstly discussed the strategic implication of the establishment of China Xinhua News Network Co. Ltd. （referred to as CNC in the paper）. Then, the paper explored the opportunity and threat in the CNC＇s competitive environment, and evaluated the news TV competitiveness of CNC compared with world main news network media based on Delphi method. Based on the strategic management framework of SWOT （strength, weakness, opportunity, and threat）, the paper proposed the developmental strategies of transnational business operation for CNC from the following three area： further expand the coverage and the number of countries entered by CNC, enhance brand effects across the world, and build more new technology experience in the world.

A Research on the Legal Designation and Conception of Consumer Cooling-off Period System

Along with the rapid development of modem China economy, some new business modes and sale areas continuously emerge in markets. For example with the continuous popularity of consumer online shopping, rapid development of TV shopping industry, compared with traditional store sales, in these special sale areas consumers＇ rights and interests are more likely to get harmed. From March 15, 2014, the newly revised ＂China consumer protection law＂ will formally implement cooling-off period legal system in special sale areas.2 Because it is a new system different from ＂obligatory compact principle＂ in traditional civil law, the scholars＇ theoretical research on cooling-off period system is still not mature enough. This paper discusses cooling-off period system from the theoretical level, puts forward the designation problem of cooling-off period system, discusses complete concepts of cooling-off period system, and puts forward its legal characteristics as a new consumer rights.