Roles and Functions of Tourism Destinations in Tourism Region of South Anhui:A Tourist Flow Network Perspective

Theoretic and practical significance has been highlighted in the research of the roles and functions of destinations,as destinations are restricted by the spatial structure based on tourist flow network from the perspective of relationship.This article conducted an empirical analysis for Tourism Region of South Anhui(TRSA) and revealed the necessity and feasibility of studying the roles and functions of destinations from tourist flow network's perspective.The automorphic equivalence analysis and centrality analysis were used to classify 16 destinations in TRSA into six role types:tourist flow distribution center,hub of tourist flows,passageway destination,common touring destination,attached touring destination,and nearly isolated destination.Some suggestions were given on suitable infrastructure construction and destinations service designs according to their functions in network.This destination role positioning was based on tourist flow network structure in integral and macroscopic way.It provided an important reference for the balanced and harmonious development of all the destinations of TRSA.In addition,this article verified the applicability of social network analysis on tourist flow research in local scale,and expanded this method to destination role and function positioning.

Study of Enterprises Marketing Risk Early Warning System Based on BP Neural Network Model

For effectively early warning the marketing risk caused along with the varied environment, a BP neural network method was introduced on the basis of analyzing the shortcomings of the risk early warning method, and combined with the practical conditions of dairy enterprises, the index system caused by the marketing risk was also studied. The＇principal component method was used for screening the indexes, the grades and critical values of the marketing risk were determined. Through the configuration of BP network, node processing and error analysis, the early warning resuits of the marketing risk were obtained. The results indicate that BP neural network method can be effectively applied through the function approach in the marketing early warning with incomplete information and complex varied conditions.

Role and limitations of rehabilitation-induced neural network remodeling after stroke

There is plenty of evidence that proves the beneficial and reliable effects of rehabilitation therapy,making it the most common treatment for patients with chronic stroke.It is believed that rehabilitation improves functional recovery through neural network remodeling,which is observed as a motor map reorganization or functional connectivity change assessed by intracortical microstimulation or functional magnetic resonance imaging（MRI）.

Analysis on the Transformation of Marketing Strategy and the Countermeasures under the Network Economic Times

In this paper, we theoretically analyze the transformation of marketing strategy and the countermeasures under the network economic times. Network marketing is based on the network technology, including the whole process of marketing activities as a new form of marketing. In this paper, we analyze the issue from the listed perspectives. （1） Ultra space-and-time. The traditional marketing has very strong boundedness to the region, and this boundedness displays, the specifi c transaction can only be closed in the specific region, if the enterprise wants to expand the market share, only then establishes the retailing organization. （2） Interactivity. Network as a media, with the one-on-one interaction, this feature allows companies to basic communicate with consumers, and strengthen consumer participation, to determine the product form, function and the price. （3） The symmetry of information. Consumers can fi nd all kinds of that related products on the Internet information, there are plenty of time to judge the various products and prices. Companies will also be released in a timely manner on the Internet the company’s latest product information. Under this basis, we propose the new idea on the network marketing development direction that will help to build up the more efficient marketing system.

The Network Marketing of Fresh Agricultural Products in China

The paper introduced the connotation of network marketing of fresh agricultural products and analyzed the fundaments of launching the C2C marketing of fresh agricultural products in China.The fundaments mainly cover the development of e-commerce,the transformation of consumption concept,the change of life style and the features of Chinese agricultural production.The developmental status of the C2C marketing of Chinese fresh vegetables and fresh fruits is introduced and the plights,including imperfect rural network infrastructure,inadequate talents specialized in network marketing of fresh agricultural products,uneven quality of agricultural products,immature logistics system,uncertainty existed in faced by the C2C marketing of fresh agricultural products and imperfect governmental protection system,are pointed out.In the end,the developmental trend of Chinese network marketing of fresh agricultural products on the basis of C2C mode is described.

Role of presynaptic calcium stores for neural network dysfunction in Alzheimer＇s disease

Alzheimer’s disease（AD）is the most common form of dementia representing a major problem for public health.In 2017 there were an estimated 50 million patients worldwide and this number is expected to almost double every 20years,reaching 75 million in 2030 and 131.5 million in 2050（https：//www.alz.co.uk/research/statistics）.

Marketing as Innovation Strategy in Non Profit Sector in China： The Network of Influence ＂Guanxi＂

In a globalized world, not only the business market is overlapped but also marketing models take shape within economic systems. While there has been a proliferation in the implementation of marketing in the private sector, this paper provides a useful entry point for the understanding role of marketing within the nonprofit sector focused on China, the second worldwide economic power. A number of senior managers and directors from different Non-Governmental Organizations （NGOs） were interviewed of what they understood marketing to be and how they considered and implemented marketing within organizational strategy. The findings showed that while marketing was identified as an interesting and influential concept, Chinese nonprofit managers generally had a limited understanding of a marketing theory. The article further discusses reasons behind the dynamic based on personalized networks of influence used and the potential implications for nonprofit entities in China, a sector that plays a very noteworthy role in transformative economies.

Application of Data mining in Enterprise Network Marketing

With the rapid development of the Internet, market has been increasingly competitive and competition means are various. Internet Marketing has become a new way for enterprises to grow. Data mining of enterprise network marketing has become the new darling of many business managers.The marketing data will become a key to develop a corporate marketing strategy as an important basis tool. However, many companies now make mistakes in marketing data. They can＇t fully exploit the marketing data.lt can affect the development of enterprise network marketing strategy. This paper is based on the concept of marketing data and outline the importance of data mining for network marketing, then analyze a significant impact on the entemrise network marketin~ strate^w made by marketinR data mininR.

Question of the status quo and countermeasure exit in the China Business Network Marketing

In the application process of the Internet and network marketing, many Chinese companies are actively engaged in practice, and after an exploratory period of time, companies accumulated some experience in a representative model. Such as： Chinese companies have a combination with traditional marketing and purchase advanced software model and then implemented through secondary development, they also change management ideas and systems, etc. These experiences and models can provide an effective and common reference for enterprise＇ s development of China＇ s e-commerce.

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.

The marketing situation and measures of the network sporting goods

This article describes the present situation of network sporting goods and analyzes the problem of sporting goods that exists on the network marketing, in addition, we propose marketing strategies, also, we have some suggestions on the sustainable developmem of the network marketing of sporting goods.

Network marketing strategy research for e-business of maternal and baby＇s products

Maternal and baby＇s product is a special needed class in our country, and the safety of the product quality is very high. Mothers aged at 70s, 80s and 90s have the unique consumption idea and consumption behavior characteristics which have profound significance for merchants. These all have significant influence to enterprise＇s marketing channel construction. Present market situation of Maternal and infant＇s products were summarized in this paper, then consumption psychology and behavior of the buyer are analyzed, and finally put forward the strategy of channel construction of network marketing of Maternal and infant＇s product＇s enterprise.

Network efficiency analysis of Chinese inter-bank market

The inter-bank market network models are constructed based on the inter-bank credit lending relationships, and the network efficiency characters of the Chinese inter-bank market are studied. Since it is impossible to obtain the specific credit data among banks, this paper estimates the inter-bank lending matrix based on the partial information of banks. Thus, directed network models of the Chinese inter-bank market are constructed by using the threshold method. The network efficiency measures and the effects of random attacks and selective attacks on the global efficiency of the inter-bank network are analyzed based on the network models of the inter-bank market. Empirical results suggest that the efficiency measures are sensitive to the threshold, and that the global efficiency is little affected by random attacks, while it is highly sensitive to selective attacks. Properties such as inter-bank market network efficiency would be useful for risk management and stability of the inter-bank market.

Multifunctional Landscape Actor-Network Construction from the Perspective of Rural Tourism Experiences

During the construction of multifunctional landscape(MFL) actor-network, economic, social, and ecological functions presented significant differences, which resulted from the different roles and effects of various heterogeneous actors according to the tourism experience. In Hekou Village at the border area between China and North Korea, the roles and effects of heterogeneous actors during the MFL actor-network construction were analyzed by means of the analytic network process(ANP), which verified the Groundings-Entrepreneurship-Markets(GEM) theoretical framework of the MFL actor-network that assumed tourism experiences were core actors, and economic, social, and ecological landscape actors acted as support. Research results showed that in the MFL actornetwork construction, social and economic functions of landscapes were strong, while ecological and tourism experience functions were weak and that folk customs and land utilization were key actors of the MFL actor-network construction. In the MFL actor-network construction, actors played different roles and had different effects on the network. Intelligence facilities and rurality were critical to drive the MFL actor network translation process and pass through "obligatory passage point". By changing the interaction mode and intensity of the actors, the MFL actor-network could be promoted.

General election effect on the network topology of Pakistan’s stock market: network-based study of a political event

To examine the interdependency and evolution of Pakistan’s stock market,we consider the cross-correlation coefficients of daily stock returns belonging to the blue chip Karachi stock exchange(KSE-100)index.Using the minimum spanning tree network-based method,we extend the financial network literature by examining the topological properties of the network and generating six minimum spanning tree networks around three general elections in Pakistan.Our results reveal a star-like structure after the general elections of 2018 and before those in 2008,and a tree-like structure otherwise.We also highlight key nodes,the presence of different clusters,and compare the differences between the three elections.Additionally,the sectorial centrality measures reveal economic expansion in three industrial sectors—cement,oil and gas,and fertilizers.Moreover,a strong overall intermediary role of the fertilizer sector is observed.The results indicate a structural change in the stock market network due to general elections.Consequently,through this analysis,policy makers can focus on monitoring key nodes around general elections to estimate stock market stability,while local and international investors can form optimal diversification strategies.

Exploring the complex structural evolution of global primary product trade network

The production and trade of primary products had a growing impact on the economic security of all countries and regions,and the strategic position of these products in the global trade network was becoming increasingly prominent.Based on complex network theory,this paper explored the spatial pattern and complex structural evolution of the global primary product trade network(GPPTN)during 1985-2015 by using index methods,such as centrality,Sankey diagram,and structure entropy,focusing on the diversified spatial structure of China’s import and export markets for primary products(with exceptions of Taiwan of China,Hong Kong of China,and Macao of China due to a lack of data)and their geographical implications for China’s energy security.The research offered the following key findings.The GPPTN showed an obvious spatial heterogeneity pattern,and the area of import consumption was more concentrated;however,the overall trend was decentralized.The trade center of gravity shifted eastwards and reflected the rise of emerging markets.The overall flow of the GPPTN was from west to east and from south to north.In terms of the community detection of the GPPTN,North America,Europe,and Asia increasingly presented an unbalanced“tripartite confrontation”.China’s exports of primary products were mainly concentrated in the Association of Southeast Asian Nations(ASEAN)and other peripheral regions of Asia,and its imports undergone a major transformation,gradually expanding from the peripheral regions of Asia to Africa,the Middle East,Latin America,and other parts of the world.Energy fuels also became the largest imported primary products.Based on the changing trend of structural entropy and main market share,the analysis showed that the stable supply of China’s energy diversification was gradually realized.In particular,the cooperation dividend proposed by the Belt and Road initiative became an important turning point and a strong support for the expansion of China’s energy market diversification pattern and guarantee of energy security.

An Empirical Study on Strategic Network,Relational Capability and Operating Performance of Agricultural Enterprises

By establishing the theoretical model of " strategic network cooperation-relational capability-operating performance" and structural equation,we conduct a sampling survey on 208 agricultural enterprises,and use Spss21. 0 and Amos21. 0 for empirical analysis of influence of three factors in strategic network cooperation( market futurity,trusting relationship and business networks) on market relational capability and operating performance of agricultural enterprises. The results show that the establishment of trusting relationship and business networks in strategic networks has a positive impact on the operating performance of agricultural enterprises,and relational capability plays a fully mediating role while relational capability has not mediating effect on market futurity. This study provides a meaningful reference for the follow-up studies on relational capability and operating performance of agricultural enterprises,to further enhance the operating performance of agricultural enterprises and effectively improve farmers' income.

Short-Term Electricity Price Forecasting Using a Combination of Neural Networks and Fuzzy Inference

This paper presents an artificial neural network, ANN, based approach for estimating short-term wholesale electricity prices using past price and demand data. The objective is to utilize the piecewise continuous na-ture of electricity prices on the time domain by clustering the input data into time ranges where the variation trends are maintained. Due to the imprecise nature of cluster boundaries a fuzzy inference technique is em-ployed to handle data that lies at the intersections. As a necessary step in forecasting prices the anticipated electricity demand at the target time is estimated first using a separate ANN. The Australian New-South Wales electricity market data was used to test the system. The developed system shows considerable im-provement in performance compared with approaches that regard price data as a single continuous time se-ries, achieving MAPE of less than 2% for hours with steady prices and 8% for the clusters covering time pe-riods with price spikes.

Comparison of Electric Load Forecasting between Using SOM and MLP Neural Network

Electric load forecasting has been a major area of research in the last decade since the production of accurate short-term forecasts for electricity loads has proven to be a key to success for many of the decision makers in the energy sector, from power generation to operation of the system. The objective of this research is to analyze the capacity of the MLP （multilayer perceptron neural network） versus SOM （self-organizing map neural network） for short-term load forecasting. The MLP is one of the most commonly used networks. It can be used for classification problems, model construction, series forecasting and discrete control. On the other hand, the SOM is a type of artificial neural network that is trained using unsupervised data to produce a low-dimensional, discretized representation of an input space of training samples in a cell map. Historical data of real global load demand were used for the research. Both neural models provide good prediction results, but the results obtained with the SOM maps are markedly better Also the main advantage of SOM maps is that they reach good results as a network unsupervised. It is much easier to train and interpret the results.

Hot Events Detection of Stock Market Based on Time Series Data of Stock and Text Data of Network Public Opinion

With the highly integration of the Internet world and the real world, Internet information not only provides real-time and effective data for financial investors, but also helps them understand market dynamics, and enables investors to quickly identify relevant financial events that may lead to stock market volatility. However, in the research of event detection in the financial field, many studies are focused on micro-blog, news and other network text information. Few scholars have studied the characteristics of financial time series data. Considering that in the financial field, the occurrence of an event often affects both the online public opinion space and the real transaction space, so this paper proposes a multi-source heterogeneous information detection method based on stock transaction time series data and online public opinion text data to detect hot events in the stock market. This method uses outlier detection algorithm to extract the time of hot events in stock market based on multi-member fusion. And according to the weight calculation formula of the feature item proposed in this paper, this method calculates the keyword weight of network public opinion information to obtain the core content of hot events in the stock market. Finally, accurate detection of stock market hot events is achieved.