核函数主成分法和系统聚类法在区域旅游竞争力评价中的应用

采用核函数主成分法(KPCA)和系统聚类法(SCA)进行区域旅游竞争力的定量分析。在借鉴国内外相关研究成果的基础上,构建了基于和谐社会的区域旅游竞争力综合评价指标体系。根据指标体系的特点,采用核函数主成分分析和系统聚类模型进行分析评价。并对广东、江苏等旅游大省进行实证分析,科学地评价了这些省份的旅游发展竞争力。研究表明:核函数主成分分析法成功地实现非线性系统的降维,具有良好的适应性和可行性;系统聚类分析进一步验证了核函数主成分分析法分析的结果。

安徽省地方桑品种酯酶同工酶遗传差异研究

依据桑树冬芽的酯酶同工酶聚丙烯酰胺凝胶电泳技术得到的谱带图对安徽省 1 7个地方桑品种进行聚类分析比较其遗传差异 ,并把这些品种分为 4类 。

Application of cluster analysis and stepwise regression in predicting the traffic volume of lanes

Because of the difficulty to obtain the traffic flow information of lanes at non-detector intersections in most metropolises of the world,based on the relationships between the lanes of signal-controlled intersections,cluster analysis and stepwise regression are integrated to predict the traffic volume of lanes at non-detector isolated controlled intersections.First cluster analysis is used to cluster the lanes of non-detector isolated signal-controlled intersections and the lanes of all signal-controlled intersections with detectors.Then, by the results of cluster analysis,the traffic volume samples are selected randomly and stepwise regression is used to predict the traffic volume of lanes at non-detector isolated signal-controlled intersections.The method is tested by the traffic volume data of lanes of the road network of Nanjing city.The problem of predicting the traffic volume of lanes at non-detector isolated signal-controlled intersections was resolved and can be widely used in urban traffic flow guidance and urban traffic control in cities without enough intersections equipped with detectors.

Study on FTIR Spectra of Corn Germs and Endosperms of Three Different Colors Combining with Cluster Analysis

[Objective] This research aimed to study the FTIR spectra of corn germs and endosperms so as to provide a scientific way for identifying corn of different types. [Method] The corn germs and endosperms of three types were studied by using Fourier transform infrared spectroscopy（FTIR） technology, combined with cluster analysis. [Result] The overall characteristics of original FTIR spectra were basically similar within the range of 700-1 800 cm^-1. The FTIR spectra were mainly composed by the absorption peaks of polysaccharides, proteins and lipids. Within the wavelength range of 700-1 800 cm^-1, there were only tiny differences in original FTIR spectra among the corn germs and endosperms of three different types. The spectra were then processed by using first derivative and second derivative. The second derivative spectra were used for hierarchical cluster analysis（HCA）. The results showed that with the wavelength range of 700-1 800 cm^-1, the second derivative spectra of the 52 samples could be better clustered according to the tree types and corn germ and corn endosperm. The clustering correct rate reached 96.1%.[Conclusion] FTIR technology, combined with cluster analysis, can be used to identify different types of corn germs and endosperms, and it is characterized by convenience and rapidness.

Analysis on the Origin and Phylogenetic Status of Tong Sheep Using 12 Blood Protein and Nonprotein Markers

This study is based on the Tong sheep obtained by the random sampling method of typical colonies in the central area of Baishui County in Shaanxi Province, China. An investigation was undertaken to clarify the gene constitution of blood protein and nonprotein types of Tong sheep. Twelve genetic markers were examined by starch-gel electrophoresis and cellulose acetate electrophoresis. Polymorphism in Tong sheep was found at the following 10 loci, transferrin （Tf）, alkaline phosphatase （Alp）, leucine aminopeptidase （Lap）, arylesterase （Ary-Es）, hemoglobin-β （Hb-β）, X-protein （X-p）, carbonic anhydrase （CA）, catalase （Cat）, malate dehydrogenase （MDH）, and lysine （Ly）, whereas, albumin （A1） and postalbumin （Po） loci were monomorphic. Genetic approach degree method and phylogenetic relationship clustering method were used to judge the origin and phylogenetic status of Tong sheep. Results from both methods maintained that Tong sheep belonged to the ＂Mongolia group＂, and Mongolia sheep was the origin of Tong sheep. This was also supported by the history of Tong sheep breeding. Compared to the phylogenetic relationship clustering method, the genetic approach degree method was more reliable for the extraction from East and South of Central Asia, and was more effective in reflecting the breeding course of Tong sheep.

A SPATIAL CLUSTER METHOD SUPPORTED BY GIS FOR URBAN-SUBURBAN-RURAL CLASSIFICATION

This study was undertaken to construct a preliminary spatial analysis method for building an urban-suburban-rural category in the specific sample area of central California and providing distribution characteristics in each category, based on which, some further studies such as regional manners of residential wood burning emission (PM2.5, the term used for a mixture of solid particles and liquid droplets found in the air, refers to particulate matter that is 2.5 mu m or smaller in size) could be carried out for the project of residential wood combustion. Demographic and infrastructure data with spatial characteristics were processed by integrating both Geographic Information System (GIS) and statistics method (Cluster Analysis), and then output to a category map as the result. It approached the quantitative and multi-variables description on the major characteristics variations among the urban, suburban and rural; and perfected the TIGER's urban-rural classification scheme by adding suburban category. Based on the free public GIS data, the spatial analysis method provides an easy and ideal tool for geographic researchers, environmental planners, urban/regional planners and administrators to delineate different categories of regional function on the specific locations and dig out spatial distribution information they wanted. Furthermore, it allows for future adjustment on some parameters as the spatial analysis method is implemented in the different regions or various eco-social models.

Genetics and phylogeny of genus Coilia in China based on AFLP markers

The taxonomy of Coilia has been extensively studied in China,and yet phylogenetic relationships among component taxa remain controversial.We used a PCR-based fingerprinting technique,amplified fragment length polymorphism(AFLP) to characterize and identify all four species of Coilia in China.We examined the genetic relationships of the four species of Coilia and a subspecies of Coilia nasus with AFLP.A total of 180 AFLP loci were generated from six primer combinations,of which 76.11% were polymorphic.The mean genetic distance between pairs of taxa ranged from 0.047 to 0.596.The neighbor-joining tree and UPGMA dendrogram resolved the investigated species into three separate lineages:(1) C.mystus,(2) C.grayii and(3) C.brachygnathus,C.nasus,and C.nasus taihuensis.Phylogenetic analysis of the AFLP data is inconsistent with current morphological taxonomic systems.The AFLP data indicated a close relationship among C.brachygnathus,C.nasus taihuensis,and C.nasus.Therefore,the two species described under Coilia(C.brachygnathus and C.nasus taihuensis) are treated as synonyms of C.nasus.

Study on the Comprehensive Tourism Development Pattern in Periphery Minority Area:A Case Study of Gannan Tibetan Autonomous Prefecture of Gansu Province, China

The paper took the human-land relations as a basic point, and the theories of tourism industry system and sustainable development as the guidance, with Gannan Tibetan Autonomous Prefecture （Gannan） as the case study area. From microcosmic and macroscopic viewpoints, the author carded out function orientation and evaluation to the tourism industry development, and research on the comprehensive tourism industry development pattern of Gannan. Results show that the fragile ecological environment and the traditional economic growth pattern have restricted regional sustainable development, and made Gannan to become a representative of the periphery minority areas in Northwest China. Tourism development of Gannan is at the primary phase, with the characteristics of short industry chain and low economic efficiency. It is an inevitable choice to transform the way of regional economic growth and the development pattern of tourism industry from the traditional pattern to the pattern of sustainable development. Simultaneously, Gannan＇s natural, national and religious culture makes Gannan a broad prospect on the comprehensive tourism development. Gannan should choose the comprehensive tourism industry as its scientific pattern to realize sustainable development, promote harmonious social, economic and ecological development, alleviate the human-land contradictory, and realize dual goals in terms of ecology construction and economical development. For Gannan and the similar areas in China, studies on the sustainable development pattern of tourism have extremely important strategic sense with respect to tourism development and the sustainable development of regional economy.

A comprehensive evaluation of enterprise emergency management capacity （EEMC） based on variable weight gray cluster

On the basis of the initial definition of Enterprise Emergency Management Capacity（EEMC）, the paper has established evaluation index system of EEMC, and provided a method to calculate index weight, with the regard to subjectivity existing in the comprehensive evaluation of EEMC multi-indicators, in accordance with the principle of Variable weight Gray Cluster, which makes the weight of indicators generate automatically in the evaluation process and not judged by human, thus decreasing subjective factors during the evaluation.

Two-Stage Resource Allocation Scheme for Three-Tier Ultra-Dense Network

In 5 G Ultra-dense Network(UDN), resource allocation is an efficient method to manage inter-small-cell interference. In this paper, a two-stage resource allocation scheme is proposed to supervise interference and resource allocation while establishing a realistic scenario of three-tier heterogeneous network architecture. The scheme consists of two stages: in stage I, a two-level sub-channel allocation algorithm and a power control method based on the logarithmic function are applied to allocate resource for Macrocell and Picocells, guaranteeing the minimum system capacity by considering the power limitation and interference coordination; in stage II, an interference management approach based on K-means clustering is introduced to divide Femtocells into different clusters. Then, a prior sub-channel allocation algorithm is employed for Femtocells in diverse clusters to mitigate the interference and promote system performance. Simulation results show that the proposed scheme contributes to the enhancement of system throughput and spectrum efficiency while ensuring the system energy efficiency.

Development of slope mass rating system using K-means and fuzzy c-means clustering algorithms

Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experience-based criteria. In order to eliminate linguistic criteria resulted from experience-based judgments and account for uncertainties in determining class boundaries developed by SMR system,the system classification results were corrected using two clustering algorithms, namely K-means and fuzzy c-means(FCM), for the ratings obtained via continuous and discrete functions. By applying clustering algorithms in SMR classification system, no in-advance experience-based judgment was made on the number of extracted classes in this system, and it was only after all steps of the clustering algorithms were accomplished that new classification scheme was proposed for SMR system under different failure modes based on the ratings obtained via continuous and discrete functions. The results of this study showed that, engineers can achieve more reliable and objective evaluations over slope stability by using SMR system based on the ratings calculated via continuous and discrete functions.

Multivariate Analysis in the Climate Change Studies and Water Quality of Lake Patzcuaro （Mexico）

In this study, the authors carried out the systemic analysis of water quality of Lake Patzcuaro in relationship with the climate change during a period of 85 years. The statistical comparison （medians, ＂t＂ Student test, regressions and correlations） for the precipitation, evaporation, observed temperature, minimum and maximum for the periods 1969-1988 （pre-impact） and 1988-2007 （post-impact） was realized. The ＂t＂ Student test for water quality during the period of 1981-2011, as well as, the regression analysis and multiple linear correlation of water quality from 2006 to 2011 were applied in joint way of the Cluster and Principal Component to observe the effects of climate change on water quality and vulnerability of Lake Patzcuaro. The comparative analysis of the meteorological data for 1921-1960 and 1973-2007 by the KOppen classification showed a climate change. The comparative Box Plots diagrams for 1973-1989 and 1989-2007, as well as, the ＂t＂ Student test, linear regression and correlation indicated significant changes in time for precipitation, evaporation, observed temperature, minimum and maximum （P ≤ 0.05）. The correlation and regression analysis indicated significant positive trends for turbidity, conductivity, total phosphorus, aluminum, oils and grease, in contrast with Secchi disk depth, transparency, Redox potential and dissolved oxygen concentration. The ＂t＂ Student test showed significant differences between 1981 and 2011 for transparency, hardness, alkalinity, conductivity, nitrite, and phosphate. Cluster and Principal Components of the physicochemical and biological of 2006-2011 confirmed the vulnerability of the system by human growth and climate change influence.

Design and Implementation of Office Management System in Small and Medium Sized Enterprises based on Data Mining Technology

This paper introduces data mining technology in enterprise competitive intelligence system; and then introduced theoretical foundation and main clustering method of cluster analysis. The article emphasis on the FCM algorithm and principle and described implementation steps, and proposed the improvement FCM algorithm based on K mean particle size; finally, realize the design and implementation of enterprise competitive intelligence analysis and mining service system, and the improved FCM algorithm is applied in the system.

Method for extracting geometrical characteristics of joint probability density based on contour lines

This paper presents a method for extracting geometrical features of the joint probability density function(PDF)of two-dimensional systems based on its contour lines,with particular interests given to the number and position of peaks and craters.In order to detect those two types of structures,a series of horizontal planes are applied to truncate the joint PDF with contour lines generated.Starting with the analysis of contour lines in a single plane,shape characteristics of the peak and the crater can be reflected on the contour lines in the aspects of gradient direction and inclusion relationship.Aided by the properties of PDF,the information about gradient direction and inclusion relationship of contour lines can be obtained simultaneously if the contour tree is built.According to the contour tree,the contour lines can be classified as two groups.Then the corresponding relation between contour lines in different planes is discussed.Based on the corresponding relation,clustering analysis about contour lines belonging to the same group but having different heights is performed.Two sets of contour lines are finally obtained as the simplest expression of geometrical characteristics of a joint PDF.They can be used to obtain the number and position of each peak and crater.Three oscillators of different types are chosen to test this method,which shows that this method can pave the way for numerical calculation about the stochastic P-bifurcation of multi-dimensional systems.

Distributed Clustering Algorithm for Energy Efficiency and Load-Balance in Large-Scale Multi-Agent Systems

To improve the energy efficiency and load-balance in large-scale multi-agent systems, a large-scale distributed cluster algorithm is proposed. At first, a parameter describing the spatial distribution of agents is designed to assess the information spreading capability of an agent. Besides, a competition resolution mechanism is proposed to tackle the competition problem in large-scale multiagent systems. Thus, the proposed algorithm can balance the load, adjust the system network locally and dynamically, reduce system energy consumption. Finally, simulations are presented to demonstrate the superiority of the proposed algorithm.

Power Network Parameter Estimation Method Based on Data Mining Technology

The parameter values which actually change with the circumstances, weather and load level etc. produce great effect to the result of state estimation. A new parameter estimation method based on data mining technology was proposed. The clustering method was used to classify the historical data in supervisory control and data acquisition （SCADA） database as several types. The data processing technology was implied to treat the isolated point, missing data and yawp data in samples for classified groups. The measurement data which belong to each classification were introduced to the linear regression equation in order to gain the regression coefficient and actual parameters by the least square method. A practical system demonstrates the high correctness, reliability and strong practicability of the proposed method.