The Bio-Geographical Regions Division of Global Terrestrial Animal by Multivariate Similarity Clustering Analysis Method

A novel multivariate similarity clustering analysis (MSCA) approach was used to estimate a biogeographical division scheme for the global terrestrial fauna and was compared against other widely used clustering algorithms. The faunal dataset included almost all terrestrial and freshwater fauna, a total of 4631 families, 141,814 genera, and 1,334,834 species. Our findings demonstrated that suitable results were only obtained with the MSCA method, which was associated with distinct hierarchies, reasonable structuring, and furthermore, conformed to biogeographical criteria. A total of seven kingdoms and 20 sub-kingdoms were identified. We discovered that the clustering results for the higher and lower animals did not differ significantly, leading us to consider that the analysis result is convincing as the first zoogeographical division scheme for global all terrestrial animals.

Mechanism Research of Regional Brand Enhancement Based on Agricultural Industry Clusters

This article makes an integral and comprehensive study on the process of regional brand enhancement based on agricultural industry clusters using the theories of industrial clusters and regional brands.By analyzing the key determinants in the process of regional brand enhancement based on agricultural industry clusters,we establish a systemic theory system.The results show that as an important mediator in the process of regional brand enhancement based on agricultural industry clusters,the construction of value chain system is of vital importance.Other factors, such as the government guidance and service,the promotion of industry associations and professional cooperatives,play a key regulating role in this process.

A Study of Mathematic Model to the Development of Regional Industry Cluster

This paper analyzes the factors that influence the development of regional industry cluster, which are location factors, accumulatable factors, and external factors. Then regarding the similarity between the development of industry cluster and biology community, a modified logistic model is built, and a field study is made between the real instances and the model.

The Cooperation of Industrial Clusters and Regional Logistics of Shaanxi Province: An Evaluation Research

As a middle organization between enterprise organization which gains the competition advantage and eration of industrial clusters and regional logistics refers development of modern regional logistics. On the basis and market, industrial cluster is now the space industrial innovation advantage for a nation or a region. The coop- to improvement of industrial clusters＇ competitiveness and of reviewing the recent years＇ situation of Shaanxi Prov- ince＇s regional logistics and its industrial clusters, this paper analyzes positively about the supporting role of the regional logistics, builds gray relational model by choosing corresponding indicators, and carries out test of signif- icance. Finally it brings out strategic recommendations to and regional logistics enhance the level of cooperation of industrial clusters

Regional Evaluation on Sustainable Development of Agriculture in Tibet Based on Cluster Analysis

To understand the spatial difference of agricultural sustainability in Tibet,this paper establishes a comprehensive evaluation model of agricultural sustainability to calculate the score of agricultural sustainability of 7 areas in 2013 in Tibet. By using cluster analysis,this paper conducts the regional evaluation of Tibet's agricultural sustainability. The results show that 7 cities' regional difference of agricultural sustainability was obvious in 2013,the agricultural sustainability index value was 0. 4232- 0. 6937,and the value was in the order of Nyingchi > Lhasa > Shannan > Ali > Shigatse > Qamdo > Nagqu. According to the agricultural sustainable development level,Tibet can be divided into three regions: the first type is the area with the highest level of sustainable development of agriculture,including Nyingchi and Lhasa; the second type is the area with the average level of sustainable development of agriculture,including Shigatse and Shannan; the third type is the area with the low level of sustainable development of agriculture,including Qamdo,Ali and Nagqu.

基于产业集群(cluster)的区域物流系统与运作模式

通过对产业集群下物流系统的分析,论述了区域物流业对产业集群发展的支撑作用,进而探讨了基于产业集群的区域物流系统的构成要素及构建物流系统的原则、措施,在此基础上,提出基于产业集群的区域物流运作模式。

Regional Merge K-means图像分割算法及其质量评价

K值是基于K-means聚类算法进行图像分割效果的关键因素,为了解决K值过小,图像分割不明显,K值过大,图像分割信息过于碎片化的问题,提出一种Regional Merge K-means(RMK)算法.首先对图像运用K-means算法进行聚类,然后运用区域合并(Regional Merge)优化图像分割效果,最后利用不同图像进行图像分割试验,并选用不同的质量评价指标对试验结果进行评价.结果表明,该算法能显著优化图像分割效果.

Regionalization of Rainfall Intensity-Duration-Frequency (IDF) Curves in Botswana

A regional analysis of design storms, defined as the expected rainfall intensity for given storm duration and return period, is conducted to determine storm Rainfall Intensity-Duration-Frequency (IDF) relationships. The ultimate purpose was to determine IDF curves for homogeneous regions identified in Botswana. Three homogeneous regions were identified based on topographic and rainfall characteristics which were constructed with the K-Means Clustering algorithm. Using the mean annual rainfall and the 24 hr annual maximum rainfall as an indicator of rainfall intensity for each homogeneous region, IDF curves and maps of rainfall intensities of 1 to 24 hr and above durations were produced. The Gamma and Lognormal probability distribution functions were able to provide estimates of rainfall depths for low and medium return periods (up to 100 years) in any location in each homogeneous region of Botswana.

SOFT IMAGE SEGMENTATION BASED ON CENTER-FREE FUZZY CLUSTERING

Image segmentation remains one of the major challenges in image analysis.And soft image segmentation has been widely used due to its good effect.Fuzzy clustering algorithms are very popular in soft segmentation.A new soft image segmentation method based on center-free fuzzy clustering is proposed.The center-free fuzzy clustering is the modified version of the classical fuzzy C-means ( FCM ) clustering.Different from traditional fuzzy clustering , the center-free fuzzy clustering does not need to calculate the cluster center , so it can be applied to pairwise relational data.In the proposed method , the mean-shift method is chosen for initial segmentation firstly , then the center-free clustering is used to merge regions and the final segmented images are obtained at last.Experimental results show that the proposed method is better than other image segmentation methods based on traditional clustering.

Identification methods for anomalous stress region in coal roadways based on microseismic information and numerical simulation

It is believed that the microseismicity induced by mining effect and gas gradient disturbance stress is a precursor to the essential characteristics of roadway unstability. In order to effectively identify and evaluate the stability of coal roadways in the process of mine development and extraction, a microseismic monitoring system was deployed for the study of the stress evolution process, damage degree and distribution characteristics in the tailgate and headgate. The mine under study is the 62113 outburst working face of Xin Zhuangzi coalmine in Huainan mining area. The whole process of microfractures initiation,extension, interaction and coalescence mechanisms during the progressive failure processes of the coal rock within the delineated and typical event clusters were investigated by means of a two dimensional realistic failure process analysis code(RFPA2D-Flow). The results show that the microseismic events gradually create different-sized event clusters. The microseismicity of the tailgate is significantly higher than that of the headgate. The study indicates that the greater anomalous stress region matches the area where microfractures continuously develop and finally connect to each other and form a fissure zone.Due to the mine layout and stress concentration, the ruptured area is mainly located on the left shoulder of the tailgate roof. The potential anomalous stress region of the coal roadway obtained by numerical simulation is relatively in good agreement with the trend of spatial macro evolution of coal rock microfractures captured by the microseismic monitoring system. The research results can provide important basis for understanding instability failure mechanism of deep roadway and microseismic activity law in complex geologic conditions, and it ultimately can be used to guide the selection and optimization of reinforcement and protection scheme.

Optimization Study of Outburst Prevention Measures for Tuzhu Coal Mine Based on Fixed Weight Clustering Analysis

Affected by many involved factors, different dimensions, data with large difference, incomplete information and so on, the most optimal selection of regional outburst prevention measures for outburst mine has become a complicated system project. The traditional way of outburst prevention measure selection belongs to qualitative method, which may cause high-cost of gas control, huge quantities of drilling work, long construction time and even secondary disaster. To solve the above-mentioned problems, in light of occurrence status of coal seam gas in No. 21 mining area of Jinzhushan Tuzhu Mine, through grey fixed weight clustering theory and a combination method of qualitative and quantitative analysis, the judging model with multi-objective classification for optimization of outburst prevention measures was established. The three weight coefficients of outburst prevention technology scheme are sorted, in order to determine the advantages and disadvantages of each outburst prevention technology scheme under the comprehensive evaluation of multi-target. Finally, the problem of quantitative selection for regional outburst prevention technology scheme is solved under the situation of multi-factor mode and incomplete information, which provides reasonable and effective technical measures for prevention of coal and gas outburst disaster.

Automatic Video Segmentation Algorithm by Background Model and Color Clustering

In order to detect the object in video efficiently, an automatic and real time video segmentation algorithm based on background model and color clustering is proposed. This algorithm consists of four phases: background restoration, moving objects extract, moving objects region clustering and post processing. The threshold of the background restoration is not given in advanced. It can be gotten automatically. And a new object region cluster algorithm based on background model and color clustering to remove significance noise is proposed. An efficient method of eliminating shadow is also used. This approach was compared with other methods on pixel error ratio. The experiment result indicates the algorithm is correct and efficient.

SLC Analysis on Earthquake Activity in the Regions of Sichuan and Yunnan of China

Using the method of Single-link Cluster(SLC),analyzing the pattern of time sliding of SLCparameters,the earthquake activity in the western Sichuan-Yunnan of China is studiedcombining with the regional earthquake catalogue since 1970 and the tectonic background.Comparing with the high level of earthquake activity in 1970’s and the low in 1980’s,theearthquake activity is in general at the middle level in 1990’s.This paper suggests that SLCmethod,which considers the temporal and spatial relationship among earthquake events,could be adopted to analyze the trend of regional earthquake activity,it is very useful forstudying seismic activity.

HiSC:A Hybrid XML Index Composing Structure-Encoded with Cluster

A new way of indexing and processing twig patterns in an XML documents is proposed in this paper. Every path in XML document can be transformed into a sequence of labels by Structure-Encoded that constructs a one-to-one correspondence between XML tree and sequence. Base on identifying characteristics of nodes in XML tree, the elements are classified and clustered. During query proceeding, the twig pattern is also transformed into its Structure-Encoded. By performing subsequence matching on the set of sequences in XML documents, all the occurrences of path in the XML documents are refined. Using the index, the numbers of elements retrieved are minimized. The search results with pertinent format provide more structure information without any false dismissals or false alarms. The index also supports keyword search Experiment results indicate the index has significantly efficiency with high precision.

基于匹配信任度机制的移动传感网簇头更新算法

为解决移动传感网部署过程中存在的簇头节点更新质量不佳和节点生存率较低等不足,提出了一种基于匹配信任度机制的移动传感网簇头更新算法。首先,引入K-means算法,利用误差平方根函数来完成网络初始聚类,以快速定位聚类中心,提升聚类形成速度。随后,综合考虑备选簇头剩余能量、备选簇头与当前簇头的欧氏距离、备选簇头覆盖范围内节点总数3个因素,设计了基于匹配信任度的簇头更新方法,按权值对各因素进行平均分配,进而将信任度权值最高的节点作为备选簇头,从而选举出生存质量较高的节点。仿真实验表明,算法具有更高的网络稳定运行时间和簇头节点生存率,以及更低的节点故障概率。其中,网络稳定运行时间提升了80%以上,簇头节点生存率保持在90%以上,节点故障概率也较低,具有明显的优势。

A Review on Clustering Methods for Climatology Analysis and Its Application over South America

South America’s climatic diversity is a product of its vast geographical expanse, encompassing tropical to subtropical latitudes. The variations in precipitation and temperature across the region stem from the influence of distinct atmospheric systems. While some studies have characterized the prevailing systems over South America, they often lacked the utilization of statistical techniques for homogenization. On the other hand, other research has employed multivariate statistical methods to identify homogeneous regions regarding temperature and precipitation, but their focus has been limited to specific areas, such as the south, southeast, and northeast. Surprisingly, there is a lack of work that compares various multivariate statistical techniques to determine homogeneous regions across the entirety of South America concerning temperature and precipitation. This paper aims to address this gap by comparing three such techniques: Cluster Analysis (K-means and Ward) and Self Organizing Maps, using data from different sources for temperature (ERA5, ERA5-Land, and CRU) and precipitation (ERA5, ERA5-Land, and CPC). Spatial patterns and time series were generated for each region over the period 1981-2010. The results from this analysis of spatially homogeneous regions concerning temperature and precipitation have the potential to significantly benefit climate analysis and forecasts. Moreover, they can offer valuable insights for various climatological studies, guiding decision-making processes in diverse fields that rely on climate information, such as agriculture, disaster management, and water resources planning.

中国乡村创新创业发展:指数构建与测度分析

鼓励乡村创新创业是推进乡村振兴战略的重要抓手,但尚未有科学严谨的研究全面揭示中国乡村创新创业的发展程度和时空特征。通过构建包括2个一级指标、7个二级指标和21个三级指标的乡村创新创业指标体系,计算2014—2021年中国县、市、省级三个层面的乡村创新创业指数,并对其发展趋势、空间特征等展开分析。研究发现:中国乡村创新创业总体上蓬勃发展,但区域间存在差异;乡村振兴示范县的创新创业程度要显著高于其他县,国家重点帮扶县的创新创业增长速度要显著高于非重点帮扶县;乡村创新创业活动存在明显的空间集聚现象,同时也表现出区域收敛的趋势。乡村创新创业指数已向社会开放,将为各界研究中国乡村创新创业提供基础性数据。

NUMERICAL CLASSIFICATION OF REGIONAL STRUCTURE OF AGRO-ECOSYSTEM IN GUANGDONG

On the basis of 'The Statistical Data of Guangdong Province in 1981' and the 14 selected original variables, 107 counties and suburbs in Guangdong are classified. In the classification, cluster analysis is applied, and the cluster hierarchy of the agro-ecosystem is achieved with a computer. According to output level, planting structure, and input level of energy, there is an evident regionalism in the agro-ecosystem of Guangdong, which presents approximately concentric circles centralized by Guangzhou City.

Evaluation of tourism climate comfort in the Grand Shangri-La region

The Grand Shangri-La(GSL) region has strong international tourist appeal. GSL has considerable international eco-tourist potential as well as being attractive for leisure, vacation, health, explorative, and scientific research activities in addition to high-end tourism experiences. These factors could promote the development of its regional tourism. GSL has been identified as a key area for tourism development in China. In this study, we investigated tourism climate conditions in GSL from 1980 to 2016 using a tourism climate index(TCI). We found that through global warming, the number of annual and monthly good-weather days, as assessed with the TCI, showed an increase over most of GSL;that trend was especially true for very good, excellent, and ideal days. The optimal travel period was May–October. We obtained the same result using cluster heat maps, in which we categorized 31 studied meteorological stations into eight types. However, heavy rainfall tended to occur during that optimal period, and it was concentrated at certain times. The annual total number of comfortable days greater than 300 was mainly located in southern GSL. We observed significant correlations between monthly and annual excellent and ideal days with latitude and elevation;in particular, we identified a significant nonlinear correlation between excellent(and ideal) days and elevation.