Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.

Spatio-temporal patterns of drought in North Xinjiang, China, 1961–2012 based on meteorological drought index

Drought, which is one of the most frequently occurring severe hazards with long time scales and cov- ering wide geographical areas, is a natural phenomenon resulting in significant economic losses in agriculture and industry. Drought is caused by an imbalance between the inputs of and the demand for water which is insufficient to meet the demands of human activities and the eco-environment. As a major arid and semi-arid area and an important agricultural region in Northwest China, North Xinjiang （NX） shows great vulnerability to drought. In this paper, the characteristics of inter-annual and seasonal drought were analyzed in terms of drought occurrence and drought coverage, by using the composite index of meteorological drought and the data of daily precipitation, air temperature, wind speed, relative humidity and sunshine duration from 38 meteorological stations during the period 1961-2012. Trend analysis, wavelet analysis and empirical orthogonal function were also applied to investigate change trend, period and regional characteristics, respectively. In NX, annual and seasonal drought occurrence and drought coverage all showed a decreasing trend that was most significant in winter （with rates of-0.26 month/10a and -15.46%, respectively）, and drought occurrence in spring and summer were more frequent than that in autumn and winter. Spatially, drought was severe in eastern regions but mild in western regions of NX. Annual and seasonal drought occurrence at 38 meteorological stations displayed decreasing trends and were most significant in ＂Shi- hezi-Urumqi-Changji＂, which can help to alleviate severe drought hazards for local agricultural production and improve human livelihood. NX can be approximately classified into three sub-regions （severe drought region, moder- ate drought region and mild drought region）, which were calculated from annual drought frequencies. The cross wavelet transform suggested that SOl （Southern Oscillation Index）, AOI （Arctic Oscillation Index）, AAOI （Antarctic Oscillation Index）, PAOI （Pacific/North American Oscillation Index） and NAOI （North Atlantic Oscillation Index） have significant correlation with the variation of drought occurrence in NX. To prevent and mitigate the occurrence of drought disasters in NX, agricultural and government managers should pay more attention to those drought events that occur in spring and summer.

Methods to evaluate the impacts of physio- geographical pattern on spatio-temporal disparity of regional development

With the rapid economic development during the last 30 years in China, more and more disparities have emerged among different regions. It has been one of the hot topics in the fields of physical geography and economic geography, and also has been the task for Chinese government to handle. Nevertheless, to quantitatively assess the impacts of physio-geographical patterns （PGP） on the regional development disparity has been ignored for a long time. In this paper, a quantitative method was adopted to assess the marginal effects of the PGP on spatio-temporal disparity using the partial determination coefficients. The paper described the construction of the evaluation model step by step following its key scientific thinking. Total GDP, per capita GDP, primary industrial output value and secondary industrial output value were employed in this study as the indicators to reflect the impacts of PGP on the regional development disparity. Based on the evaluation methods built by researchers, this study firstly analyzed the temporal impacts of the PGP on spatio-temporal disparity of the regional development in China during the past 50 years, and then explained the spatial differences at each development stage. The results show that the spatio-temporal disparity in China is highly related to the PGP, and that the marginal contribution rate could be employed as an effective way to quantitatively assess the impact of the PGP on spatio-temporal disparity of the regional development.

Spatio-temporal point pattern analysis on Wenchuan strong earthquake

For exploring the aftershock occurrence process of the 2008 Wenchuan strong earthquake, the spatio-temporal point pattern analysis method is employed to study the sequences of aflershocks with magnitude M≥4.0, M≥4.5, and M≥5.0. It is found that these data exhibit the spatio-temporal clustering on a certain distance scale and on a certain time scale. In particular, the space-time interaction obviously strengthens when the distance is less than 60 km and the time is less than 260 h for the first two aftershock sequences; however, it becomes strong when the distance scale is less than 80 km and the time scale is less than 150 h for the last aftershock sequence. The completely spatial randomness analysis on the data regardless of time component shows that the spatial clustering of the aftershocks gradually strengthens on the condition that the distance is less than 60 km. The results are valuable for exploring the occurrence rules of the Wenchuan strong earthquake and for predicting the aftershocks.

“stppSim”: A Novel Analytical Tool for Creating Synthetic Spatio-Temporal Point Data

In crime science, understanding the dynamics and interactions between crime events is crucial for comprehending the underlying factors that drive their occurrences. Nonetheless, gaining access to detailed spatiotemporal crime records from law enforcement faces significant challenges due to confidentiality concerns. In response to these challenges, this paper introduces an innovative analytical tool named “stppSim,” designed to synthesize fine-grained spatiotemporal point records while safeguarding the privacy of individual locations. By utilizing the open-source R platform, this tool ensures easy accessibility for researchers, facilitating download, re-use, and potential advancements in various research domains beyond crime science.

Formation mechanism of bright and dark concentric-ring pattern in dielectric barrier discharge

In this work,a bright and dark concentric-ring pattern is reported in a dielectric barrier discharge for the first time.The spatiotemporal dynamics of the bright and dark concentric-ring pattern are investigated with an intensified charge-coupled device and photomultiplier tubes.The results indicate that the bright and dark concentric-ring pattern is composed of three concentric-ring sublattices.These are bright concentric-ring structures,dark concentric-ring structures and wider concentric-ring structures,respectively.The bright concentric-ring structures and dark concentricring structures are alternately distributed.The bright concentric-ring structures are located at the centre of the wider concentric-ring structures.The wider concentric-ring structures first form from the outer edge and gradually develop to the centre.The essence of all three concentric-ring structures is the individual discharge filaments.The optical emission spectra of different sublattices are acquired and analysed.It is found that the plasma parameters of the three concentricring sublattices are different.Finally,the formation mechanism of the bright and dark concentricring pattern is discussed.

Multi-scale regionalization based mining of spatio-temporal teleconnection patterns between anomalous sea and land climate events

Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.

Spatio-temporal Pattern and Driving Forces of Comprehensive Agricultural Productivity in Jilin Province,China

Improving comprehensive agricultural productivity is an important measure to realize agricultural modernization.Based on the data from Jilin Statistical Yearbook,this study analyzed the spatial and temporal characteristics of comprehensive agricultural productivity discrepancy in the main agricultural production areas of Jilin Province,China.The comprehensive agricultural productivity of 25 county-level administrative units were evaluated by a comprehensive index system based on five aspects which included 20 indicators from 2004 to 2017.The pattern of the discrepancy was analyzed by the spatial differentiation indices and spatial convergence theory.The results were as follows:1) the overall comprehensive agricultural productivity was in a ’W-type’ rising trend;2) the discrepancy was in’inverted W-type’ trend;3) the spatial distribution characteristics were mainly discrete plaque and ’inverted V-type’;4) the formation of differences was forced by a combination of internal and external driving forces.Our study demonstrates the effectiveness of rising agricultural productivity and the level of economic and social developments in different counties in Jilin Province.

Spatio-Temporal Patterns of Wildlife Road Mortality in Golestan National Park-North East of Iran

Nowadays, wildlife road mortality is acknowledged as a main source of threatening long-term survival of wildlife. This paper as the first to analysis wild life vehicle collisions in Iran, aims to reconstruct and interpret the spatio-temporal patterns of WVCs on Asiaei highway in Golestan National Park (GNP). With the collaboration of environmental protection department of GNP, we identified about 1900 WVC Records involving 34 different species of mammals, birds, reptiles and amphibians between 2004 and 2013. Mammals were involved in more than 50% of overall WVCs, among which wild boar (Sus scrofa), Golden Jackal (Canis aureus), Red Fox (Vulpes vulpes), hedgehog (Erinaceus concolor), stone marten (Martes foina) and porcupine (Hystrix indica) were involved in more than 90% of mammals’ mortalities;So, we focused on analyzing spatio-temporal pattern of vehicle collisions of these six mammal species. During the study period, these species have undergone 95% increase in road mortalities, averagely. Detailed temporal analyses exhibited an increasing trend of road mortalities from spring to summer and then a reducing one to late winter. It was shown that a large number of collisions occurred in holiday periods when recreational trips considerably increased the traffic volume of Asiaei highway. Preliminary inspection of spatial patterns using Kernel density analysis revealed six collision hotspots, mostly located in the road bends with densely forested land cover on both sides;the promenades along the road seemed to play a significant role too. Scale dependency analyses of collision patterns, demonstrated clustering pattern at micro scales less than 10 km, randomness at meso scales 10 - 20 km and both regularity and clustering at macro scales more than 20 km. This paper suggests that road mortality of common species in GNP is a momentous issue, which needs to be considered by relevant governmental and public organizations. We also emphasize that the analyses of spatial and temporal patterns of WVCs are fundamentals to plan for mitigate wildlife road mortality.

COVID-19 lockdown has indirect,non-equivalent effects on activity patterns of Reeves's Pheasant(Syrmaticus reevesii)and sympatric species

The outbreak of the COVID-19 pandemic has brought massive shifts in human activities through a global blockade,directly affecting wildlife survival.However,the indirect impacts of changes in human activities are often easily overlooked.We conducted surveys of Reeves's Pheasant(Syrmaticus reevesii)and its sympatric species by camera traps in forest-type nature reserves in three different scenarios:pre-lockdown,lockdown and postlockdown.An increase in livestock activities observed during the lockdown and post-lockdown period in our study area provided us an opportunity to investigate the indirect impact of the lockdown on wildlife.The prelockdown period was used as a baseline to compare any changes in trends of relative abundance index,activity patterns and temporal spacing of targeted species and livestock.During the lockdown period,the relative abundance index of livestock increased by 50%and there was an increase in daytime activity.Reeves's Pheasant showed avoidance responses to almost all sympatric species and livestock in three different periods,and the livestock avoidance level of Reeves's Pheasant during the lockdown period was significantly and positively correlated with the relative abundance index of livestock.Species-specific changes in activity patterns of study species were observed,with reduced daytime activities of Hog Badger and Raccoon Dog during and after the confinement periods.This study highlights the effect of the COVID-19 lockdown on the responses of wildlife by considering the changes in their temporal and spatial use before,during and after lockdown.The knowledge gained on wildlife during reduced human mobility because of the pandemic aids in understanding the effect of human disturbances and developing future conservation strategies in the shared space,to manage both wildlife and livestock.

Spatio-temporal Variability of Disastrous Convective Weather in China from 1961 to 2016

Based on the data of hail,gale,thunderstorm and lightning days in 2 481 stations in China from 1961 to 2016,the spatial and temporal distribution characteristics,periodicity and climate abruption characteristics of four kinds of disastrous convective weather in China were analyzed by various mathematical statistics methods. The results showed that in time,the days of four kinds of disastrous convective weather in China decreased,and the hail and thunderstorm days were characterized by " increasing firstly and then decreasing" from 1961 to 2016. The hail,gale,thunderstorm and lightning days in China had oscillation cycles of 3-5,2-3,1-2 and 1-4 a respectively,and the hail and thunderstorm days changed suddenly in 2002 and 1992 respectively. In space,the Qinghai-Tibet Plateau and western Sichuan were the highvalue distribution areas of hail,gale and thunderstorm days. The high-value distribution areas of thunderstorm days were also distributed to the south of the Yangtze River. South China and its southwestern regions at the same latitude were the high-value distribution areas of lightning days. In terms of trend,the hail days in China showed a decreasing trend mainly in the Qinghai-Tibet Plateau. The gale days in China decreased in the east,was unchanged in the central region,and increased and decreased alternately in the west. The thunderstorm days in China increased in Tibet,North China,Chongqing,Zhejiang and northwestern Heilongjiang. The lightning days in China decreased obviously to the south of the Yangtze River. In terms of the fluctuation,the hail days fluctuated greatly in the southeast. The gale days fluctuated greatly to the east of Hu Huanyong line. The thunderstorms days in China fluctuated greatly in the northwest and slightly in the southeast. In addition to the small fluctuation in northern Xinjiang and South China,the lightning days fluctuated greatly in other regions of China.

Application of Design Patterns in Process of Large-Scale Software Evolving

To search for the Design Patterns’ influence on the software, the paper abstracts the feature models of 9 kinds of classic exiting design patterns among the 23 kinds and describes the features with algorithm language. Meanwhile, searching for the specific structure features in the network, the paper designs 9 matching algorithms of the 9 kinds design patterns mentioned above to research on the structure of the design patterns in the software network. At last, the paper analyzes the evolving trends of the software scale and the application frequency of the 9 kinds of design patterns as the software evolves, and search for the rules how these design patterns are applied into 4 kinds of typical software.

Integrated Evolving Spiking Neural Network and Feature Extraction Methods for Scoliosis Classification

Adolescent Idiopathic Scoliosis(AIS)is a deformity of the spine that affects teenagers.The current method for detecting AIS is based on radiographic images which may increase the risk of cancer growth due to radiation.Photogrammetry is another alternative used to identify AIS by distinguishing the curves of the spine from the surface of a human’s back.Currently,detecting the curve of the spine is manually performed,making it a time-consuming task.To overcome this issue,it is crucial to develop a better model that automatically detects the curve of the spine and classify the types of AIS.This research proposes a new integration of ESNN and Feature Extraction(FE)methods and explores the architecture of ESNN for the AIS classification model.This research identifies the optimal Feature Extraction(FE)methods to reduce computational complexity.The ability of ESNN to provide a fast result with a simplicity and performance capability makes this model suitable to be implemented in a clinical setting where a quick result is crucial.A comparison between the conventional classifier(Support Vector Machine(SVM),Multi-layer Perceptron(MLP)and Random Forest(RF))with the proposed AIS model also be performed on a dataset collected by an orthopedic expert from Hospital Universiti Kebangsaan Malaysia(HUKM).This dataset consists of various photogrammetry images of the human back with different types ofMalaysian AIS patients to solve the scoliosis problem.The process begins by pre-processing the images which includes resizing and converting the captured pictures to gray-scale images.This is then followed by feature extraction,normalization,and classification.The experimental results indicate that the integration of LBP and ESNN achieves higher accuracy compared to the performance of multiple baseline state-of-the-art Machine Learning for AIS classification.This demonstrates the capability of ESNN in classifying the types of AIS based on photogrammetry images.

Evaluation of six gauge-based gridded climate products for analyzing long-term historical precipitation patterns across the Lancang-Mekong River Basin

Freshwater plays a vital role in global sustainability by improving human lives and protecting nature.In the Lancang-Mekong River Basin(LMRB),sustainable development is principally dependent upon precipitation that predominantly controls freshwater resources availability required for both life and livelihood of~70 million people.Hence,this study comprehensively analyzed long-term historical precipitation patterns(in terms of trends,variability,and links to climate teleconnections)throughout the LMRB as well as its upper(Lancang River Basin,LRB)and lower(Mekong River Basin,MRB)parts employing six gauge-based gridded climate products:Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources(APHRODITE),Climate Prediction Center(CPC),Climate Research Unit(CRU),Global Precipitation Climatology Center(GPCC),Precipitation Reconstruction over Land(PRECL),and University of Delaware(UDEL).Accordingly,annual and seasonal(dry and wet)precipitation time series were calculated for three study periods:century-long outlook(1901-2010),mid-past(1951-2010),and recent decades(1981-2010).However,the role of climate teleconnections in precipitation variability over the LMRB was only identified during their available temporal coverages:mid-past and recent decades.The results generally showed that:(i)both annual and seasonal precipitation increased across all three basins in 1981-2010;(ii)wet and dry seasons got drier and wetter,respectively,in all basins in 1951-2010;(iii)all such changes were fundamentally attributed to increases in precipitation variability on both annual and seasonal scales over time;(iv)these variations were most strongly associated with the Pacific Decadal Oscillation(PDO),Atlantic Multi-decadal Oscillation(AMO)and East Pacific/North Pacific(EP/NP)pattern in the LMRB and the MRB during 1951-2010,but with the North Sea-Caspian Pattern(NCP)and the Southern Annular Mode(SAM)in the LRB;(v)such relationships got stronger in 1981-2010,while the Southern Oscillation Index(SOI)became the most influential teleconnection for dry season precipitation variability across all basins;and(vi)GPCC(APHRODITE)provided the most reliable gauge-based gridded precipitation time series over the LMRB for the years before(after)1951.These findings lay a foundation for further studies focusing on water resources and sustainable development in the LMRB.

Sequential Therapy Based on Evolvement of Patterns: A New Model for Treatment of Alzheimer's Disease

In order to solve the problem of long-term (>9 months) efficacy in the treatment of Alzheimer's disease (AD) by conventional therapy (CT), a staged and multiply-targeted sequential therapy based on the evolvement of patterns (STEP) was developed. Its main innovations include:(1) the time order of evolution of patterns defined by Chinese medicine (CM) in AD was found, that is,"the orderly pattern evolution starting from Shen (Kidney) deficiency, progressing to phlegm, stasis and fire, and worsening to severe toxin as well as functional collapse";(2) the cascade hypothesis of Shen deficiency in AD and its sequential therapy based on Shen-reinforcing was proposed, that is,"reinforcing Shen in the early stage and throughout the whole process, resolving phlegm, activating blood and purging fire in the middle stage, detoxifying and replenishing vitality to stop the collapse in the advanced stage", and through meta-analysis, clinical drug use was optimized, thus the leap from "inferential selection" to "evidence-based selection" was realized;(3) the STEP regimen combined with CT maintained cognitive and behavioral stability in AD patients for at least 12 months, with cognitive enhancement and behavioral synergy after 9 months, and cognitive benefit was superior to CT at 9, 12, 15, 18, 21, and 24 months, respectively. The 2-year cognitive improvement rate was increased by 25.64%(P=0.020) and the cognitive deterioration rate was decreased by 48.71%(P=0.000). Among them, the cognitive and functional benefits of Shen-reinforcing therapy for very early AD (350 cases) for 1 year were better than the placebo (P<0.001), and the dementia conversion rate was reduced by 8.85%(P=0.002). The behavioral symptomatic relief of patients with vascular dementia received fire-purging therapy (540 cases) was superior to those received CT (P=0.016). These data suggested that the STEP regimen has synergistic effects on CTs at least in terms of cognitive benefit, and the earlier the use, the greater the benefit will have. Therefore, the STEP regimen should be considered as one of the clinical options, particularly for the dearth of effective pharmaceutical or immunological interventions that are currently available for AD.

Discussion on marine source rocks thermal evolvement patterns in the Tarim Basin and Sichuan Basin,west China

Taking marine source rocks of lower Paleozoic in the Tarim Basin and Paleozoic ones in the Sichuan Basin as examples, their sedimentation process could be classified into four styles: continuous subsidence with deep sedimentation in early stage, continuous subsidence with deep sedimentation in later stage, that deeply buried-uplift-shallowly buried, and that shallowly buried-uplift-deeply buried. Unlike that in East China, the marine source rocks evolvement patterns did not accord with sedimentation styles one by one in superimposed basins in west China. Taking local geothermal field into account, four types of source rock evolvement patterns were built: that evolved fast in early stage, evolved fast in middle stage, evolved continuously and evolved in multistage. Among them, the 1st pattern contributed little to the present industrial oil pools directly, but paleo-oil reservoirs and gases cracked from crude oils were main exploration targets. Although some gases were found in the 2nd pattern, the scale was not big enough. For the 3rd and 4th patterns, the hydrocarbon potential depended on organic matters maturity in early stage. For relatively low mature rocks, it was possible to generate some oils in later stage; otherwise the main products were gases. Paleo-oil reservoirs remained fairly well in the Sichuan Basin, and most source rocks underwent kerogen-oil-gas processes, which was useful reference to gas exploration in the Tarim Basin.

Spatio-temporal patterns and changes in environmental attitudes and place attachment in Gauteng, South Africa

In this study,we employed a number of geospatial techniques to examine the spatiotemporal patterns and changes of environmental attitudes and place attachment values in the Gauteng province of South Africa.The data were obtained from the Gauteng City Region Observatory’s Quality of Life Survey collected at three separate points in time,namely 2013,2015,and 2017.Results indicated that wards(smallest administrative and analysis units)located on the urban periphery of Gauteng,which are generally less affluent,largely held more negative environmental attitudes and place attachment values during the three time periods.In contrast,centrally located wards,which are generally more affluent,expressed more positive environmental attitudes but less place attachment values,especially in 2017.The findings of this research not only highlight the complex spatio-temporal distribution of environmental attitudes and place attachment values throughout Gauteng but also empha-size the need for spatially targeted state interventions for future environmental planning within the province.

Mapping frequent spatio-temporal wind profile patterns using multi-dimensional sequential pattern mining

Holistic understanding of wind behaviour over space,time and height is essential for harvesting wind energy application.This study presents a novel approach for mapping frequent wind profile patterns using multidimensional sequential pattern mining(MDSPM).This study is illustrated with a time series of 24 years of European Centre for Medium-Range Weather Forecasts European Reanalysis-Interim gridded(0.125°×0.125°)wind data for the Netherlands every 6 h and at six height levels.The wind data were first transformed into two spatio-temporal sequence databases(for speed and direction,respectively).Then,the Linear time Closed Itemset Miner Sequence algorithm was used to extract the multidimensional sequential patterns,which were then visualized using a 3D wind rose,a circular histogram and a geographical map.These patterns were further analysed to determine their wind shear coefficients and turbulence intensities as well as their spatial overlap with current areas with wind turbines.Our analysis identified four frequent wind profile patterns.One of them highly suitable to harvest wind energy at a height of 128 m and 68.97%of the geographical area covered by this pattern already contains wind turbines.This study shows that the proposed approach is capable of efficiently extracting meaningful patterns from complex spatio-temporal datasets.

基于县域尺度的江苏省乡村性空间格局演变及其机理研究

基于区域城乡一体的思想构建乡村性指数RI,通过GIS-ESDA空间分析框架,运用空间自相关、空间变差函数等测度模型对20世纪90年代以来县域尺度江苏省乡村性空间格局演变和机理进行了研究。结果表明:1990年以来县域尺度江苏省乡村性表现出较强的空间自相关性,相似地区在空间聚集分布,且集聚的程度不断增强;乡村性热点区空间结构主要以徐州—宿迁—淮安为核心的圈层结构,并且不断向盐城集聚,呈现出明显的地理集中演变特征;县域尺度乡村性空间格局的连续性和自组织性越来越强,由空间自相关引起的结构化分异的机理越来越显著;东北—西南方向乡村性空间差异较小,东南—西北方向乡村性的异质性则十分明显,空间差异较大。

演变图上的连接子图演变模式挖掘

探讨演变图(即随时间变化的图)的挖掘,重点研究在演变图中挖掘连接子图的演变模式集合.提出一种连接子图的相似度函数及其快速计算算法.基于该相似度函数,提出一种发现演变模式集合的多项式时间复杂度的动态规划算法.模拟数据集上的实验结果表明,该算法具有较低的误差率和较高的效率.真实数据集上的实验结果表明,挖掘结果在真实应用中具有实际意义.