基于马氏距离和Canopy改进K-means的交通聚类算法

在对交通数据的研究中经常会使用到聚类算法,且不同的聚类算法有不同的特性。K-means作为其中的一种聚类算法,具有较高的准确性和实用性,但其准确性易受主观选取K值和确定初始聚类中心的影响。为了优化聚类中心和K值的选取问题,提出MC-Kmeans算法。在所提方法中,首先通过Canopy算法选取K值,然后依据马氏距离的计算准则来确定初始聚类中心,最后将K值和聚类中心的值作为K-means的参数进行聚类。将MC-Kmeans算法应用到某时间段的纽约出租车交通数据中进行实际的验证。结果表明,与K-means算法比较,所提方法准确度更高,与实际交通情况更加相匹配,更能反映区域内的交通热点情况。

基于信息熵和Canopy-K-Means算法的货车驾驶风格识别

为识别货车的激进驾驶行为,保障货车行车安全,提出1种基于信息熵和Canopy-K-Means算法的货车驾驶风格识别方法。首先,从货车自然驾驶数据中提取出604个驾驶片段,根据信息熵理论计算各个驾驶片段的速度熵值、横向加速度熵值和纵向加速度熵值,构成货车驾驶风格表征指标集;其次,针对K-Means算法的聚类数量主观选取、初始聚类中心随机选取的问题,使用Canopy算法改进K-Means算法(Canopy-K-Means算法);最后,分别使用K-Means算法和Canopy-K-Means算法对货车驾驶风格进行识别。研究结果显示,Canopy-K-Means算法的轮廓系数和Calinski-Harabasz指数均大于K-Means算法,表现出更优的聚类性能。根据Canopy-K-Means算法,可将货车驾驶风格分为沉稳型、常规型和激进型3类,其中激进型货车驾驶风格的指标熵值和极差均较大,存在较高的安全隐患,需要引起相关部门的高度重视。

基于改进的Canopy-k-means的大跨屋盖表面风荷载分区方法

针对k-means聚类算法在大跨屋盖结构表面风荷载分区计算中,聚类数k值随机选取容易导致结果不稳定和计算效率低等问题,提出改进的Canopy-k-means聚类算法。首先,引入Canopy算法并对其初始阈值和聚类中心的选取方式进行改进,减少初始值选取的盲目性,以提高风荷载分区结果的可靠性;其次,通过改进Canopy算法对风荷载数据集进行预处理,快速准确地确定聚类数k值;第三,将改进Canopy算法与k-means结合使用,实现最优分类数k值的精准识别,使得改进的Canopy-k-means聚类算法进行大跨屋盖结构表面风荷载分区时能够快速准确地得到分区结果;最后,以一大跨柱面屋盖干煤棚结构为例,基于风洞试验所得结构表面风荷载数据测试结果,采用所提改进的Canopy-k-means聚类算法对其表面风荷载进行分区计算。结果表明,采用改进的Canopy-k-means聚类算法,将0°、50°和90°风向角时大跨屋盖表面风荷载划分为了3个不同的分区,其对应的SD值分别为2.36、3.51和2.52,较传统k-means聚类算法所得对应值明显降低,类内紧凑性和类间分散性明显提升。所提改进Canopy-k-means聚类算法能够快速准确地得到最优分区结果,对大跨屋盖表面风荷载分区具有工程参考价值。

核电站控制棒驱动机构Canopy焊缝焊接温度场和应力-应变场模拟

目的研究机加工和拉拔2种成形方式下得到的填充环对Canopy焊缝的影响,获取焊接焊缝成形、焊接残余应力和变形的相关数据,以指导Canopy焊缝焊接工艺。方法采用数值模拟的方法,建立Canopy焊缝焊接数值分析模型,模拟焊接温度场、焊接残余应力和焊接残余变形。结果拉拔成形环焊接熔池高度为9 mm,机加工成形环焊接熔池高度为8.3 mm;机加工成形环焊接最大残余应力为255.6 MPa,而拉拔成形环焊接最大残余应力为277.8 MPa,均出现在管座紧贴焊缝的位置;机加工成形环焊接残余变形为0.19 mm,拉拔成形环焊接残余变形为0.186 mm,最大残余变形均出现在焊接起始位置附近,在焊缝与管座交接的位置。结论熔池形貌直接影响了热影响区域的大小,拉拔Y型环焊接熔池高度更大,焊接的热影响区域更大;拉拔Y型环焊接残余应力略大于机加工Y型环焊接残余应力;机加工成形环和拉拔成形环焊接残余变形相近。

Rice canopy temperature is affected by nitrogen fertilizer

Canopy temperature strongly influences crop yield formation and is closely related to plant physiological traits.However, the effects of nitrogen treatment on canopy temperature and rice growth have yet to be comprehensively examined. We conducted a two-year field experiment with three rice varieties(HD-5, NJ-9108, and YJ-805) and three nitrogen treatments(zero-N control(CK), 200 kg ha~(–1)(MN), and 300 kg ha~(–1)(HN)). We measured canopy temperature using a drone equipped with a high-precision camera at the six stages of the growth period. Generally,canopy temperature was significantly higher for CK than for MN and HN during the tillering, jointing, booting, and heading stages. The temperature was not significantly different among the nitrogen treatments between the milky and waxy stages. The canopy temperature of different rice varieties was found to follow the order: HD-5>NJ-9108>YJ-805, but the difference was not significant. The canopy temperature of rice was mainly related to plant traits, such as shoot fresh weight(correlation coefficient r=–0.895), plant water content(–0.912), net photosynthesis(–0.84), stomatal conductance(–0.91), transpiration rate(–0.90), and leaf stomatal area(–0.83). A structural equation model(SEM) showed that nitrogen fertilizer was an important factor affecting the rice canopy temperature.Our study revealed:(1) A suite of plant traits was associated with the nitrogen effects on canopy temperature,(2) the heading stage was the best time to observe rice canopy temperature, and(3) at that stage, canopy temperature was negatively correlated with rice yield, panicle number, and grain number per panicle. This study suggests that canopy temperature can be a convenient and accurate indicator of rice growth and yield prediction.

Drought events influence nutrient canopy exchanges and green leaf partitioning during senescence in a deciduous forest

The increase in the frequency and intensity of drought events expected in the coming decades in Western Europe may disturb forest biogeochemical cycles and create nutrient deficiencies in trees.One possible origin of nutrient deficiency is the disturbance of the partitioning of the green leaf pool during the leaf senescence period between resorption,foliar leaching and senesced leaves.However,the effects of drought events on this partitioning and the consequences for the maintenance of tree nutrition are poorly documented.An experiment in a beech forest in Meuse(France)was conducted to assess the effect of drought events on nutrient canopy exchanges and on the partitioning of the green leaf pool during the leaf senescence period.The aim was to identify potential nutritional consequences of droughts for trees.Monitoring nutrient dynamics,including resorption,chemistry of green and senesced leaves,foliar absorption and leaching in mature beech stands from 2012 to 2019 allowed us to compare the nutrient exchanges for three nondry and three dry years(i.e.,with an intense drought event during the growing season).During dry years,we observed a decrease by almost a third of the potassium(K)partitioning to resorption(i.e.resorption efficiency),thus reducing the K reserve in trees for the next growing season.This result suggests that with the increased drought frequency and intensity expected for the coming decades,there will be a risk of potassium deficiency in trees,as already observed in a rainfall exclusion experiment on the same study site.Reduced foliar leaching and higher parititioning to the senesced leaves for K and phosphorus(P)were also observed.In addition,a slight increase in nitrogen(N)resorption efficiency occurred during dry years which is more likely to improve tree nutrition.The calcium(Ca)negative resorption decreased,with no apparent consequence in our study site.Our results show that nutrient exchanges in the canopy and the partitioning of the green leaf pool can be modified by drought events,and may have consequences on tree nutrition.

Effects of dust controls on respirable coal mine dust composition and particle sizes:case studies on auxiliary scrubbers and canopy air curtain

Control of dust in underground coal mines is critical for mitigating both safety and health hazards.For decades,the National Institute of Occupational Safety and Health(NIOSH)has led research to evaluate the effectiveness of various dust control technologies in coal mines.Recent studies have included the evaluation of auxiliary scrubbers to reduce respirable dust downstream of active mining and the use of canopy air curtains(CACs)to reduce respirable dust in key operator positions.While detailed dust characterization was not a focus of such studies,this is a growing area of interest.Using preserved filter samples from three previous NIOSH studies,the current work aims to explore the effect of two different scrubbers(one wet and one dry)and a roof bolter CAC on respirable dust composition and particle size distribution.For this,the preserved filter samples were analyzed by thermogravimetric analysis and/or scanning electron microscopy with energy dispersive X-ray.Results indicate that dust composition was not appreciably affected by either scrubber or the CAC.However,the wet scrubber and CAC appeared to decrease the overall particle size distribution.Such an effect of the dry scrubber was not consistently observed,but this is probably related to the particular sampling location downstream of the scrubber which allowed for significant mixing of the scrubber exhaust and other return air.Aside from the insights gained with respect to the three specific dust control case studies revisited here,this work demonstrates the value of preserved dust samples for follow-up investigation more broadly.

The influences of canopy temperature measuring on the derived crop water stress index

Crop water stress index(CWSI)is widely used for efficient irrigation management.Precise canopy temperature(T_(c))measurement is necessary to derive a reliable CWSI.The objective of this research was to investigate the influences of atmospheric conditions,settled height,view angle of infrared thermography,and investigating time of temperature measuring on the performance of the CWSI.Three irrigation treatments were used to create different soil water conditions during the 2020-2021 and 2021-2022 winter wheat-growing seasons.The CWSI was calculated using the CWSI-E(an empirical approach)and CWSI-T(a theoretical approach)based on the T_(c).Weather conditions were recorded continuously throughout the experimental period.The results showed that atmospheric conditions influenced the estimation of the CWSI;when the vapor pressure deficit(VPD)was>2000 Pa,the estimated CWSI was related to soil water conditions.The height of the installed infrared thermograph influenced the T_(c)values,and the differences among the T_(c)values measured at height of 3,5,and 10 m was smaller in the afternoon than in the morning.However,the lens of the thermometer facing south recorded a higher T_(c)than those facing east or north,especially at a low height,indicating that the direction of the thermometer had a significant influence on T_(c).There was a large variation in CWSI derived at different times of the day,and the midday measurements(12:00-15:00)were the most reliable for estimating CWSI.Negative linear relationships were found between the transpiration rate and CWSI-E(R^(2)of 0.3646-0.5725)and CWSI-T(R^(2)of 0.5407-0.7213).The relations between fraction of available soil water(FASW)with CWSI-T was higher than that with CWSI-E,indicating CWSI-T was more accurate for predicting crop water status.In addition,The R^(2)between CWSI-T and FASW at 14:00 was higher than that at other times,indicating that 14:00 was the optimal time for using the CWSI for crop water status monitoring.Relative higher yield of winter wheat was obtained with average seasonal values of CWSI-E and CWSI-T around 0.23 and 0.25-0.26,respectively.The CWSI-E values were more easily influenced by meteorological factors and the timing of the measurements,and using the theoretical approach to derive the CWSI was recommended for precise irrigation water management.

Fuzzy C-Means Algorithm Based on Density Canopy and Manifold Learning

Fuzzy C-Means(FCM)is an effective and widely used clustering algorithm,but there are still some problems.considering the number of clusters must be determined manually,the local optimal solutions is easily influenced by the random selection of initial cluster centers,and the performance of Euclid distance in complex high-dimensional data is poor.To solve the above problems,the improved FCM clustering algorithm based on density Canopy and Manifold learning(DM-FCM)is proposed.First,a density Canopy algorithm based on improved local density is proposed to automatically deter-mine the number of clusters and initial cluster centers,which improves the self-adaptability and stability of the algorithm.Then,considering that high-dimensional data often present a nonlinear structure,the manifold learning method is applied to construct a manifold spatial structure,which preserves the global geometric properties of complex high-dimensional data and improves the clustering effect of the algorithm on complex high-dimensional datasets.Fowlkes-Mallows Index(FMI),the weighted average of homogeneity and completeness(V-measure),Adjusted Mutual Information(AMI),and Adjusted Rand Index(ARI)are used as performance measures of clustering algorithms.The experimental results show that the manifold learning method is the superior distance measure,and the algorithm improves the clustering accuracy and performs superiorly in the clustering of low-dimensional and complex high-dimensional data.

Analysis on the Application and Improvement of Canopy without Sunshade Curtain

Nowadays,in order to expand the roof view to bring passengers closer to nature,more and more new energy vehicles are opting for canopy designs without sunshades.However,after removing traditional sunshades,new solutions must be sought to address issues such as heat insulation,glaring sunlight,and interior reflections from the roof glass during the summer months.This paper conducts an in-depth analysis of the technical advantages and shortcomings of sunshade-free canopy in terms of heat insulation and interior reflections during summer,from both theoretical analysis and experimental comparison perspectives,and proposes improvement strategies.The research results indicate that although the panoramic roof enhances the vehicle's interior view and technological appeal,it still has shortcomings in terms of heat insulation and the problem of interior reflections caused by direct sunlight.The proposed improvement strategies can effectively mitigate these issues,and offers consumers more comfortable and intelligent driving experiences.

不同Y形环应用于核电站控制棒驱动机构Canopy焊缝焊接工艺及焊缝性能的研究

试验采用两种机械加工Y形环和一种拉拔Y形环应用于核电站控制棒驱动机构Canopy焊缝,研究不同Y形环对Canopy焊缝焊接工艺及焊缝性能的影响。结果表明:机械加工Y形环为整圈环,相比拉拔Y形环,更有利于定位焊;机械加工Y形环(控公差)与拉拔Y形环装配间隙范围相当,比机械加工Y形环装配间隙范围大,更有利于工程应用;3种Y形环熔成的Canopy焊缝组织主要由铁素体和柱状奥氏体组成,无明显差异;3种Y形环熔成的Canopy焊缝经23.1~23.3MPa水压试验,焊缝表面均无渗漏,无可见变形。该研究为机械加工Y形环应用于核电站控制棒驱动机构Canopy焊缝提供了宝贵的经验。

核电站控制棒驱动机构Canopy焊缝组织和性能研究

试验采用专用自动TIG焊机焊接核电站控制棒驱动机构Canopy焊缝,选用机械加工Y形环作为填充材料,研究Canopy焊缝组织和性能。结果表明:通过自动TIG焊,机械加工Y形环熔成的Canopy焊缝,成形良好,宽度适中,焊缝与母材冶金熔合良好;焊缝组织主要由板条状或骨架状铁素体与快速凝固的柱状奥氏体组成;经23.1~23.3MPa水压试验,Canopy焊缝表面无渗漏,无可见变形;维氏硬度结果表明:焊缝硬度在210HV左右,焊缝硬度分布均匀。该研究为核电站控制棒驱动机构Canopy焊缝用机械加工Y形环提供了宝贵的经验。

基于油中溶解气体Canopy高维模型的变压器异常状态快速识别方法

在线油中溶解气体数据是电力变压器重要状态参数,故障诊断前首先要识别异常。针对当前异常识别方法受数据波动、缺失影响大及运算时间长的问题,提出基于油中溶解气体Canopy高维模型的变压器异常状态快速识别方法。该文分析在线油中溶解气体数据质量,提出基于滑窗的离群点识别方法,引入波动系数评价数据质量,根据特征气体波动系数建立变权高维空间,抑制识别中波动大的气体影响。针对缺失值,在变权高维空间上利用Canopy簇合并算法对状态进区分,结合异常事件库对异常状态进行识别。对比该方法与K-Means聚类算法,该方法可改善状态边界数据的分类效果,并减小计算量。将该方法应用于现场检测,可有效识别未达到注意阈值的过热异常案例,并且避免数据质量差导致的过阈值误报。

压水堆控制棒驱动机构CANOPY密封焊缝服役环境与失效

综述了国际上对PWR核电站控制棒驱动机构密封焊缝(CSWs)结构、载荷、应力状态、失效分析的研究。研究认为CSWs的结构设计易造成高溶解氧服役环境,在CSWs死水区空腔存在微量氯离子污染的可能,导致较大应力腐蚀倾向。目前研究确认的失效模式有穿晶应力腐蚀(TGSCC)、沿晶应力腐蚀(IGSCC)、SCC+点蚀。计算出CSWs死水区空腔理论浓度可达230×10^(-6),分析认为溶解氧和低浓度水平的氯污染是可引起上述腐蚀的环境因素;CSWs应力腐蚀裂纹扩展模式与材料敏化、服役溶液环境、初始应变、应力状态等因素相关;点蚀可能成为应力腐蚀的起源也可发展成为独立的破坏形式。

开发区升格政策能促进企业创新增量提质吗?

通过构建多时点DID模型实证检验开发区升格政策对企业创新数量和创新质量的影响,结果表明:省级开发区升格通过降低制度性交易成本、提升市场化程度和加速创新要素流入对企业创新产出数量和产出质量产生促进作用,该政策对非民营企业、非高技术制造行业、高新区和小规模城市的作用效果更强。因此,要充分发挥开发区“以升促建”的创新激励效应,不仅要注重有为政府和有效市场的结合,还要根据城市固有经济特征优化开发区制度环境。

Effects of Elevated CO 2 and High Temperature on Single Leaf and Canopy Photosynthesis of Rice

The increase of atmospheric CO 2 concentration is indisputable. In such condition, photosynthetic response of leaf is relatively well studied, while the comparison of that between single leaf and whole canopy is less emphasized. The stimulation of elevated CO 2 on canopy photosynthesis may be different from that on single leaf level. In this study, leaf and canopy photosynthesis of rice (Oryza sativa L.) were studied throughout the growing season. High CO 2 and temperature had a synergetic stimulation on single leaf photosynthetic rate until grain filling. Photosynthesis of leaf was stimulated by high CO 2, although the stimulation was decreased by higher temperature at grain filling stage. On the other hand, the simulation of elevated CO 2 on canopy photosynthesis leveled off with time. Stimulation at canopy level disappeared by grain filling stage in both temperature treatments. Green leaf area index was not significantly affected by CO 2 at maturity, but greater in plants grown at higher temperature. Leaf nitrogen content decreased with the increase of CO 2 concentration although it was not statistically significant at maturity. Canopy respiration rate increased at flowering stage indicating higher carbon loss. Shading effect caused by leaf development reached maximum at flowering stage. The CO 2 stimulation on photosynthesis was greater in single leaf than in canopy. Since enhanced CO 2 significantly increased biomass of rice stems and panicles, increase in canopy respiration caused diminishment of CO 2 stimulation in canopy net photosynthesis. Leaf nitrogen in the canopy level decreased with CO 2 concentration and may eventually hasten CO 2 stimulation on canopy photosynthesis. Early senescence of canopy leaves in high CO 2 is also a possible cause.

Influence of canopy on precipitation and its nutrient elements in broadleaved/Korean pine forest on the northern slope of Changbai Mountain

The precipitation distribution quantity of canopy in broadleaved/Korean pine forest was measured during the growing season (Jun.–Sept.) in 2001 in the Changbai Mountain, Jilin Province, P. R. China. Results indicated that the amounts of stemflow, throughfall, and interception were 37.39, 322.12 and 109.69 mm, accounting for 7.97%, 68.65% and 23.38% of the total rainfall, respectively. The rate of stemflow was higher in Jul. and Aug. than other months. The rate of throughfall dropped off from Jun. to Sept., however, rate of interception changed contrarily from 19.43% to 31.02% during the growing season. According to our analysis, the concentration of nutrient elements were arranged as Ca>Mg>N>K>Fe>P>Cu>Mn for rainfall, K>N>Mg>Ca>P>Fe>Mn>Cu for throughfall, and Mn>P>K>Cu>Fe>N>Mg>Ca for being leached through canopy. Nutrients concentration in stewflow and throughfall changed significantly when rainfall passed canopy, and concentration of all elements increased except for Ca and Mg.

基于Openness可视化参数的二维地貌显示

Openness是一种二维地貌的可视化参数,不受光源设置和邻近地形遮蔽的影响,更强调地形的凹凸,使得直观的立体感更强。该参数不仅可以从多种来源的DEM数据计算获取,也可以用于不同精细程度的地貌分析。闽江入海口地区具有丰富的构造地貌类型,基于SRTM(90 m)高程数据计算该地区的Openness参数,探讨该参数在地形地貌方面的初步应用。通过闽江入海口地区构造地貌的分析结果表明,Openness参数方法比传统的地形晕渲等常用二维可视化方法编制的图件效果更好,更强调地形的凹凸感,能够更详细地反映实际地形地貌的细节。

基于Canopy聚类的谱聚类算法

传统的谱聚类算法对初始化敏感,针对这个缺陷,引入Canopy算法对样本进行“粗”聚类得到初始聚类中心点,将结果作为K-Means算法的输入,提出了一种基于Canopy和谱聚类融合的聚类算法(Canopy-SC),减少了传统谱聚类算法选择初始中心点的盲目性,并将其用于人脸图像聚类。与传统的谱聚类算法相比,Canopy-SC算法能够得到较好的聚类中心和聚类结果,同时具有更高的聚类精确度。实验结果表明了该算法的有效性和可行性。

低空经济的内涵、特征和运行模式

低空经济作为低空飞行活动与产业融合的新型综合性经济形态,具有空间立体性、区域依赖性、数字生态性、产业融合性以及辐射带动性等特征。党和政府高度重视发展低空经济,将其确定为国家战略性新兴产业,各地加紧布局,发展势头良好。但具体实践中仍存在发展低空经济的体制机制不畅、技术创新支持不足、新型基础设施不全、产业领域需不断拓展等问题。针对上述问题,文本依据螺旋理论,提出“政产学研金服用”的低空经济开放式创新生态模式。