High Dimension Multivariate Data Analysis for Small Group Samples of Chemical Volatile Profiles of African Nightshade Species

Quantitative headspace analysis of volatiles emitted by plants or any other living organisms in chemical ecology studies generates large multidimensional data that require extensive mining and refining to extract useful information. More often the number of variables and the quantified volatile compounds exceed the number of observations or samples and hence many traditional statistical analysis methods become inefficient. Here, we employed machine learning algorithm, random forest (RF) in combination with distance-based procedure, similarity percentage (SIMPER) as preprocessing steps to reduce the data dimensionality in the chemical profiles of volatiles from three African nightshade plant species before subjecting the data to non-metric multidimensional scaling (NMDS). In addition, non-parametric methods namely permutational multivariate analysis of variance (PERMANOVA) and analysis of similarities (ANOSIM) were applied to test hypothesis of differences among the African nightshade species based on the volatiles profiles and ascertain the patterns revealed by NMDS plots. Our results revealed that there were significant differences among the African nightshade species when the data’s dimension was reduced using RF variable importance and SIMPER, as also supported by NMDS plots that showed S. scabrum being separated from S. villosum and S. sarrachoides based on the reduced data variables. The novelty of our work is on the merits of using data reduction techniques to successfully reveal differences in groups which could have otherwise not been the case if the analysis were performed on the entire original data matrix characterized by small samples. The R code used in the analysis has been shared herein for interested researchers to customise it for their own data of similar nature.

Similarity measurement method of high-dimensional data based on normalized net lattice subspace

The performance of conventional similarity measurement methods is affected seriously by the curse of dimensionality of high-dimensional data.The reason is that data difference between sparse and noisy dimensionalities occupies a large proportion of the similarity,leading to the dissimilarities between any results.A similarity measurement method of high-dimensional data based on normalized net lattice subspace is proposed.The data range of each dimension is divided into several intervals,and the components in different dimensions are mapped onto the corresponding interval.Only the component in the same or adjacent interval is used to calculate the similarity.To validate this method,three data types are used,and seven common similarity measurement methods are compared.The experimental result indicates that the relative difference of the method is increasing with the dimensionality and is approximately two or three orders of magnitude higher than the conventional method.In addition,the similarity range of this method in different dimensions is [0,1],which is fit for similarity analysis after dimensionality reduction.

Local Similarity Relationships of Non-Dimensional Wind and Temperature Gradient in the Tower-Layer Atmosphere over Beijing City

Micrometeorological data for wind and temperature from a 325 m high tower in Beijing City are analyzed by use of local similarity theory. Non-dimensional wind and temperature gradients, Phi(m) and Phi(h), are determined by three techniques called, respectively, eddy-correlation, mean profiles and inertia-subrange cospectra (ISC) method for a wide range of atmospheric stratification from unstable to stable conditions. Average dissipation rate Phi(e) of turbulent kinetic energy (TKE) is evaluated from u-spectrum, as a quantity required in the last technique. Ratio of the eddy transfer coefficients, alpha(= K-h / K-m), is calculated from Phi(m) and Phi(h) estimations. The results from various techniques are compared with each other and with some available empirical results in the tower-layer, It is shown that the empirical relationships determined by mean profiles and ISC methods in the lower-layer turbulence ore in agreement with each other and with some other results.

Dimensional and Mechanical Similarity Analysis of the Flow in Rotating Liquid Film Reactor

A rotating liquid film reactor (RLFR) is a device of two coaxial rotating conical cylinders with the inner cone rotating and the outer one stationary. A complete mathematical model for the flow between the conical cylinders is built and a dimensional analysis is carried out. It is proved that at each point of the flow field the dimensionless pressure and velocity of the flow are determined by parameters: Reynolds number (Re), aspect ratio (Γ), radius ratio (η) and wall inclination angle (α). Furthermore, a sufficient and a necessary condition are derived from mechanical similarity between RLFR and a manufacturing equipment geometrically similar to RLFR. Finally, a numerical simulation for the distribution of pressure and velocity is performed. The results may provide a theoretical basis for experiment method and numerical simulation of the flow in a RLFR-like device.

基于三维空间面积划分的轨迹相似性度量算法

针对大部分轨迹相似性度量算法无法区分方向相反轨迹的问题,提出了一种基于三维空间面积划分的三维三角分割(3TD)算法。首先,按照3TD算法的时间转换规则将轨迹集的绝对时间序列转变为相对时间序列;然后,在由经度、纬度以及时间三要素构成的三维空间坐标系中,通过划分规则将轨迹间面积分割成若干互不重叠的三角形,累加三角形面积并计算轨迹相似度;最后,在从船舶自动识别系统(AIS)收集的随机采样轨迹数据集上,与最长公共子序列(LCSS)算法和三角分割(TD)算法等进行了对比实验。实验结果表明:3TD算法对实验数据集中异向轨迹识别精确度达到100%;同时该算法面对海量数据集以及轨迹点部分缺失的数据集时,也能维持准确的度量结果以及较高的运算效率,能更好地适应异向轨迹相似度量工作。

Modified (2+1)-dimensional displacement shallow water wave system and its approximate similarity solutions

Recently, a new （2＋1）-dimensional shallow water wave system, the （2＋1）-dlmenslonal displacement shallow water wave system （2DDSWWS）, was constructed by applying the variational principle of the analytic mechanics in the Lagrange coordinates. The disadvantage is that fluid viscidity is not considered in the 2DDSWWS, which is the same as the famous Kadomtsev-Petviashvili equation and Korteweg-de Vries equation. Applying dimensional analysis, we modify the 2DDSWWS and add the term related to the fluid viscidity to the 2DDSWWS. The approximate similarity solutions of the modified 2DDSWWS （M2DDSWWS） is studied and four similarity solutions are obtained. For the perfect fluids, the coefficient of kinematic viscosity is zero, then the M2DDSWWS will degenerate to the 2DDSWWS.

电路的量纲模型与相似性原理和对偶性原理

宇宙量纲模型的思想适用于任何系统,物理系统适用,电路系统也同样适用。系统地分析总结了电路运行的基本原理,确定了电路系统的量纲,提出了电路的量纲模型、相似性原理和对偶性原理及规律拓展性原理等概念,并给出了相似性原理和对偶性原理的一些应用实例。

综合天气相似分析方法及其气象预报服务应用

为改进传统“切片”式天气形势相似分析方法存在的不同切片相似结果不一致、预报稳定性欠佳问题,借鉴大数据思维,将天气系统视为一个由高中低层大气相互配合、静力热力动力条件相互影响的综合体,以多种气象要素再分析格点资料为基础,采用机器学习PCA方法对原始数据进行降维、浓缩,经归一化处理后构建出适于综合天气相似分析的样本衍生特征因子矩阵;然后使用KNN算法计算样本间各特征维度的相似距离、并结合方差贡献率赋予其相应的权重,最终按综合相似距离大小排序给出目标样本在历史天气形势库中的综合最相似序列,从而实现对传统相似天气预报方法的升级改进。对比分析和测试应用表明,该方法可提供多要素、多层次“立体”综合相似下的一致性结论,有助于预报员更好地理解天气系统结构和演变过程、进而更准确地研判可能发生的相关天气现象,在精细化气象预报服务方面有良好的应用前景。在2023年以来的几次广西区域性极端降水气象预报服务中,该方法取得了较为显著的应用效果。

基于量纲分析的深埋硬岩相似材料研究

为获得具有岩爆倾向性的深埋灰岩相似模型,基于量纲分析方法引入岩爆能量原理建立岩爆相似准则,参考原岩相关参数结合岩爆相似准则推算相似模型对应的原岩目标相关参数。引入岩爆倾向性指数、弹性能和耗散能,以石英粉含量、重晶石粉含量、石膏水泥质量比、水含量为影响因素采用4因素5水平的正交试验方案,进行单轴抗压试验得到各项参数。对试验结果进行敏感性分析并将优选试件进行二次优化试验完善配比,将试件与目标相似模型参数误差降低在10%以内,结果表明,二次优化后的模型试件与目标相似模型误差为5%。对优化后的试件设置不同的冲击速度进行动态冲击力学试验,其峰值应力规律符合灰岩动态破坏时规律,为灰岩室内静力学与动力学相关研究提供参考。

曲线链式回转弹仓动力学模型不确定参数辨识

为了准确模拟曲线链式回转弹仓输送弹药过程中的非线性动力学特性,根据系统的拓扑结构和控制原理建立包含不确定参数的动力学模型。利用优化设计思想,基于系统测试数据建立不确定参数辨识模型。提出一种函数型时间序列相似度作为辨识准则,采用基于径向基函数的高维模型表示和径向基函数分别构建从机械系统和控制系统不确定参数到辨识准则的代理模型。将麻雀搜索算法嵌入岛屿模型进行多种群结构化,形成岛屿麻雀搜索算法,进行寻优求解。以工况1测试数据为基准,对机械系统和控制系统的不确定参数进行辨识。研究结果表明,辨识后的动力学模型对两种工况的输出结果与测试数据相似度较高,验证了建模的准确性和辨识的有效性,为动作可靠性分析和故障诊断研究提供了可靠的样本数据来源。

关于水流挟沙力的非完全自相似分析

张瑞瑾挟沙力公式在泥沙工程计算中已得到广泛应用,然而如何确定公式中的系数和指数,目前尚无有效的直接计算方法。从量纲分析入手,基于非完全自相似原理,提出了一种新的挟沙力分析方法,并采用水槽实验资料进行了检验和详细说明。分析结果表明:张瑞瑾公式中的指数可表达为V/ω(其中V为水流平均流速,ω为泥沙颗粒沉速)的对数函数,而其系数则与V/ω成幂函数关系。通过考虑V/ω对公式系数和指数的影响后,挟沙力公式的预测精度明显提高,计算误差可减少36%~49%。由于所用资料的范围有限,提出的公式普适性有待验证,但所采用的分析方法可能也适用于其他挟沙力问题。

煤矿开采二维物理相似模拟试验平台

提出了一种煤矿开采二维物理相似模拟试验平台。该平台具有可模拟煤矿开采1000 m埋深以内的地应力、可调角度、可做垂向及两侧地应力模拟加载、可模拟煤层开采等功能,并经有限元分析验证了其强度和刚度。该平台可以为煤矿开采的安全和高效提供重要的技术支撑。

三维荧光结合区域积分鉴别酸枣仁及其掺伪品

目的:研究建立酸枣仁三维荧光光谱鉴别方法,为酸枣仁真伪鉴别提供依据。方法:建立6批不同产地酸枣仁三维荧光光谱,并利用三维荧光技术对2批酸枣仁伪品、3批掺伪品鉴别分析,采用荧光区域积分法对不同产地酸枣仁、酸枣仁伪品及掺伪品三维荧光图谱进行区域积分,将区域积分值进行相似度评价、聚类分析和主成分分析。结果:相似度结果显示,不同产地酸枣仁三维荧光图谱相似性均为1,相似性极高;聚类结果与主成分分析结果一致,明确将样品分为3类,均能通过区域积分值实现酸枣仁正品、伪品、掺伪品的区分。结论:利用三维荧光技术可以对不同产地酸枣仁质量进行一致性评价,实现酸枣仁真伪的快速鉴别,为酸枣仁的质量评价提供参考。

基于SVM的多维相似大数据分类系统设计

受大数据自身相似性的影响,传统数据分类方式的分类精度偏低,为此提出基于支持向量机(Support Vector Machine,SVM)的多维相似大数据分类系统设计研究。将MYC-JX8MMA7核心板作为系统设计的开发载体,构建SVM线性回归模型,通过构建一个回归平面,保障所有多维相似大数据与平面之间的距离均处于最小状态,利用待分类数据与最佳分类界面被标记样本之间的相似度,实现对数据的分类。在测试结果中,分类结果F1 Score稳定在0.82以上,明显优于对照组。

多维信息感知地标匹配的PDR定位算法

针对行人航位推算(Pedestrian Dead Reckoning,PDR)室内定位系统的累计误差问题,提出了一种多维信息感知地标匹配的PDR定位算法(PDR positioning algorithm based Multi-imensional Information Perception Landmark Matching,MIPLM)。算法利用行人在室内走廊环境下的众包轨迹,并基于突出性路口结构,从位置、航向、影响范围以及WiFi特征指纹等方面构建多维信息感知地标库。给出的自适应地标检测算法,结合航向约束轨迹相似度匹配模型,更新行人位置和航向,避免了本地化匹配过程对空间位置的强依赖性。实验结果表明,相比于其他地标构建及匹配算法,所提算法更好地反映了行人活动与室内空间结构的相关性,且在未知起始位置时,算法能够快速收敛并提供较高的定位精度,对于室内行人连续定位具有较高的应用价值。

基于倾斜摄影测量的建筑模型单体化方法

实景三维模型是一种三维虚拟展示的数字空间,能够对空间进行真实、立体化表达。然而,连续的实景三维模型无法对对象进行单独管理与分析。针对此问题,本文基于实景三维模型,提出了一种分层“切割”与多边形几何相似性判定的建筑模型单体化方法。该方法实现建筑模型单体化的思路为:首先,对不同高程面的建筑物三角格网进行投影等处理,得到建筑初始轮廓;其次,采用多边形空间相似性判定方法提取建筑轮廓;最后,对单体化模型进行渲染,实现单个建筑模型的三维构建。通过实验对本方法进行验证,结果表明本文方法能够高效、自动实现建筑单体化构建,为模型中建筑对象的管理与分析提供了便利,对于当前实景中国建设的实体化处理提供了一定的参考。

基于H型指数的AI多维知识地图信息检索研究

当前的传统信息检索系统无法有效识别出AI地图的多维信息。为此,提出基于H型指数的AI多维知识地图信息检索方法。该方法对AI多维知识地图数据信息完成相似性计算,获取地图信息的相似度值,并结合H型指数获取地图信息的中心性指标;通过确定的检索边界以及选取的模型参数,构建地图信息的多维检索模型,通过模型求解结果,实现信息的检索。实验结果表明,该方法应用下,检索时间短,查全率、查准率均高于90%。

Three-dimensional physical simulation and optimization of water injection of a multi-well fractured-vuggy unit

With complex fractured-vuggy heterogeneous structures, water has to be injected to facilitate oil pro- duction. However, the effect of different water injection modes on oil recovery varies. The limitation of existing numerical simulation methods in representing fractured- vuggy carbonate reservoirs makes numerical simulation difficult to characterize the fluid flow in these reservoirs. In this paper, based on a geological example unit in the Tahe Oilfield, a three-dimensional physical model was designed and constructed to simulate fluid flow in a fractured-vuggy reservoir according to similarity criteria. The model was validated by simulating a bottom water drive reservoir, and then subsequent water injection modes were optimized. These were continuous （constant rate）, intermittent, and pulsed injection of water. Experimental results reveal that due to the unbalanced formation pressure caused by pulsed water injection, the swept volume was expanded and consequently the highest oil recovery increment was achieved. Similar to continuous water injection, intermit- tent injection was influenced by factors including the connectivity of the fractured-vuggy reservoir, well depth, and the injection-production relationship, which led to a relative low oil recovery. This study may provide a constructive guide to field production and for the devel- opment of the commercial numerical models specialized for fractured-vuggy carbonate reservoirs.

采动岩层全空间“类双曲面”立体移动模型

基于大量现场调研及岩层移动内外“类双曲线”移动模型分析,本文对哈拉沟煤矿厚松散岩层煤层开挖展开了物理相似模型试验,验证了内外“类双曲线”整体移动模型的有效性;将其推广到三维空间,提出采动岩层全空间“类双曲面”立体移动模型。该模型包含“类单叶”、“类双叶”两类双曲面,能近似描述不同岩性条件下全空间采动岩层立体移动与地表沉陷特征。“类单叶双曲面”模型为空间岩层水平移动边界模型,隐含于厚松散层覆岩内部;“类双叶双曲面”模型为空间地表沉降与覆岩裂隙拱、冒落拱垂向移动边界模型,均在主关键层近似关于“原点”对称,具体表现为采掘扰动下地表沉陷及采场围岩拱形垮落等外部形态。通过理论分析、相似模型试验及3DEC数值模拟,本文建立并验证了厚松散层近水平煤层开采条件下空间采动岩层立体移动与地表沉陷“类双曲面”模型。同时,分析了共渐近锥面“类双曲面”模型的构成条件、影响因素及整体运移规律。研究结果表明:在薄基岩厚松散层近水平煤层开采条件下,“类双曲面”理论模型与3DEC模拟结果吻合较好,表明采动空间覆岩运移和地表沉降呈“类双曲面”特征。

Invariance of Painlev property for some reduced (1+1)-dimensional equations

We study the Painlevé property of the （1＋1）-dimensional equations arising from the symmetry reduction for the （2＋1）- dimensional ones. Firstly, we derive the similarity reduction of the （2＋1）-dimensional potential Calogero-Bogoyavlenskii- Schiff （CBS） equation and Konopelchenko-Dubrovsky （KD） equations with the optimal system of the admitted one-dimensional subalgebras. Secondly, by analyzing the reduced CBS, KD, and Burgers equations with Painlevé test, re-spectively, we find both the Painlevé integrability, and the number and location of resonance points are invariant, if the similarity variables include all of the independent variables.