HB-Continuous Mappings in L-Topological Space

In this paper, we introduce and study the notion of HB-closed sets in L-topological space. Then, HB-convergence theory for L-molecular nets and L-ideals is established in terms of HB-closedness. Finally, we give a new definition of fuzzy H-continuous [1] which is called HB-continuity on the basis of the notion of H-bounded L-subsets in L-topological space. Then we give characterizations and properties by making use of HB-converges theory of L-molecular nets and L-ideals.

The closed finite-to-one mappings and their applications

In this paper,we discuss the closed finite-to-one mapping theorems on generalized metric spaces and their applications.It is proved that point-G_δ properties,■-snf-countability and csf-countability are invariants and inverse invariants under closed finite-to-one mappings.By the relationships between the weak first-countabilities,we obtain the closed finite-to-one mapping theorems of weak quasi-first-countability,quasi-first-countability,snf-countability,gfcountability and sof-countability.Furthermore,these results are applied to the study of symmetric products of topological spaces.

TRANSFER OPEN OR CLOSED SETVALUED MAPPING AND GENERALIZ－ATION OF H－KKM THEOREM WITH APPLICATIONS

In this paper ,we introduce a class of generalized mapping called transfer open orclosed valued mapping to generalize the KKM theorem on H-space.Then asapplications,using our H-KKM theorem,we prove some coincidence theorems.matching theorems and vector valued minimax inequalities which generalize slightly thecorresponding results in[1,2,4,5,6,7].

基于神经网络的VSLAM综述

传统的基于视觉的SLAM技术成果颇丰,但在具有挑战性的环境中难以取得想要的效果.深度学习推动了计算机视觉领域的快速发展,并在图像处理中展现出愈加突出的优势.将深度学习与基于视觉的SLAM结合是一个热门话题,诸多研究人员的努力使二者的广泛结合成为可能.本文从深度学习经典的神经网络入手,介绍了深度学习与传统基于视觉的SLAM算法的结合,概述了卷积神经网络(CNN)与循环神经网络(RNN)在深度估计、位姿估计、闭环检测等方面的成就,分析了神经网络在语义信息提取方面的优点,以期为未来自主移动机器人真正自主化提供帮助.最后,对未来VSLAM发展进行了展望.

拓扑保持映射下的拓扑性质

讨论在拓扑保持映射定义下的拓扑性质,得到了在T0分离公理的假设下拓扑保持映射是同胚映射.此外,还讨论拓扑保持映射下几类基数不变量,并得到拓扑保持映射保持连通性、紧性、仿紧性、可数紧性等.

贴近摄影测量技术在建筑立面图测绘中的应用

建筑物立面图测绘对旧城改造、工程造价计算以及工程验收等都具有重要意义,传统立面图测绘主要以全站仪、经纬仪和三维激光扫描仪为主,长期面临着外业采集效率低和成本高等问题。基于无人机贴近摄影测量技术可以高效、精准地获取建筑物立面的图像数据,并应用图像处理技术建立测区实景三维模型,再在三维模型基础上进行立面图绘制。研究结果表明,该技术能为建筑设计、施工和管理等立面图测绘提供可靠的数据支持。

闭环供应链领域回收问题研究的热点与演进分析

出于保护环境、节约资源的要求,闭环供应链领域的回收问题在国际上引起了越来越多学者的关注。文章从Web of Science数据库中筛选出21世纪以来发表的相关文献,利用CiteSpace 5.8.R3可视化软件进行演进分析、聚类分析、突现词分析等,发现了闭环供应链领域回收问题研究的热点和演进趋势。结果表明,学者对于回收视角下闭环供应链领域的研究产出整体呈上升趋势,“企业社会责任”、“减排”、“政府补贴”、“渠道选择”、“网络设计”等为该领域的热点议题,值得更多学者的探索。

绿色闭环供应链网络解的存在性研究

利用变分不等式相关知识对绿色闭环供应链网络均衡条件进行研究,构建各个决策者的可行策略的集值映射,将绿色闭环供应链网络均衡问题转化为广义Nash均衡问题,结合集值映射的连续性、凸性与紧性,利用不动点定理研究绿色闭环供应链网络解的存在性与均衡条件。基于研究结论,提出绿色闭环供应链网络各层决策者对应的变分不等式以及多准则网络均衡条件和绿色闭环供应链网络解的存在性定理。

无人机近距离摄影的建筑三维测绘模型构建

三维测绘建模技术在各个行业及领域中都有广泛应用,如林业保护、城市服务、文物保护、工程测量等。本文探讨了无人机近距离摄影测绘技术,并以释迦塔三维建模为例介绍了近摄测绘的基本原理、测绘方式、常用坐标系,分析了三维测绘建模的关键步骤,包括建模基础、航线设计和摄影流程。运用无人机技术收集释迦塔的影像材料,建立精确的三维模型。该模型经过人工测量验证,误差微小,证实了该技术在建筑三维模型构建中的可行性和有效性。

GENERALIZATIONS AND CARTESIAN CLOSED SUBCATEGORIES OF SEMICONTINUOUS LATTICES

In this article, the authors mainly study how to obtain new semicontinuous lattices from the given semicontinuous lattices and discuss the conditions under which the image of a semicontinuous projection operator is also semicontinuous. Moreover, the authors investigate the relation between semicontinuous lattices and completely distributive lattices. Finally, it is proved that the strongly semicontinuous lattice category is a Cartesian closed category.

CONVERGENCE OF IMPLICIT ITERATIVE PROCESS WITH ERRORS FOR A FINITE FAMILY OF ASYMPTOTICALLY NONEXPANSIVE MAPPINGS

The purpose of this article is to study the weak and strong convergence of implicit iteration process with errors to a common fixed point for a finite family of asymptotically nonexpansive mappings and nonexpansive mappings in Banach spaces. The results presented in this article extend and improve the corresponding results of [1, 2, 4-9, 11-15].

On Some Properties of Neutrosophic Semi Continuous and Almost Continuous Mapping

The neutrality’s origin,character,and extent are studied in the Neutrosophic set.The neutrosophic set is an essential issue to research since it opens the door to a wide range of scientific and technological applications.The neutrosophic set can find its spot to research because the universe is filled with indeterminacy.Neutrosophic set is currently being developed to express uncertain,imprecise,partial,and inconsistent data.Truth membership function,indeterminacymembership function,and falsitymembership function are used to express a neutrosophic set in order to address uncertainty.The neutrosophic set producesmore rational conclusions in a variety of practical problems.The neutrosophic set displays inconsistencies in data and can solve real-world problems.We are directed to do our work in semi-continuous and almost continuous mapping on the basis of the neutrosophic set by observing these.Since we are going to study the properties of semi continuous and almost continuous mapping,we present the meaning of N-semi-open set,N-semi-closed set,N-regularly open set,N-regularly closed set,N-continuous mapping,N-open mapping,N-closed mapping,Nsemi-continuous mapping,N-semi-open mapping,N-semi-closed mapping.Additionally,we attempt to demonstrate a portion of their properties and furthermore referred to some examples.

A screw dislocation near one open inhomogeneity and another closed inhomogeneity both permitting constant interior stresses

We prove that the interior stresses within both a non-parabolic open inhomogeneity and another interacting non-elliptical closed inhomogeneity can still remain constant when the matrix is simultaneously under the action of a screw dislocation and uniform remote anti-plane stresses.The constancy of interior stresses is realized through the construction of a conformal mapping function for the doubly connected domain occupied by the surrounding matrix.The mapping function is endowed with the information describing the screw dislocation via the incorporation of two specifically defined logarithmic terms.The constant interior stress fields are observed to be independent of the specific open and closed shapes of the two inhomogeneities and the existence of the screw dislocation.In contrast,the existence of the neighboring screw dislocation significantly affects the open and closed shapes of the two inhomogeneities.

ON PROBLEM OF NEAREST COMMON FIXED POINT OF NONEXPANSIVE MAPPINGS

The purpose is by using the viscosity approximation method to study the convergence problem of the iterative scheme for an infinite family of nonexpansive mappings and a given contractive mapping in a reflexive Banach space. Under suitable conditions, it was proved that the iterative sequence converges strongly to a common fixed point which was also the unique solution of some variational inequality in a reflexive Banach space. The results presented extend and improve some recent results.

Intuitionistic Fuzzy α-Generalized Closed Sets in Terms of Minimal Structure Spaces

In this paper, we introduce the notion of intuitionistic fuzzy α-generalized closed sets in intuitionistic fuzzy minimal structure spaces and investigate some of their properties. Further, we introduce and study the concept of intuitionistic fuzzy α-generalized minimal continuous functions.

二维不连续映射中心分叉的动力学分析

研究了二维分段不连续线性映射中心分叉的一些性质.类比光滑映射Neimark-Sacker分叉分析了中心分叉.首先,当定义分段线性映射的两个线性矩阵中有一个的特征值为共轭复根并且通过单位圆时,会发生中心分叉;其次,当定义分段线性映射的两个线性矩阵的特征值均为共轭复根并且通过单位圆时,会发生中心分叉.证明了发生中心分叉时在相空间中存在两个与不动点有关的不变区域,并且给出了寻找不变区域并确定其位置和大小的计算方法.讨论了相空间中在不变区域外的动力学行为,最后说明了系统在中心分叉后在不动点附近可能存在不变闭曲线.

一种基于快速鲁棒特征匹配算法的类脑SLAM导航

类脑导航是模拟鼠类感知环境机制提出的一种同步定位与构图(Simultaneous localization and mapping,SLAM)的导航算法。针对复杂环境如室内光线变化导致类脑SLAM导航产生误差的问题,本文提出了基于特征匹配(Speeded up robust features,SURF)算法的优化类脑SLAM导航模型。该模型通过一套移动视觉系统采集环境信息,构建的局部场景细胞通过SURF特征匹配算法获取到载体在环境中的方向与位置信息;头朝向细胞与位置细胞通过连续吸引子神经网络共同表示载体当前的位姿。利用所获取的位姿与时间信息,通过路径积分计算当前载体在坐标系中所处的位置;最后,构建基于认知点的拓扑经验地图。此外,在局部场景细胞获取环境信息的同时,通过SURF特征匹配算法来进行闭环检测,判断是否需要对当前位置进行修正。本文提出的优化类脑SLAM模型很大程度改进了原有模型在有光线变化的室内情况下易产生场景误匹配的问题,并通过实验验证了本文提出方法的有效性。

基于对比阈值的大数据流特征量最优挖掘算法

针对因大数据流基数大、特征难提取导致的闭合模式下数据挖掘效率低、质量差的问题,提出一种基于知识图谱的大数据流闭合模式挖掘算法。结合闭合模式下大数据流的实体-关系-实体关系,通过迁移学习算法构建特征提取器,采集在该模式下不同特征数的输出标签,计算不同标签数据经过一次输出的特征损失量,以此作为损失函数的初始输入值,即为挖掘算法的初始参照。将大数据流在闭合模式下的标准元素作为挖掘目标,按照数据特征量大小建立状态序列,查找挖掘目标与序列中元素的相关性大小和对比阈值,结合目标点的映射关系得到最佳挖掘量,完成有效挖掘。实验结果表明,所提方法的挖掘精准度较高,耗用时间少,具备一定的实用价值。

基于激光雷达的室外实时闭环检测算法

论文探讨适用于激光雷达同时定位与地图构建系统的室外点云实时闭环检测算法,其任务是如何在大规模室外环境下快速准确完成位置识别,以便构建更加鲁棒的SLAM算法。论文提出了一种基于位置和改进的点云全局描述符相融合的闭环检测算法,并设计了新型的适用于该算法的点云帧间相似度匹配计算公式,最后使用一致性校验来尽可能避免误匹配。实验结果表明,论文算法相比于改进前的闭环检测算法无论是在时间还是准确率上都更具竞争力。

桥梁快速建模及病害识别技术应用研究

利用无人机近景摄影测量技术采集桥梁表观多维度影像数据,再进行多点配准及自动纹理映射解析计算得到精确的纹理三维模型;同时建立深度学习神经网络模型对各种构件和病害图像进行特征提取和训练,开发出桥梁构件划分与自动识别软件;最后在可视化桥梁三维模型的基础上,应用桥梁表观病害识别系统自动识别出构件中的病害信息,识别准确率可以达到75%以上,识别精度可以达到厘米级,从而实现了定量、快速、智能化的检测,大幅提高了桥梁检测评估效率。