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INFOCOMMUNICATIONS JOURNAL 2022年第1期14卷 2-10页

作者： Pan, Qinghe Qiu, Zeguo Xu, Yaoqun Yao, Guilin Harbin Univ Commerce Sch Comp & Informat Engn Harbin Peoples R China

In this paper a system is designed and implemented to predict the price of second-hand housing. This system based on Lambda architecture can execute prediction in both real-time and batch modes so it can give two kinds of different price predictions that reflect current and historical conditions respectively. The kNN related algorithms are used for price prediction. By comparing the performance of brute kNN, kd tree and ball tree, kd tree is selected as the price prediction model of the system. In system implementation the kd tree model is chosen to predict prices in both real-time and batch services. The kd tree model can also recommend housings to user besides price prediction. The experiment shows the effectiveness of our system. Time and space performance of brute kNN, kd tree and ball tree are compared by experiments. And the evaluation metrics of other available maching learning models are compared. The reason of choosing the kd tree model is also explained by the experimental results.

关键词： Lambda Architecture real-time system batch system kd tree

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Cloud service selection based on weighted kd tree nearest neighbor search

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APPLIED SOFT COMPUTING 2022年 131卷

作者： Bi, Wenhao Ma, Junwen Zhu, Xudong Wang, Weixiang Zhang, An Northwestern Polytech Univ Sch Aeronaut Xian 710072 Shaanxi Peoples R China

The military organization cloud cooperation is a new type of military organization that encapsulates combat resources into services and makes them available as a service. Because of the heterogeneity of the combat resources, the cloud services are different not only in functional properties, but also in non-functional properties. Hence, the idea of cloud service selection, which aims at providing service requester with cloud services that meet their needs for non-functional attributes, has emerged. To this end, this paper proposes a cloud service selection method based on the weighted kd tree nearest neighbor search (WkdTNNS) algorithm for the personalized search of cloud services with different weights in each dimension. Firstly, for the atomic cloud service selection, the kd tree of all atomic cloud services with the quality of service (QoS) as the key is constructed, and WkdTNNS is used to match cloud services for service requests from users. Then, for combined cloud service selection, the kd tree is constructed based on pre-established combined cloud services to select several similar services as seeds, and the WkdTNNS algorithm is applied to optimize the seeds and obtain the final results. Finally, a case study is presented to show the feasibility and effectiveness of the proposed method, the results show that the proposed method could achieve better results than other algorithms, with 26%-56% less computation time.

关键词： kd tree Nearest neighbor search Cloud service Service selection

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An adaptive image feature matching method using mixed Vocabulary-kd tree

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MULTIMEDIA TOOLS AND APPLICATIONS 2020年第23-24期79卷 16421-16439页

作者： Zhang, Fengquan Gao, Yahui Xu, Liuqing North China Univ Technol Sch Comp Sci Beijing 100144 Peoples R China Chinese Acad Sci Airborne Remote Sensing Ctr Inst Remote Sensing & Digital Earth Beijing 100094 Peoples R China

This paper proposes an adaptive scale-invariant feature matching method based on data clustering, to solve the problem of low robustness of the kd tree matching method caused by SIFT feature noise sensitivity, and our method can be used to AR applications. The method has two stages: offline data re-clustering and online two-stage feature matching. This paper is the first to present a Vocabulary-kd data structure which achieves SIFT using kd tree by tuning the number of features of the Vocabulary nodes. Moreover, based on the Vocabulary-kd data structure, an adaptive feature matching method is proposed, which is consist of two clustering, one on the feature sets and the other on the feature sets contained by the leaf nodes of the Vocabulary-kd tree, along with adaptive adjustment of the relevant parameters of the Vocabulary-kd tree. At last, key images are selected in real-time for the second stage feature matching. The different results show that the proposed method can effectively resist noise, improve the adaptivity of the SIFT feature matching method, so as to achieve the trade-off between efficiency and robustness.

关键词： SIFT Clustering Vocabulary tree kd tree Voronoi graph AR

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An Improved Method to Build the kd tree Based on Presorted Results 11

An Improved Method to Build the KD Tree Based on Presorted R...

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11th IEEE International Conference on Software Engineering and Service Science (IEEE ICSESS)

作者： Cao, Yu Zhang, Xiaojiang Duan, Boheng Zhao, Wenjing Wang, Huizan Natl Univ Def Technol Coll Meteorol & Oceanog Changsha Hunan Peoples R China

ISBN: (数字)9781728165790

ISBN: (纸本)9781728165790

kd (K-dimension) tree is widely used in solving multidimensional space search problems, such as the nearest neighbor search, ray tracing, etc. During the process of kd tree construction, the median point in a specified dimension is generally chosen as the split point so as to build a balanced tree. As the performance of building a kd tree is strongly influenced by the efficiency of the selection of the median point, a variety of methods have been developed to select the median point quickly and accurately. However, the performance of methods introduced in most previous literature is either uncertain or time consuming. This paper proposes an improved method to build the kd tree based on presorted results. Compared with previous similar work, the new algorithm not only reduces unnecessary comparisons during presorting and construction, but also could handle problems with duplicate data, which expands the application of such methods.

关键词： kd tree median point balanced tree presorting

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Capacity value of wind power using kd tree and nearest neighbor search algorithm

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 2019年第1期32卷

作者： Nayak, Ashwini K. Mohanty, Kanungo B. Natl Inst Technol Elect Engn Dept Rourkela India

Electrical power demand is increasing cumulatively with the increase in population. Economic and environmental impacts restrict the expansion of conventional generation but prompting for intermittent wind sources due to its economic and environmental benefits. But the average capacity value of the wind power is not the same as that of the same rated conventional generation due to its intermittent nature and wind speed dependence. Several definitions of capacity value of wind power are proposed on the basis of reliability evaluation of the system. The estimation of capacity value is not easy as at hourly step wind speed is changing so the power. Therefore, a new procedure is developed here to accumulate all the information like the sequential value of wind power, their reliability indices, and the corresponding capacity values using the capacity value definitions in a single database. To search the capacity value of the wind power, the database is represented in a multidimensional k-dimensional tree and nearest neighbor search algorithm is implemented. A case study is considered to validate the proposed methodology.

关键词： annual risk capacity credit kd tree nearest neighbor search reliability wind power

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A Fast Calculation Method for Multiple Scattering of Rays Based on kd-tree

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电脑学刊 2020年第6期31卷 305-318页

作者： Pei-Lei Zhang Fu-Bing Li Wen-Jian Chen

In this paper, a single-ended open rectangular parallelepiped cavity model is used as an example to calculate the multiple scattering propagation path of incident rays in the target. In order to improve the efficiency of ray tracing, a multi-layer kd tree structure of the target is constructed and the ray-triangle intersection is determined based on kd tree structure. To construct a kd tree, several steps are performed. First, the degree of triangle centroid dispersion of the target is separately calculated for three coordinate axes. The axis with the maximum dispersion is selected as splitting axis. Second, the 3D bounding box that containing the whole target (i.e., the root node) is divided into two sub-bounding boxes (i.e., the child nodes) along the splitting axis, each containing about half of target triangles. The above procedure is then repeated for each new-generated bounding box until the number of triangles in these boxes (i.e., the leaf nodes) satisfies the preset condition, and a kd tree is finally constructed. To calculate the ray-triangle intersection, the kd tree is firstly searched from the root node layer by layer to find the leaf node that intersects with the incident ray, and the ray-triangle intersection coordinate as well as the reflected ray can be calculated in the leaf box. Multiple scattering of the ray can be determined similarly by the steps above. Result indicates that under the parameter settings in this article, multiple scattering calculation based on kd tree can achieves a speedup of about 10 compared with the traditional method that calculates the ray-triangle intersection one surface by one surface. It also indicates that as the height of the kd tree increases, computation time gradually decreases and finally tends to stabilize.

关键词： kd tree multiple scattering ray-triangle intersection algorithm shooting-bouncing rays

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Analysis and Evaluation of Desert Sand Performance After Improvement of Plant-Based Bio-Cement (PBBC)

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INDIAN GEOTECHNICAL JOURNAL 2025年 1-14页

作者： Fu, Xiao Ye, Wan-jun Yuan, Gang Kang, Jiang Niu, Rui-yuan Xian Univ Sci & Technol Sch Architecture & Civil Engn Xian 710054 Shaanxi Peoples R China China Telecom Co Ltd Liupanshui Branch Liupanshui 553000 Guizhou Peoples R China Shaanxi Inst Engn Prospecting Xian 710068 Shaanxi Peoples R China

As a kind of green and energy-efficient building material, bio-cement has received continuous attention in the field of ecological environment and construction in recent years. At the same time, desert sand is a recognized natural waste with no building use value. It is not only in line with the international advocacy of low-carbon environmental protection, but also can turn waste into treasure, if the two can be scientifically combined. In this work, the combination of plant-based bio-cement (PBBC) and fly ash (FA) improves the uniaxial compression strength of desert sand and improves its permeability resistance and water erosion resistance. The effect of fly ash on improving the curing level of PBB was expounded, which is based on the macroscopic mechanical properties and microscopic characteristics of the improved sand. And we used image processing technology to analyze the crack evolution of the sample under uniaxial compression. The results show that the increase of FA content increases the peak compressive strength of PBBC-FA-modified desert sand. UCS treated with PBBC plus 7% FA (770.01 kPa) was about 50 times higher than that treated with PBBC alone (15.27 kPa). The immersion curve of the sample shows that the immersion process of the improved desert sand consists of three stages. It is also found that the lowest water content of the improved desert sand is 5.73%. The permeability of the sample and the amount of calcium carbonate precipitation increased with the increase in the dosage. The cracks of the sample evolved along the uniaxial compressive strength, from microcrack propagation, interpenetration, penetration, lateral expansion damage, and complete failure.

关键词： Plant-based bio-cement (PBBC) Tap water Fly ash Mechanical properties Fracture identification analysis kd tree

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Fast query by humming system based on complex multiscale music entropy and CMMEB kd tree

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INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING 2015年第3-4期6卷 159-169页

作者： Nagavi, Trisiladevi C. Bhajantri, Nagappa U. SJ Coll Engn Dept Comp Sci & Engn Mysore Karnataka India Govt Engn Coll Dept Comp Sci & Engn Chamarajanagar Karnataka India

Query by Humming (QBH) Music Information Retrieval (MIR) system is one of the enlivened areas of research for matching hummed query to music excerpts existing within the music database. This paper proposes a fast QBH content based music retrieval technique based on the estimation of Complex Multiscale Music Entropy (CMME). The proposed concept exploits the statistical reliability through the CMME for approximation of music signals. In order to enhance the speed of the system, the CMME feature vectors of music database are indexed through Complex Multiscale Music Entropy Balanced (CMMEB) kd tree leading to reduced search space and retrieval time. Eventually, CMME feature vectors are extracted from humming query for retrieval of the target song from music database. The experimental results effectually locate the humming queries and state the prominence of CMME and CMMEB kd tree for retrieving the target song by humming.

关键词： CMME complex multiscale music entropy CMMEB complex multiscale music entropy balanced kd tree entropy QBH query by humming

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kdM-OPTICS based vehicle clustering algorithm for traffic millimeter-wave radar

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MEASUREMENT SCIENCE AND TECHNOLOGY 2025年第5期36卷 056306-056306页

作者： Tian, Feng Wang, Siyuan Fu, Weibo Wei, Tianyu Yang, Jiqing Xian Univ Sci & Technol Coll Commun & Informat Technol Xian 710054 Peoples R China Xian Key Lab Network Convergence Commun Xian 710054 Peoples R China

Traffic millimeter-wave radar suffers from environmental noise, dynamic changes in the number of vehicles, and feature similarity leading to degradation of point-trace clustering accuracy when measuring moving vehicle targets. We propose a new density-based clustering algorithm to address this problem. Unlike traditional datasets, the radar measurement dataset used in this algorithm contains specific multidimensional information against a moving vehicle target, such as target distance, normal angle, relative velocity, and reflection intensity. In order to eliminate the correlation interference between the parameters as well as the influence of measurement units, the normalized Mahalanobis distance method is introduced to generate the target spot trace distance matrix. Subsequently, based on the target point trace distance matrix, the reachable distance map is quickly generated by kd tree nearest neighbor search. At the same time, the dynamic adjustment of neighborhood radius of OPTICS is introduced to enhance the contrast of the target point traces in the reachable distance matrix, to obtain the point trace segmentation data of similar vehicles,and to realize the point trace clustering of vehicle targets in the distance and speed dimensions. Finally,the target ranking recognition clustering structure algorithm (kdM-OPTICS) based on kd tree and normalized martens distance is *** this study,experimental validation based on vehicle target data from real urban traffic scenarios is carried *** results show that enhancing the target information by local power-law transformation can improve the stability and reliability of distinguishing vehicles with similar distance speed. In addition,the kdM-OPTICS algorithm has higher recognition accuracy and lower computational speed compared with other algorithms.

关键词： millimeter-wave radar vehicle detection clustering algorithm mahalanobis distance OPTICS power-law transformation kd tree

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kd-tree and quad-tree decompositions for declustering of 2D range queries over uncertain space

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Frontiers of Information Technology & Electronic Engineering 2015年第2期16卷 98-108页

作者： Ahmet SAYAR Suleyman EKEN Okan OZTURK Department of Computer Engineering Kocaeli University Kocaeli 41380 Turkey

We present a study to show the possibility of using two well-known space partitioning and indexing techniques, kd trees and quad trees, in declustering applications to increase input/output （I/O） paraUelization and reduce spatial data processing times. This parallelization enables time-consuming computational geometry algorithms to be applied efficiently to big spatial data rendering and querying. The key challenge is how to balance the spatial processing load across a large number of worker nodes, given significant performance heterogeneity in nodes and processing skews in the workload.

关键词： kd tree Quad tree Space partitioning Spatial indexing Range queries Query optimization

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