检索结果-内蒙古大学图书馆

IEEE/CIC International Conference on Communications in China (ICCC)

作者： Wang, Jin Zeng, Zexi Jiang, Jing Wan, Pengwu Sutthiphan, Worakrin Xian Univ Posts & Telecommun Sch Commun & Informat Engn Xian Peoples R China Xian Univ Posts & Telecommun Sch Artificial Intelligence Xian Peoples R China Natl Telecommun Publ Co Bangkok Thailand

ISBN: (纸本)9798350377675;9798350377682

In Wi-Fi fingerprinting location, constructing traditional fingerprint databases consumes a large amount of human resources. Interpolation algorithms are typically used to reduce the workload of database construction, and the kriging algorithm is a widely used interpolation algorithm. However, existing algorithms do not consider the nonlinear variation in received signal strength indication (RSSI) in free space. In this paper, an improved kriging algorithm based on spatial variability is proposed by analysing the propagation law of electromagnetic waves in free space, separating the regions with drastic and slow changes in RSSI, and then fitting a semivariance function to the two regions for interpolation. Through real simulation tests, the proposed algorithm has demonstrated improvements in interpolation accuracy, achieving gains of approximately 4.6% and 8.1% over traditional kriging and the Inverse Distance Weighting (IDW) algorithm, respectively. The interpolation accuracy of the proposed algorithm is superior to both kriging and IDW algorithms, effectively enhancing localization precision, making it more suitable for constructing an RSSI fingerprint database.

关键词： Wi-Fi fingerprinting kriging algorithm indoor positioning

来源：评论

学校读者我要写书评

暂无评论

The surrogate model for short-term extreme response prediction based on ANN and kriging algorithm

引用

APPLIED OCEAN RESEARCH 2024年 152卷

作者： Zhao, Guanhua Zhao, Yuliang Dong, Sheng Ocean Univ China Coll Engn Qingdao 266404 Peoples R China

Numerical simulation is a common method for calculating the short-term extreme response of floating offshore wind turbines (FOWTs). However, it requires significant computational resources. This study presents a dynamic response database for a 5MW semi-submersible FOWT under complex environmental conditions, including wind speed, effective wave height, and wave spectral peak period, using a numerical model. The peak over threshold (POT) method can be used to obtain the parametric database of short-term extreme responses, which includes the short-term extreme response distribution parameters for four responses: float surge, mooring tension, outward bending moment at the leaf root surface (OoPBM) and tower base pitching moment (TBPM). And the parameter database is applied to train models such as the Genetic algorithm optimization Back Propagation neural network (GA-BP) and kriging algorithm models. The research indicates that a correlation can be established between environmental conditions and short-term extreme response parameters using two algorithms. The accuracy of surrogate model prediction for some parameters can be improved by grouping the data based on wind speed and training separately. Additionally, selecting the appropriate surrogate model for each parameter separately can improve the accuracy of short-term extreme response prediction.

关键词： Floating offshore wind turbines Short-term extreme response Surrogate model Neural network kriging algorithm

来源：评论

学校读者我要写书评

暂无评论

Efficient GPU-based Parallel kriging algorithm for Predicting the Air Quality Index

Efficient GPU-based Parallel Kriging Algorithm for Predictin...

引用

International Conference on Green Informatics (ICGI)

作者： Lin, Zhihong Wang, Jianqin Zhang, Ye Cai, Saihua Hao, Shangbo China Agr Univ Coll Informat & Elect Engn Beijing 100083 Peoples R China

ISBN: (纸本)9781538622803

Air quality index (AQI) is an evaluation standard of air quality and a major concern in the daily lives of people. However, predicting the AQI is difficult;existing prediction methods are few and they cannot satisfy the requirements of real-time prediction. This paper proposes an efficient GPU-based parallel kriging algorithm (GP-kriging) for real-time AQI prediction. Parallel computing strategy is used in the sub-steps of the serial kriging algorithm, and some steps are designed and implemented in GPU to accelerate the computing speed. The data sets of the experiments are collected from Beijing Environmental Monitoring Center. Experimental results show that the time requirement of the GP-kriging algorithm is approximately 20 times faster than that of serial kriging. The successful application of the GP-kriging algorithm in this study suggests that the method can be used to predict AQI.

关键词： kriging algorithm parallel computing graphics processing unit prediction method

来源：评论

学校读者我要写书评

暂无评论

Parallelization of the kriging algorithm in Stochastic Simulation with GPU Accelerators 3rd

Parallelization of the Kriging Algorithm in Stochastic Simul...

引用

3rd Annual International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem (GRMSE)

作者： Liu, Lin Wu, Chonglong Wang, Zhibo China Univ Geosci Inst Informat Technol 388 Lumo Rd Wuhan 430074 Peoples R China E China Inst Technol Software Inst Nanchang 430074 Peoples R China Wuhan Univ Int Sch Software Wuhan 430079 Peoples R China

ISBN: (纸本)9783662491553;9783662491546

3D realtime modeling places a heavy load on CPU. This paper presents a new method on 3D visualization in reservoir modeling system by using the computation power of modern programmable graphics hardware (GPU). The proposed scheme is devised to achieve parallel processing of massive reservoir logging data. By taking advantage of the GPU's parallel processing capability, moreover, the performance of our scheme is discussed in comparison with that of the implementation entirely running on CPU. Experimental results clearly show that the proposed parallel processing can remarkably accelerate the data clustering task. Especially, although data-transferring from GPU to CPU is generally costly, acceleration by GPU is significant to save the total execution time of data-clustering, and significantly alleviates the computing load on CPU.

关键词： kriging algorithm Massive data Stochastic simulation Graphics processing unit (GPU)

来源：评论

学校读者我要写书评

暂无评论

3D morphing method based on kriging algorithm for surgical navigation 34

3D morphing method based on Kriging algorithm for surgical n...

引用

34th Chinese Control Conference (CCC)

作者： Hu, Yan Wei, Jun Wang, Tianmiao Zhao, Qinjun Zhao, Honghua Li, Shi Univ Jinan Sch Automat & Elect Engn Jinan 250022 Shandong Peoples R China Beijing Univ Aeronaut & Astronaut Coll Mech Engn & Automat Beijing 100191 Peoples R China Univ Jinan Sch Mech Engn Jinan 250022 Shandong Peoples R China

ISBN: (纸本)9789881563897

A set of preoperative CT reconstructed model can not be used in operating on individual patient in 3D surgical navigation systems. According to the problem above, a 3D bone morphing method based on kriging algorithm was presented. Two point sets, one of which was acquired from physical space by the optical localizer and the other was from 3D model reconstructed by the marching cube method, were used to calculate the transformation matrix between the preoperative CT image space and the intraoperative marker space. Then 4 appropriate reference points were chosen to solve the equations based on kriging algorithm, and the positions of points on CT model after deformation respect to the physical case were acquired. At last, precision analysis of morphing and evaluation experiment of knee joint navigation was carried out with CT and plastic model. The result shows that under this condition the final morphing accuracy is less than 1 mm, and this technology can be used in operation evaluation of the anterior cruciate ligament navigation reconstruction.

关键词： knee joint surgical navigation kriging algorithm registration morphologic bone

来源：评论

学校读者我要写书评

暂无评论

3D morphing method based on kriging algorithm for surgical navigation

3D morphing method based on Kriging algorithm for surgical n...

引用

第三十四届中国控制会议

作者： Yan Hu Jun Wei Tianmiao Wang Qinjun Zhao Honghua Zhao Shi Li School of automation and electrical engineering University of Jinan Colleage of Mechanical Engineering and Automation Beijing University of Aeronautics and Astronautics School of mechanics engineering University of Jinan

ISBN: (纸本)9781467374439

关键词： knee joint surgical navigation kriging algorithm registration morphologic bone

来源：评论

学校读者我要写书评

暂无评论

A Dual Robust Strategy for Removing Outliers in Multi-Beam Sounding to Improve Seabed Terrain Quality Estimation

引用

SENSORS 2024年第5期24卷 1476页

作者： Zhou, Ping Chen, Jifa Wang, Shengping Jiangxi Acad Water Sci & Engn Res Ctr Hydraul Safety Engn Technol Nanchang 330029 Peoples R China Nanchang Inst Technol Sch Hydraul & Ecol Engn Nanchang 330099 Peoples R China Jiangxi Normal Univ Minist Educ Key Lab Poyang Lake Wetland & Watershed Res Nanchang 330022 Peoples R China Second Inst Oceanog Key Lab Submarine Geosci Hangzhou 310012 Peoples R China

During the process of seabed terrain exploration using a multi-beam echo system, it is inevitable to obtain a sounding set containing anomalous points. Conventional methods for eliminating outliers are unable to reduce the disruption caused by outliers over the whole dataset. Furthermore, incomplete consideration is given to the terrain complexity, error magnitude, and outlier distribution. In order to achieve both a high-precision terrain quality estimate and quick detection of depth anomalies, this study suggests a dual robust technique. Firstly, a robust polyhedral function is utilized to solve anomaly detection for large errors. Secondly, the robust kriging algorithm is used for refined outlier removal. Ultimately, the process of dual detection and anomaly removal is achieved. The experimental results demonstrate that DRS technology has the most favorable mean square error and error fluctuation range in the test set, with values of 0.8321 and [-2.0582, 1.9209], respectively, when compared to RPF, WT, GF, and WLS-SVM schemes. Furthermore, DRS is able to adjust to various terrain complexities, discrete distribution features, and cluster outlier detection, as shown by objective indicators and visual outcome maps, guaranteeing a high-quality seabed terrain estimate.

关键词： multibeam sounding seabed terrain robust estimation polyhedral function kriging algorithm

来源：评论

学校读者我要写书评

暂无评论

Neural network-based indoor localization system with enhanced virtual access points

引用

JOURNAL OF SUPERCOMPUTING 2021年第1期77卷 638-651页

作者： Labinghisa, Boney A. Lee, Dong Myung Tongmyong Univ Busan South Korea

Wi-Fi indoor positioning systems are based on received signal strength indicator (RSSI) measurements and fingerprinting, by matching measured data with the database. Hence, generation of RSSI fingerprint database is essential for a Wi-Fi-based indoor positioning system;this requires significant time and effort. The study utilizes virtual access points to increase the number of access points in an indoor environment without necessitating additional hardware. Increases in the total access points is advantageous because it makes the database more granular, and the kriging algorithm is introduced to solve the issue with less effort. The study also aims to apply deep learning neural network (DNN) in Wi-Fi fingerprinting using RSSI. The proposed system utilizes the neural network (NN) and kriging algorithm to perform standard Wi-Fi fingerprinting, without difficulties in generating a fingerprint map. The result of a simple location estimation test led to an accuracy of 97.14%, thereby indicating that the application of NN and kriging improves indoor localization. Further experiments should be conducted to test the complete effectiveness of the proposed system as compared to other systems employing DNN.

关键词： Indoor localization Neural network Virtual access points WiFi kriging algorithm RSSI

来源：评论

学校读者我要写书评

暂无评论

Data-driven prediction of critical collapse pressure of flexible pipeline carcass layer

引用

OCEAN ENGINEERING 2022年 249卷 110948-110948页

作者： Yan, Jun Li, Wenbo Du, Hongze Zhang, Hengrui Huo, Sixu Lu, Qingzhen Dalian Univ Technol Int Res Ctr Computat Mech Dept Engn Mech State Key Lab Struct Anal Ind Equipment Dalian 116024 Peoples R China Dalian Univ Technol Ningbo Res Inst Ningbo 315016 Zhejiang Peoples R China Dalian Univ Technol Sch Ocean Sci & Technol State Key Lab Struct Anal Ind Equipment Panjin 124221 Peoples R China

Carcass layers in flexible pipelines are mainly used to resist the radial external pressure. The large hydrostatic pressure in deep-water environments often leads to collapse failure of the carcass layer, thus causing the destruction of the entire flexible pipeline. Therefore, the critical collapse pressure of the carcass layer under external pressure must be evaluated in engineering design. At present, the established equivalent theoretical model or numerical simulation method used to study the critical collapse pressure of the carcass layer has certain limitations, such as low accuracy or excessive calculation time. To overcome these problems, a kriging-modified buckling model is proposed with radius R and thickness t as design variables, based on data-driven technology, to predict the critical collapse pressure of the carcass layer accurately. First, sample points are selected in the design domain based on the optimal Latin hypercube sampling, and the weight between the sample points and predicted points is calculated using the kriging algorithm. Then, the above-mentioned weights are used to modify the buckling theory to predict the critical collapse pressure of the carcass layer. The numerical results indicate that the modified model has a higher prediction accuracy than that of the traditional buckling theory. Additionally, the effects of the number and pattern of sample points on the modified model are discussed. This paper presents an efficient design method and implementation technology for the design of deep-water flexible pipeline carcass.

关键词： Flexible pipeline Carcass layer Data driven Critical collapse pressure kriging algorithm

来源：评论

学校读者我要写书评

暂无评论

Model updating for slope stability assessment in spatially varying soil parameters using multi-type observations

引用

MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2022年第0期171卷 108906-108906页

作者： Ouyang, Jiayi Liu, Yong [a]State Key Laboratory of Water Resources and Hydropower Engineering Science Institute of Engineering Risk and Disaster Prevention Wuhan University 299 Bayi Road Wuhan 430072 China [b]Key Laboratory of Rock Mechanics in Hydraulic Structural Engineering of the Ministry of Education Wuhan University Wuhan 430072 China

With site-specific information, model updating can calibrate the probability distributions of material parameters, and the updated distributions can be further utilized to facilitate a more realistic slope reliability assessment. Many model updating methods have been proposed, while the inherent spatial variability of material properties is scarcely discussed in the literature, mainly due to the curse of dimensionality when considering thousands of random variables. The BUS (Bayesian updating with structural reliability methods) algorithm can well tackle the highdimensional problem by converting it into an equivalent structural reliability problem. The BUS algorithm can integrate monitoring data and field observations to back analyse stability parameters. However, when generating a conditional random field using a large number of in-situ test data, the BUS algorithm becomes less efficient because low acceptance probability often occurs, while the kriging algorithm is applicable for this situation. This study proposes an effective approach for model updating that combines kriging-based conditional random field with the BUS algorithm to integrate multi-type observations. To illustrate the effectiveness of the proposed approach, an undrained saturated clay slope with a spatially varying soil parameter is taken as an example. The results indicate that the proposed approach is able to update the probability distribution of spatially varying soil parameters and update the slope reliability using multi-type observations with reasonable calculation efficiency.

关键词： Model updating Spatial variability Bayesian updating kriging algorithm Slope reliability

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：