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A parameter determination method of unscented transformation and its approximate ability analysis in the precision estimation of nonlinear measurement adjustment

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MEASUREMENT 2020年 166卷

作者： Wang, Leyang Ding, Rui East China Univ Technol Fac Geomat Nanchang 330013 Jiangxi Peoples R China Shandong Jianzhu Univ Sch Surveying & Geoinformat Jinan 250101 Peoples R China

Unscented transformation (UT) is the key technology of unscented Kalman filter, which can approximate probability distribution to estimate second-order approximate mean and covariance matrix of nonlinear function. In parameter selection of various sampling strategies in the framework of the unscented transformation (UT), there are few studies on the determination method of sampling parameters. In this study, the particle swarm optimization (PSO) algorithm is introduced into UT for high convergence efficiency and few control parameters. The parameter selection of several commonly used sampling strategies is analyzed from the numerical point of view, and a method to determine the sampling parameters is proposed. Furthermore, the higher-order information ignored by the recommended parameters of UT is considered, and the approximation ability of UT is tapped and improved by the obtained parameters. For the first time, the minimal skew simplex sampling (MSS) and the scaled minimal skew simplex sampling (SMSS) are applied to the precision estimation of nonlinear measurement adjustment. Considering the influence of non-normal distribution data on nonlinear error propagation in geodetic measurement, this study analyzes the PSO-UT model in a case study from the geodetic field. Experiments show that PSO can effectively determine the parameters of UT and improve its approximation ability, which enriches UT theory. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Nonlinear measurement adjustment Precision estimation Unscented transformation particle swarm optimization algorithm Parameter selection Non-normal distribution

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The calculation of the reliability index in nonlinear problems: A new method

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AIN SHAMS ENGINEERING JOURNAL 2020年第3期11卷 705-716页

作者： Alamdarloo, Pezhman Derakhshan Moghaddam, Mehdi Azhdary Univ Sistan & Baluchestan Civil Engn Dept Zahedan Iran

The accurate estimation of the health (reliability) index is important to estimate probability of failure in the reliability assessment of structures. The conventional first-order reliability methods including the Hasofer-Lind, Rackwitz-Fiessler, and Monte Carlo could lead to unstable, fluctuating, and distorted solutions to nonlinear problems, featuring complicated structural performance functions. The present study aimed to propose a new method by combining the particle swarm optimization and differential evolution algorithms in order to calculate the reliability index. The performance of the proposed method was evaluated by 10 examples from different studies, and the convergence results were compared to the results of studies such as Hasofer-Lind, Rackwitz-Fiessler, Monte Carlo and some other methods. To verify the accuracy of the proposed method, to verify the accuracy of the proposed method, a reliability index chart was applied. The comparisons indicated the high accuracy and speed of the proposed method. Accordingly, in higher order nonlinear problems, the proposed method successfully calculated the reliability index while some failed to solve these problems. (C) 2019 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University.

关键词： Reliability index Combination of algorithms particle swarm optimization algorithm Differential evolution algorithm

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A generalized pseudo-rigid-body PPRR model for both straight and circular beams in compliant mechanisms

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MECHANISM AND MACHINE THEORY 2020年 154卷

作者： Xu, Hao Gan, Jinqiang Zhang, Xianmin China Univ Geosci Sch Mech Engn & Elect Informat Wuhan 430074 Peoples R China South China Univ Technol Guangdong Prov Key Lab Precis Equipment & Mfg Tec Guangzhou 510640 Peoples R China

The pseudo-rigid-body (PRB) models have been widely applied for modeling of straight beams in compliant mechanisms. In this paper, a generalized PRB PPRR model with two mutually perpendicular linear springs is established for both straight and circular beams in compliant mechanisms. In the developed model, the static equations of the deflected beams are derived from Bernoulli's equation. The characteristic parameters of the developed model are identified by the reasonably organized particle swarm optimization (PSO) algorithm. A simulation experiment of tip locus of a circular beam is conducted to evaluate the developed model. The simulation results show the developed model has higher accuracy than the PRB 2R, 3R, and RRHR model. In addition, two numerical examples are further implemented to demonstrate the effectiveness of the developed model. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Compliant mechanism Pseudo-rigid-body model Circular beam particle swarm optimization algorithm

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Environment-dependent edge reconstruction of transition metal dichalcogenides: a global search

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MATERIALS TODAY ADVANCES 2020年 8卷

作者： Li, D. Ding, F. Jilin Univ Coll Phys State Key Lab Superhard Mat Changchun 130012 Peoples R China Inst Basic Sci Ctr Multidimens Carbon Mat Ulsan 44919 South Korea Ulsan Natl Inst Sci & Technol UNIST Dept Mat Sci & Engn Ulsan 44919 South Korea

The properties of an edge of a transition metal dichalcogenide (TMDC) sensitively depend on its atomic structure;therefore, knowing the exact structure is a precondition for predicting the applications of TMDC, such as in catalysis. Although some edge reconstructions of TMDCs have been reported in previous studies, a global search of TMDC edge structures and calculations of their stabilities are still absent. Here, we propose an approach to explore all possible edge reconstructions of a monolayer TMDC by employing the particle swarm optimization algorithm and first-principles calculations. Taking the most studied TMDC material, MoS2, as a representative, we have built a database of the edge structures of TMDCs. Including the five experimentally observed edges, the thirty-four most stable edges with various sulfur concentrations are predicted for the first time. The most stable edge structures of 1H-MoS2 in different environments along both the armchair and zigzag directions have been predicted and agree well with experimental observations. A specific edge of 1H-MoS2 in the database can be stabilized by modulating the chemical composition of the atoms, which offers an efficient way to tune the properties of TMDC nanostructures, such as TMDC quantum dots and/or nanoribbons. (C) 2020 The Author(s). Published by Elsevier Ltd.

关键词： Transition metal dichalcogenide Molybdenum disulfide Edge reconstruction particle swarm optimization algorithm First-principles calculation

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Evolutionary algorithms For k-Anonymity In Social Networks Based On Clustering Approach

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COMPUTER JOURNAL 2020年第7期63卷 1039-1062页

作者： Yazdanjue, Navid Fathian, Mohammad Amiri, Babak Iran Univ Sci & Technol Sch Ind Engn Tehran *** Iran

The usage of social networks shows a growing trend in recent years. Due to a large number of online social networking users, there is a lot of data within these networks. Recently, advances in technology have made it possible to extract useful information about individuals and the interactions among them. In parallel, several methods and techniques were proposed to preserve the users' privacy through the anonymization of social network graphs. In this regard, the utilization of the k-anonymity method, where k is the required threshold of structural anonymity, is among the most useful techniques. In this technique, the nodes are clustered together to form the super-nodes of size at least k. Our main idea in this paper is, initially, to optimize the clustering process in the k-anonymity method by means of the particle swarm optimization (PSO) algorithm in order to minimize the normalized structural information loss (NSIL), which is equal to maximizing 1-NSIL. Although the proposed PSO-based method shows a higher convergence rate than the previously introduced genetic algorithm (GA) method, it did not provide a lower NSIL value. Therefore, in order to achieve the NSIL value provided by GA optimization while preserving the high convergence rate obtained from the PSO algorithm, we present hybrid solutions based on the GA and PSO algorithms. Eventually, in order to achieve indistinguishable nodes, the edge generalization process is employed based on their relationships. The simulation results demonstrate the efficiency of the proposed model to balance the maximized 1-NSIL and the algorithm's convergence rate.

关键词： social network k-anonymity particle swarm optimization algorithm genetic algorithm structural information loss

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Application of improved genetic algorithm in ultrasonic location of transformer partial discharge

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NEURAL COMPUTING & APPLICATIONS 2020年第6期32卷 1755-1764页

作者： Zhu, Youchan Zhou, Li Xu, Haisheng N China Elect Power Univ Sch Control Comp Engn Baoding Peoples R China

Detecting and locating the partial discharge point inside the transformer is one of the key measures to ensure the normal operation of transformer. In this paper, an improved genetic algorithm (GAICM) based on improved cross-model was proposed. In this algorithm, crossover operator and mutation operator are improved, and an adaptive model is introduced. GAICM was tested by classical test functions. The test results showed that GAICM has good convergence speed and optimization ability. Meanwhile, GAICM was applied to the ultrasonic localization of transformer partial discharge, and its positioning effect was compared with the location effect of genetic algorithm, simulated annealing algorithm and particle swarm optimization algorithm. The experimental result showed that the application of GAICM to the ultrasonic localization of the transformer partial discharge is more effective.

关键词： Improved genetic algorithm particle swarm optimization algorithm Simulated annealing algorithm Transformer partial discharge

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A New Cycle Slip Detection and Repair Method Using a Single Receiver's Single Station B1 and L1 Frequencies in Ground-Based Positioning Systems

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SENSORS 2020年第2期20卷 346-346页

作者： Zhao, Xinyang Niu, Zun Li, Gaoxu Shuai, Qiangqiang Zhu, Bocheng Peking Univ Dept Elect Beijing 100871 Peoples R China

The detection and repair of the cycle slip is a key step for high precision navigation and positioning in indoor environments. Different methods have been developed to detect and repair cycle slips for carrier phase processing. However, most approaches are designed to eliminate the effects of the ionosphere in an outdoor environment, and many of them use pseudorange (code) information that is no longer suitable for indoor multipath environments. In this paper, a method based on the geometry-free combination without the pseudorange data is proposed to detect and fix cycle slips. A ground-based navigation system is built for data collection. Unlike the traditional dual-frequency cycle slip detection method, the Beidou B1, GPS L1 carrier phase combination is used instead of the B1, B2, or L1, L2 carrier phase combination, Ublox is used for data collecting. For fixing the cycle slips quickly, an improved adaptive particle swarm optimization (PSO) algorithm is employed. We compared the performance of the new method with the existing two methods using simulated data in different conditions. The results show that the proposed method has better performance than other methods.

关键词： cycle slip detection ground-based navigation multipath effect particle swarm optimization algorithm

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An Optimized Mass-spring Model with Shape Restoration Ability Based on Volume Conservation

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2020年第4期14卷 1738-1756页

作者： Zhang, Xiaorui Wu, Hailun Sun, Wei Yuan, Chengsheng Nanjing Univ Informat Sci & Technol Sch Comp & Software Engn Res Ctr Digital Forens Jiangsu Engn Ctr Network MonitoringMinist Educ Nanjing 210044 Peoples R China Nanjing Univ Informat Sci & Technol Jiangsu Collaborat Innovat Ctr Atmospher Environm Nanjing 210044 Peoples R China

To improve the accuracy and realism of the virtual surgical simulation system, this paper proposes an optimized mass-spring model with shape restoration ability based on volume conservation to simulate soft tissue deformation. The proposed method constructs a soft tissue surface model that adopts a new flexion spring for resisting bending and incorporates it into the mass-spring model (MSM) to restore the original shape. Then, we employ the particle swarm optimization algorithm to achieve the optimal solution of the model parameters. Besides, the volume conservation constraint is applied to the position-based dynamics (PBD) approach to maintain the volume of the deformable object for constructing the soft tissue volumetric model base on tetrahedrons. Finally, we built a simulation system on the PHANTOM OMNI force tactile interaction device to realize the deformation simulation of the virtual liver. Experimental results show that the proposed model has a good shape restoration ability and incompressibility, which can enhance the deformation accuracy and interactive realism.

关键词： Virtual surgery soft tissue deformation mass-spring model position-based dynamics particle swarm optimization algorithm

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Analysis of Charging Load Acceptance Capacity of Electric Vehicles in the Residential Distribution Network

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WORLD ELECTRIC VEHICLE JOURNAL 2022年第11期13卷

作者： Hua, Yuan-Peng Wang, Shi-Qian Han, Ding Bai, Hong-Kun Wang, Yuan-Yuan Li, Qiu-Yan State Grid Henan Elect Power Co Econ & Technol Res Inst Zhengzhou 450015 Peoples R China

After large-scale electric vehicles (EVs) are connected to the residential distribution network, community charging has become one of the main bottlenecks at present, especially in old residential areas. Therefore, the current residential distribution network's ability to accept charging load and when and how the distribution network needs to be transformed have become meaningful research points. Based on the characteristics of the EVs' charging load of residential areas on a typical day and the size of the target annual charging load, this paper analyzes the acceptance capacity of the charging load of the distribution network on typical weekdays and weekends. By taking the charging load characteristics, the charging time of EVs, the voltage of each node of the distribution network, the line capacity, the transformation capacity of the distribution station as constraints, and the maximum capacity of the residential distribution network to accept the charging load as the objective function, the charging load capacity of the residential distribution network is analyzed. The particle swarm optimization algorithm is employed to solve the optimized mathematical model. The simulation uses an actual residential distribution network as an analysis example, and the partition optimization results prove the correctness and feasibility of this proposed method.

关键词： residential distribution network electric vehicle acceptance capacity charging load particle swarm optimization algorithm

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Iterative convergence control method for planar underactuated manipulator based on support vector regression model

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NONLINEAR DYNAMICS 2020年第4期102卷 2711-2724页

作者： Wang, Ya-Wu Yang, Hui-Qing Zhang, Pan China Univ Geosci Sch Automat Wuhan 430074 Hubei Peoples R China Hubei Key Lab Adv Control & Intelligent Automat C Wuhan 430074 Hubei Peoples R China

An iterative convergence control method (ICCM) based on the support vector regression (SVR) is proposed to realize the position-posture control of the planar four-link underactuated manipulator with a passive second link. Firstly, the particle swarm optimization (PSO) algorithm is used to obtain the target angles of all links according to the position-posture control objective. Then, two prediction models for the coupling relationship between the first link and the passive link, and the third link and the passive link are established based on the SVR, whose optimal parameters are selected by the chaos particle swarm optimization (CPSO) algorithm. By repeatedly controlling the first link or the third link to rotate an angle which is calculated by the trained SVR model, the passive link gradually converges to its target angle after several iterations. Next, the active links are controlled to rotate to their target angles with low speeds, and the passive link does not rotate due to friction. Finally, the experimental results verify the effectiveness and feasibility of the proposed method.

关键词： Underactuated manipulator Position– posture control Support vector regression particle swarm optimization algorithm Coupling relationship

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