Yao Li

Southeast University

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Tao Zhang

Southeast University

Jinwu Tong

Nanjing Institute of Technology

Xiaosu Xu

Southeast University

Yiqing Yao

Southeast University

Liang Zhang

Institute of Geographic Sciences and Natural Resources Research

Xiang Xu

Nanjing University of Science and Technology

Jian Wang

Sun Yat-sen University

Lihua Zhu

Nanjing University of Science and Technology

Weng Chengcheng

Southeast University

Lanhua Hou

Southeast University

Cooperative Institutions

Southeast University

Chinese Academy of Sciences

Ministry of Education of the People's Republic of China

University of Chinese Academy of Sciences

Fudan University

Sun Yat-sen University

Northwest University

University of Science and Technology of China

Beijing National Laboratory for Molecular Sciences

Beijing Institute of Technology

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Application of Machine Learning in Organic Chemistry

Chinese Journal of Organic Chemistry (2020)

Yidi Liu Qi Yang Yao Li Long Zhang Sanzhong Luo

近年来,由于计算能力、大数据和算法的不断进步,人工智能(Artificial intelligence,AI)重新兴起,已成为诸多研究领域变革性发展背后的重要推动力.机器学习(Machine learning,ML)是人工智能一个重要的研究领域.随着化学信息学的发展,机器学习在化学领域展现出巨大的发展潜力,也为有机化学的发展带来了新的机遇.为帮助有机化学家了解这一新兴领域,对如何将机器学习策略应用于有机化学研究做简单介绍,同时,概括总结了机器学习在化合物性质预测、分子从头设计、化学反应预测、逆合成分析和智能合成机器方面的应用实例,分析讨论了当前机器学习在有机化学领域面临的挑战和难题.

10.6023/cjoc202006051

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Citations (18)

An autonomous underwater vehicle positioning matching method based on iterative closest contour point algorithm and affine transformation

Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment (2016)

Tao Zhang Yao Li Jinwu Tong

An improved autonomous underwater vehicle federal integrated navigation method based on two-stage position matching technology is proposed in this study to solve the problem of positioning divergence caused by the defects of error accumulation in an inertial navigation system. The improved two-stage position matching method includes the acquisition and preprocessing of the strap-down inertial navigation system and indicates track sequences and elevation measurement sequences. The first-stage position matching is based on iterative closest contour point, while the second-stage position matching is based on an affine algorithm. Simulation results indicate that the proposed algorithm solves the problem of the limitation of the rigid transformation of traditional iterative closest contour point and effectively resolves the matching failure caused by the large initial position error of long-time navigation.

Iterative closest point

Position (finance)

Dilution of precision

Unmanned underwater vehicle

Navigation System

10.1177/1475090216683310

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Citations (3)

Design of intelligent fault-tolerant to passive underwater integrated navigation system

Journal of Chinese Inertial Technology (2013)

Yao Li

To improve the navigation accuracy of autonomous underwater vehicle,an integrated navigation system was proposed,which was composed of strapdown inertial navigation system(SINS),terrain-aided navigation(TAN) system and gravity-aided navigation(GAN) system.A fault-tolerant federated Kalman filter was used to fuse the various navigation sensors,detect the system fault and reconstruct the navigation system.In view that traditional cai-square hypothesis testing processes fault detection cannot determine the specific cause of the fault,and could only determine the validity of measure information,a new fault detection algorithm based on neural network was adopted.The application on underwater integrated navigation system demonstrates that the algorithm can rapidly and accurately detecting and identify the faults in the system.Therefore the effective fault isolating can be performed to realize the fault tolerance navigation.

Navigation System

Source

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Citations (2)

Learning-based Separation of Macromolecules and Metabolites in Ultrashort-TE FID MRSI with Auxiliary SE MRSI Data

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2024)

Yibo Zhao Yudu Li Jin Wen Rong Guo Yao Li

Motivation: Macromolecules have significant spectral overlap with metabolites, confounding accurate quantification of metabolites in ultrashort-TE MRSI. Goal(s): To develop a novel method for effective and reliable separation of metabolites and macromolecules from ultrashort-TE FID MRSI data. Approach: We translated auxiliary macromolecule-free SE metabolite signals to FID signals using a learning-based approach. The translated metabolite reference was incorporated in the spectral model of FID MRSI data through generalized series modelling. Macromolecules signals were modelled with probabilistic subspaces. Results: The proposed method has been validated using numerical simulation and experimental data from healthy subjects and a tumor patient, producing encouraging results. Impact: This work provides a novel approach to exploiting the characteristic spectral features in FID and SE MRSI experiments for effective separation of metabolites and macromolecules.

10.58530/2024/2984

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A fast mutant fault detection method of underwater integrated navigation

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering (2015)

Yiting Liu Xiaosu Xu Xixiang Liu Jin Sun Tao Zhang

The concepts of the mean of residual and the sum of absolute residuals are introduced in this paper. Both of them along with the fault detection function are used to detect mutant fault of the assisted navigation devices in underwater integrated navigation system. (1) The traditional residual χ 2 detection method is improved according to the structural characteristics of the underwater navigation system. (2) The mean of residual and the sum of absolute residuals are introduced as the characteristics of mutant faults. (3) The improved residual χ 2 detection method is used to make sure of the happening of the mutant fault firstly. Then the residual mean and the sum of residual absolute values are used to distinguish the noise mutant system fault and the information mutant system fault. The results of simulations and the vehicle tests show that: (1) the mutant fault of the sub-system can be detected and the faulty sub-system can be isolated immediately when the fault appears with our novel method; (2) The noise mutant fault and the information mutant fault can be distinguished efficiently according to characteristics of the mean of residuals and the sum of the absolute residuals.

Navigation System

10.1177/0954410015599011

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Citations (3)

Comparison of EKF and UKF target tracking algorithms based on observation distance

Dongheng Li Yao Li Gaofeng Zhu Yun Cheng

Target tracking is one of the important research directions in the field of computer vision, and it is widely used in many fields such as precision guidance, human-computer interaction, and robot navigation. In this paper, a target tracking model is established, and the EKF and UKF target tracking algorithms based on observation distance are deeply studied, and simulation experiments are carried out respectively. The results show that when the nonlinearity of the system is not strong, the accuracy of the two algorithms is similar. In more complex situations, the UKF tracking target accuracy is higher.

Tracking (education)

Tracking system

10.1109/icisce50968.2020.00090

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Citations (2)

A hull deformation measurement method based on fiber optic gyro angular rate matching in complex sea conditions

Proceedings of the Institution of Mechanical Engineers Part M Journal of Engineering for the Maritime Environment (2021)

Yao Li Di Wang Jinwu Tong

In the conventional hull deformation measurement method, the external measurement noise is considered constant. However, due to the complex sea conditions and the high-frequency chatter caused by the waves, the measurement noise is colored noise. The aim of this paper is to develop a hull deformation measurement method based on fiber optic gyro (FOG) angular rate matching in complex sea conditions. On the one hand, the traditional system model is optimized to reduce the dimension, and a simplified linear state space model is proposed. On the other hand, a finite impulse response (FIR) low-pass digital filter is designed and introduced into the angular rate matching measurement method, so that the deformation estimation accuracy can still be maintained in complex sea conditions. The simulation and swing table test are designed to verify the effectiveness of the hull deformation measurement method proposed in this paper. The results show that the proposed method in this paper can effectively eliminate external noise interference and improve estimation accuracy.

10.1177/14750902211033264

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Citations (5)

Robust Attitude and Positioning Alignment Methods for SINS/DVL Integration Based on Sliding Window Improvements

IEEE Transactions on Industrial Electronics (2023)

Xiang Xu Yao Li Lihua Zhu Yiqing Yao

The strapdown inertial navigation system (SINS) and Doppler velocity log (DVL) are the major positioning system for underwater vehicles. The initial alignment process is the first working stage of SINS/DVL integration. Currently, the initial alignment method for SINS/DVL integration is imperfect. The major problems can be summarized in two aspects. One is the initial velocity errors and outliers of DVL outputs, which are not suppressed simultaneously. The other is the positioning uncertainty when the attitude alignment is finished. To address these two problems, robust attitude and positioning alignment methods are proposed in this article. First, a vector observation, which is based on the sliding windows improvements, is constructed for eliminating the initial velocity errors. Second, the apparent velocity motion model for the vector observation with the sliding window improvements is constructed. Based on the constructed model, a parameter estimation method, which is established by a robust Kalman filter, is proposed. Using the estimated parameters, the new observed vectors are reconstructed. Thus, the robust attitude alignment process is finished. Third, real-time and postprocessing positioning alignment methods are proposed for addressing positioning uncertainty. At last, the simulation and field tests are designed for verifying the performance of the proposed method. The test results are shown that the existing two problems are overcome.

Sliding window protocol

10.1109/tie.2023.3294582

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Citations (5)

Application of improved fifth-degree cubature Kalman filter in the nonlinear initial alignment of strapdown inertial navigation system

Review of Scientific Instruments (2019)

Tao Zhang Jian Wang Bonan Jin Yao Li

This paper addresses the state estimation of the nonlinear initial alignment of the strapdown inertial navigation system (SINS), which mainly focuses on the initial alignment on the swaying base and under the in-motion condition with the measurement uncertainties. In order to achieve a higher alignment precision, stronger numerical stability, and lower computational cost for the initial alignment of SINS on the swaying base, a new discrete large azimuth misalignment error model of SINS is established, and an improved fifth-degree cubature Kalman filter (5th-CKF) algorithm is proposed, which combines the 5th-CKF and a simplified dimensionality reduction filtering algorithm. The 5th-CKF is introduced to solve the nonlinear filtering problem, a simplified dimensionality reduction algorithm is derived to reduce the large calculation values of 5th-CKF. Furthermore, under the Bayesian framework, a novel filtering approach named the fifth-degree variational Bayesian (VB) adaptive cubature Kalman filter is deduced for the in-motion alignment with a large azimuth misalignment angle and unknown and time-varying measurement noise statistics, which combines the iterative VB approach and 5th-CKF. The 5th-CKF is exploited to handle the nonlinear initial alignment model, and the VB approach is utilized to iteratively estimate the sufficient statistics of the measurement noise. Mathematical simulation, turntable, and vehicle experiments are performed to demonstrate the effectiveness and the superiority of the proposed approaches.

Nonlinear filter

10.1063/1.5061790

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Citations (15)

AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL

Sensors (2015)

Tao Zhang Liping Chen Yao Li

This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV.

Dead reckoning

Position (finance)

Tracking (education)

10.3390/s16010042

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Citations (41)