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| 1 | Adaptive filtering for deformation parameter estimation in consideration of geometrical measurements and geophysical models显示文摘There are two kinds of methods in researching the crust deformation: geophysical method and geometrical (or observational) method. Considerable differences usually exist between the two kinds of results, because of the datum differences, geophysical model errors, observational model errors, and so on. Thus, it is reasonable to combine the two kinds of information to collect the crust deformation information. To use the reliable geometrical and geophysical information, we have to control the observational and geophysical model error influences on the estimated deformation parameters, and to balance their contributions to the evaluated parameters. A hybrid estimation strategy is proposed here for evaluating the deformation parameters employing an adaptively robust filtering. The effects of measurement outliers on the estimated parameters are controlled by robust equivalent weights. Adaptive factors are introduced to balance the contribution of the geophysical model information and the geometrical measurements to the model parameters. The datum for the local deformation analysis is mainly determined by the highly accurate IGS station velocities. The hybrid estimation strategy is applied in an actual GPS monitoring network. It is shown that the hybrid technique employs locally repeated geometrical displacements to reduce the displacement errors caused by the mis-modeling of geophysical technique, and thus improves the precision of the estimated crust deformation parameters. | YuanXi Yang AnMin Zeng | 2009 | Science China Earth Sciences2009，52，8： | 14 |
| 2 | Model predictive control and improved low-pass filtering strategies based on wind power fluctuation mitigation显示文摘The rapid development of renewable energy sources such as wind power has brought great challenges to the power grid. Wind power penetration can be improved by using hybrid energy storage(ES) to mitigate wind power fluctuation. We studied the strategy of smoothing wind power fluctuation and the strategy of hybrid ES power distribution. Firstly, an effective control strategy can be extracted by comparing constant-time low-pass filtering(CLF), variable-time low-pass filtering(VLF), wavelet packet decomposition(WPD), empirical mode decomposition(EMD) and model predictive control algorithms with fluctuation rate constraints of the identical grid-connected wind power. Moreover, the mean frequency of ES as the cutoff frequency can be acquired by the Hilbert Huang transform(HHT), and the time constant of filtering algorithm can be obtained. Then, an improved low-pass filtering algorithm(ILFA) is proposed to achieve the power allocation between lithium battery(LB) and supercapacitor(SC), which can overcome the over-charge and over-discharge of ES in the traditional low-pass filtering algorithm(TLFA). In addition, the optimized LB and SC power are further obtained based on the SC priority control strategy combined with the fuzzy control(FC) method. Finally, simulation results show that wind power fluctuation can be effectively suppressed by LB and SC based on the proposed control strategies, which is beneficial to the development of wind and storage system. | Yushu SUN Xisheng TANG Xiaozhe SUN Dongqiang JIA Zhihuang CAO Jing PAN Bin XU | 2019 | Journal of Modern Power Systems and Clean Energy2019，7，3： | 13 |
| 3 | New normalized LMS adaptive filter with a variable regularization factor显示文摘A new normalized least mean square(NLMS) adaptive filter is first derived from a cost function, which incorporates the conventional one of the NLMS with a minimum-disturbance(MD)constraint. A variable regularization factor(RF) is then employed to control the contribution made by the MD constraint in the cost function. Analysis results show that the RF can be taken as a combination of the step size and regularization parameter in the conventional NLMS. This implies that these parameters can be jointly controlled by simply tuning the RF as the proposed algorithm does. It also demonstrates that the RF can accelerate the convergence rate of the proposed algorithm and its optimal value can be obtained by minimizing the squared noise-free posteriori error. A method for automatically determining the value of the RF is also presented, which is free of any prior knowledge of the noise. While simulation results verify the analytical ones, it is also illustrated that the performance of the proposed algorithm is superior to the state-of-art ones in both the steady-state misalignment and the convergence rate. A novel algorithm is proposed to solve some problems. Simulation results show the effectiveness of the proposed algorithm. | LI Zhoufan LI Dan XU Xinlong ZHANG Jianqiu | 2019 | Journal of Systems Engineering and Electronics2019，30，2： | 9 |
| 4 | Analysis and application of automatic deformation monitoring data for buildings and structures of mining area显示文摘The buildings and structures of mines were monitored automatically using modern surveying technology. Through the analysis of the monitoring data, the deformation characteristics were found out from three aspects containing points, lines and regions, which play an important role in understanding the stable state of buildings and structures. The stability and deformation of monitoring points were analysed, and time-series data of monitoring points were denoised with wavelet analysis and Kalman filtering, and exponent function and periodic function were used to get the ideal deformation trend model of monitoring points. Through calculating the monitoring data obtained, analyzing the deformation trend, and cognizing the deformation regularity, it can better service mine safety production and decision-making. | XIAO Jie1, 2, 3, ZHANG Jin4 1. Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China 2. Key Laboratory of Dynamic Geodesy, Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430077, China 3. Graduate School of Chinese Academy of Sciences, Beijing 100049, China 4. Department of Surveying and Mapping, Taiyuan University of Technology, Taiyuan 030024, China | 2011 | 中国有色金属学会会刊:英文版2011，21，S3： | 9 |
| 5 | A Novel Deep Hybrid Recommender System Based on Auto-encoder with Neural Collaborative Filtering显示文摘Due to the widespread availability of implicit feedback(e.g., clicks and purchases), some researchers have endeavored to design recommender systems based on implicit feedback. However, unlike explicit feedback,implicit feedback cannot directly reflect user preferences. Therefore, although more challenging, it is also more practical to use implicit feedback for recommender systems. Traditional collaborative filtering methods such as matrix factorization, which regards user preferences as a linear combination of user and item latent vectors, have limited learning capacities and suffer from data sparsity and the cold-start problem. To tackle these problems,some authors have considered the integration of a deep neural network to learn user and item features with traditional collaborative filtering. However, there is as yet no research combining collaborative filtering and contentbased recommendation with deep learning. In this paper, we propose a novel deep hybrid recommender system framework based on auto-encoders(DHA-RS) by integrating user and item side information to construct a hybrid recommender system and enhance performance. DHA-RS combines stacked denoising auto-encoders with neural collaborative filtering, which corresponds to the process of learning user and item features from auxiliary information to predict user preferences. Experiments performed on the real-world dataset reveal that DHA-RS performs better than state-of-the-art methods. | Yu Liu Shuai Wang M.Shahrukh Khan Jieyu He | 2018 | Big Data Mining and Analytics2018，1，3： | 7 |
| 6 | Estimation of non-point source pollution loads with flux method in Danjiangkou Reservoir area,China显示文摘The estimation of non-point source pollution loads into the Danjiangkou Reservoir is highly significant to environmental protection in the watershed. In order to overcome the drawbacks of traditional watershed numerical models, a base flow separation method was established coupled with a digital filtering method and a flux method. The digital filtering method has been used to separate the base flows of the Hanjiang,Tianhe, Duhe, Danjiang, Laoguan, and Qihe rivers. Based on daily discharge, base flow, and pollutant concentration data, the flux method was used to calculate the point source pollution load and non-point source pollution load. The results show that:(1) In the year 2013, the total inflow of the six rivers mentioned above accounted for 95.9% of the total inflow to the Danjiangkou Reservoir. The total pollution loads of chemical oxygen demand(CODMn) and total phosphorus(TP) from the six rivers were 58.20 103 t and 1.863 10~3 t, respectively, and the non-point source pollution loads were 39.82 10~3 t and 1.544 10~3 t, respectively, indicating that the non-point source pollution is a major factor(with a contribution rate of 68.4% for CODMnand 82.9% for TP).(2) The Hanjiang River is the most significant contributor of pollution loads to the Danjiangkou Reservoir, and its CODMnand TP contribution rates reached 79.3% and 83.2%, respectively. The Duhe River took the second place.(3) Non-point source pollution mainly occurred in the wet season in 2013, accounting for 80.8% and 90.9% of the total pollution loads of CODMnand TP, respectively. It is concluded that the emphasis of pollution control should be placed on non-point source pollution. | Xiao-kang Xin Wei Yin Ke-feng Li | 2017 | Water Science and Engineering2017，10，2： | 7 |
| 7 | REAL-TIME FLOOD FORECASTING MODELING OF 1D UNSTEADY CHANNEL FLOW AND KALMAN FILTER显示文摘WT5”BZ]The model of 1D unsteady channel flow combined with the Kalman filter for real-time channel flood forecasting was attempted in this study. The suitable upstream and downstream boundary conditions were suggested. The system equation was given by the linearization of the finite-difference equations of the mass conservation and momentum equations as well as the boundary conditions. In the Kalman filter updating model, because the number of measurement variable is less then that of state-space variables, the measurement error covariance matrix could be estimated in real time through the innovation sequence, and the system error covariance matrix needs to be estimated preliminarily. A real example of flood forecasting in the Huaihe River was given to explain how the method works. The results show that the model is reasonable and effective. [WT5”HZ] | Li, Z.J. Weng, M.H. | 2001 | Journal of Hydrodynamics2001，13，1： | 5 |
| 8 | H-infinity filtering for discrete-time switched linear systems under arbitrary switching显示文摘This paper is concerned with the problem of H-infinity filtering for discrete-time switched linear systems under arbitrary switching laws.New sufficient conditions for the solvability of the problem are given via switched quadratic Lyapunov functions.Based on Finsler's lemma,two sets of slack variables with special structure are introduced to provide extra degrees of freedom in optimizing the guaranteed H-infinity performance.Compared to the existing methods,the proposed one has better performances and less conservatism.An example is given to illustrate its effectiveness. | Ding, Dawei Yang, Guanghong Li, Xiaoli | 2011 | 控制理论与应用(英文版)2011，9，2： | 4 |
| 9 | An improved iterative thresholding algorithm for L_(1)-norm regularization based sparse SAR imaging显示文摘Dear editor,Sparse signal processing techniques have been widely used after being introduced to synthetic aperture radar(SAR)imaging,and have shown desirable potential in imaging performance improvement compared with traditional matched filtering(MF)based methods[1,2]. | Hui BI Yong LI Daiyin ZHU Guoan BI Bingchen ZHANG Wen HONG Yirong WU | 2020 | Science China(Information Sciences)2020，63，11： | 4 |
| 10 | Fast filtering algorithm based on vibration systems and neural information exchange and its application to micro motion robot显示文摘This paper develops a fast filtering algorithm based on vibration systems theory and neural information exchange approach. The characters, including the derivation process and parameter analysis, are discussed and the feasibility and the effectiveness are testified by the filtering performance compared with various filtering methods, such as the fast wavelet transform algorithm, the particle filtering method and our previously developed single degree of freedom vibration system filtering algorithm, according to simulation and practical approaches. Meanwhile, the comparisons indicate that a significant advantage of the proposed fast filtering algorithm is its extremely fast filtering speed with good filtering performance. Further, the developed fast filtering algorithm is applied to the navigation and positioning system of the micro motion robot, which is a high real-time requirement for the signals preprocessing. Then, the preprocessing data is used to estimate the heading angle error and the attitude angle error of the micro motion robot. The estimation experiments illustrate the high practicality of the proposed fast filtering algorithm. | 高娃 查富生 宋宝玉 李满天 | 2014 | Chinese Physics B2014，23，1： | 4 |
| 11 | Signal-to-noise ratio application to seismic marker analysis and fracture detection显示文摘Seismic data with high signal-to-noise ratios (SNRs) are useful in reservoirexploration. To obtain high SNR seismic data, significant effort is required to achieve noiseattenuation in seismic data processing, which is costly in materials, and human and financialresources. We introduce a method for improving the SNR of seismic data. The SNR iscalculated by using the frequency domain method. Furthermore, we optimize and discussthe critical parameters and calculation procedure. We applied the proposed method on realdata and found that the SNR is high in the seismic marker and low in the fracture zone.Consequently, this can be used to extract detailed information about fracture zones that areinferred bv structural analysis but not observed in conventional seismic data. | 许辉群 桂志先 | 2014 | Applied Geophysics2014，11，1： | 4 |
| 12 | Modeling of UAV path planning based on IMM under POMDP framework显示文摘In order to enhance the capability of tracking targets autonomously of unmanned aerial vehicle (UAV), the partially observable Markov decision process (POMDP) model for UAV path planning is established based on the POMDP framework. The elements of the POMDP model are analyzed and described. The state transfer law in the model can be described by the method of interactive multiple model (IMM) due to the diversity of the target motion law, which is used to switch the motion model to accommodate target maneuvers, and hence improving the tracking accuracy. The simulation results show that the model can achieve efficient planning for the UAV route, and effective tracking for the target. Furthermore, the path planned by this model is more reasonable and efficient than that by using the single state transition law. | YANG Qiming ZHANG Jiandong SHI Guoqing | 2019 | Journal of Systems Engineering and Electronics2019，30，3： | 4 |
| 13 | Multi-sensor optimal weighted fusion incremental Kalman smoother显示文摘In practical applications, the system observation error is widespread. If the observation equation of the system has not been verified or corrected under certain environmental conditions,the unknown system errors and filtering errors will come into being.The incremental observation equation is derived, which can eliminate the unknown observation errors effectively. Furthermore, an incremental Kalman smoother is presented. Moreover, a weighted measurement fusion incremental Kalman smoother applying the globally optimal weighted measurement fusion algorithm is given.The simulation results show their effectiveness and feasibility. | SUN Xiaojun YAN Guangming | 2018 | Journal of Systems Engineering and Electronics2018，29，2： | 4 |
| 14 | Collecting aerosol in airflow with a magnetically stabilized fluidized bed显示文摘A magnetically stabilized fluidized bed (MSB) is a highly efficient filter that takes the advantage of both fluidized beds and fixed beds. This paper presents the research to collect aerosol in airflow with a MSB. The filtering model of MSB is established with its parameters including magnetic field intensity, gas superficial velocity, average grain size, and bed height on the collection efficiency of MSB. The model is verified by experiments. | Gui, KT Zhang, H Shi, MH Xu, YQ | 2001 | Journal of Environmental Sciences2001，13，4： | 3 |
| 15 | Trust-Based Personalized Service Recommendation: A Network Perspective显示文摘Recent years have witnessed a growing trend of Web services on the Internet. There is a great need of efective service recommendation mechanisms. Existing methods mainly focus on the properties of individual Web services(e.g., functional and non-functional properties) but largely ignore users' views on services, thus failing to provide personalized service recommendations. In this paper, we study the trust relationships between users and Web services using network modeling and analysis techniques. Based on the findings and the service network model we build, we then propose a collaborative filtering algorithm called Trust-Based Service Recommendation(TSR) to provide personalized service recommendations. This systematic approach for service network modeling and analysis can also be used for other service recommendation studies. | 邓水光 黄龙涛 吴健 吴朝晖 | 2014 | Journal of Computer Science & Technology2014，29，1： | 3 |
| 16 | Spline wavelet overlapped peaks analysis显示文摘The proposed method of spline wavelet overlapped peaks analysis is based on the model of wavelet multifrequency channel decomposition. If the suitable optimal wavelet basis and frequency scale value are selected, the useful information can be extracted from noised overlapped signal. Then, according to the linear relationship between individual components in blurred version, multiple linear regression in low frequency domain is employed to resolve highly overlapped peaks. The results show that even signal-to-noise (S/N) decreases to 0.2, relative errors of peak intensity are less than 12% and the sum of square deviations Q is less than 0. | Xiaoyong Zou Jinyuan Mo | 1999 | Chinese Science Bulletin1999，44，10： | 3 |
| 17 | Experimental study on filtering,transporting, concentrating and focusing of microparticles based on optically induced dielectrophoresis显示文摘The key problem to be solved for the dielectrophoresis (DEP) application is to provide dynamically reconfigurable microelectrodes and low-cost methodology for bioparticle manipulation.The emergence of optically induced DEP (ODEP) based on photoconductive effect provides a potential solution for the above problem.In this paper,an ODEP chip is designed and fabricated,and the corresponding experimental platform was established,whereupon four types of particle manipulation regimes–filtering,transporting,concentrating and focusing based on ODEP are experimentally demonstrated and the operating performances are quantitatively analyzed.The experiment results show that the functions and performances of ODEP manipulation are heavily dependent on the geometrical shape,scales and speed of optical patterns,actuating signal frequency and the electric conductivity of the solution.The manipulation efficiency can increase by more than 50% via increasing the optical line width.Moreover,the efficiency is obviously affected by the inclination angle of the optical oblique lines in the manipulation of particle focusing.Additionally,the maximum velocity of particles increases with the increment of the inside radius and the thickness of the optical trapping ring.Particle manipulation efficiency is always related to signal frequency and solution conductivity,and empirically,satisfactory performance and high efficiency are obtained when the solution electric conductivity ranges from 5×10-4 S/m to 5×10-3 S/m. | ZHU XiaoLu,YIN ZhiFeng,GAO ZhiQiang & NI ZhongHua Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments,Southeast University,Nanjing 211189,China | 2010 | Science China(Technological Sciences)2010，53，9： | 3 |
| 18 | Phase error correction method based on the Gaussian filtering algorithm and intensity variance显示文摘To overcome the invalid phase and phase jump phenomenon generated during the phase unwrapping, a phase error correction method based on the Gaussian filtering algorithm and intensity variance is proposed in this paper. First, a threshold of fringe intensity variance is set to identify and clear the phase in the invalid region. Then, the Gaussian filtering algorithm is employed to correct the phase order at the fringe junction, and then the absolute phase is corrected. Finally, the phase correction experiments of different geometric objects are carried out to verify the feasibility and accuracy of the proposed method. The method proposed in this paper can be extended to the correction of absolute phase error obtained by any coding method. | 谷倩倩 吕珊珊 姜明顺 张雷 张法业 隋青美 贾磊 | 2021 | Optoelectronics Letters2021，17，4： | 3 |
| 19 | Shaking Table Test Study on Dynamic Characteristics of Bridge Foundation Reinforcement on Slopes显示文摘With the fast development of bridge construction in mountainous and seismic areas,it is necessary to conduct related research. Based on the design of a shaking table model test,here are the following test results: the filtering effect exists in soil and is affected by the dynamic constraint conditions,the amplitude is strengthened around the natural frequency and weakened in other frequency bands in the Fourier spectrum. Since the acceleration scaling effect occurred on a sloped surface,the acceleration response decreases from the outside to the inside in soil. The dynamic response is relatively strong near the slip surface in bedrock due to the reflection of seismic waves. The failure mode of landslide is decided by the slope angle and slipping mass distribution, and the test shows the front row stabilizing piles should keep a proper distance from bridge foundation so that seismic resistance can be guaranteed for the bridge foundation. | Lei Da Qi Zhihui Jiang Guanlu Wang Zhimeng Li Anhong | 2017 | Earthquake Research in China2017，31，3： | 3 |
| 20 | Multi-model deep learning approach for collaborative filtering recommendation system显示文摘As a result of a huge volume of implicit feedback such as browsing and clicks,many researchers are involving in designing recommender systems(RSs)based on implicit feedback.Though implicit feedback is too challenging,it is highly applicable to use in building recommendation systems.Conventional collaborative filtering techniques such as matrix decomposition,which consider user preferences as a linear combination of user and item latent features,have limited learning capacities,hence suffer from a cold start and data sparsity problems.To tackle these problems,the research direction towards considering the integration of conventional collaborative filtering with deep neural networks to maps user and item features.Conversely,the scalability and the sparsity of the data affect the performance of the methods and limit the worthiness of the results of the recommendations.Therefore,the authors proposed a multimodel deep learning(MMDL)approach by integrating user and item functions to construct a hybrid RS and significant improvement.The MMDL approach combines deep autoencoder with a one-dimensional convolution neural network model that learns user and item features to predict user preferences.From detail experimentation on two real-world datasets,the proposed work exhibits substantial performance when compared to the existing methods. | Mohammed Fadhel Aljunid Manjaiah Doddaghatta Huchaiah | 2020 | CAAI Transactions on Intelligence Technology2020，5，4： | 3 |
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