Journal of Northeastern University(Natural Science)

Sliding Mode Control of TCP Network Based on Event-Triggered

JING Yuan-wei， BAI Yun

2021, 42 (4): 457-462. DOI: 10.12068/j.issn.1005-3026.2021.04.001

Abstract ( 651 )

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Aiming at the TCP network congestion problem with uncertain parameters and UDP flow interference， an event-triggered TCP network sliding mode control strategy was proposed. The global sliding mode control method was used to make the response process of the entire system robust. On this basis， an event-triggered mechanism was introduced to ensure the stability of the system while saving network resources. The Lyapunov theory proves that all signals in the TCP network closed-loop system are bounded， and the Zeno phenomenon is also effectively avoided. Simulation results show the effectiveness of the proposed control method.

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Admissibility and Robust Stabilization of Discrete Singular Systems Based on LMI

ZHANG Xue-feng， JIN Kai-jing

2021, 42 (4): 463-469. DOI: 10.12068/j.issn.1005-3026.2021.04.002

Abstract ( 543 )

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The admissibility issue of discrete singular systems was mainly studied. Applying restricted equivalent transformations of the discrete singular system， a new necessary and sufficient condition was proposed to ensure discrete singular system admissible. By introducing an intermediate matrix to configure partial poles of system matrix such that the closed-loop system is regular， a state feedback controller was designed to make the closed-loop system admissible. Using similar methods， the controller design problem of uncertain discrete singular systems was discussed as well， a sufficient condition of robust stabilization for uncertain discrete singular systems was obtained. All the methods proposed in this article are strictly linear matrix inequalities(LMI). Two numerical examples verify the effectiveness of the proposed methods.

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Sensitivity Analysis of ZnO Nanometer Gas Sensor Based on Dynamic Temperature Modulation

YUAN Zhen-yu， LEI Yan-feng， DONG Hui， MENG Fan-li

2021, 42 (4): 469-477. DOI: 10.12068/j.issn.1005-3026.2021.04.003

Abstract ( 704 )

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The nano-ZnO gas-sensing material was produced by the hydrothermal method， and the morphology of the finished product under two-solvent washing and water washing was analyzed. The sensitivity， stability and response/recovery time and other characteristic parameters were tested by the traditional static test methods. Aiming at the selectivity and stability of metal oxide gas sensors， a novel dynamic temperature modulation test method was proposed based on the static test. The response of sensors under different waveform(triangular wave， rectangular wave， and trapezoidal wave)was systematically studied， and the influence of symmetry under triangular wave and the influence of interfering gas and amplitude based on trapezoidal wave on sensor response were analyzed.The research results can provide the technical foundation for accurate sensing devices in the front of artificial intelligence industry.

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Control Algorithm of Three-Dimensional Game Based on Reinforcement Learning

MENG Lu， SHEN Ning， QI Yin-qiao， ZHANG Hao-yuan

2021, 42 (4): 478-483. DOI: 10.12068/j.issn.1005-3026.2021.04.004

Abstract ( 593 )

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Based on reinforcement learning， an agent for three-dimensional first person shooting game(DOOM)was designed. The agent can move， shoot enemies and collect objects in the game environment. The proposed algorithm combines the Faster RCNN algorithm of deep learning and the Deep Q-Networks(DQN)algorithm of reinforcement learning， which can greatly reduce the search space of DQN algorithm and improve the training efficiency of the proposed algorithm. The experiments were carried out in two scenes(Defend_the_center and Health_gathering)of the virtual game platform(ViZDoom)， and the proposed algorithm was compared with the state-of-the-art three-dimensional shooting game agent algorithm. The results show that the proposed algorithm can achieve better training results with fewer iterations.

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Medium and Short-Term Electricity Coal Price Forecast Based on Feature Space Transformation and LSTM

LIAO Zhi-wei， CHEN Lin-tao， HUANG Jie-dong， ZHUANG Jing

2021, 42 (4): 483-493. DOI: 10.12068/j.issn.1005-3026.2021.04.005

Abstract ( 518 )

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Aiming at the problem that there are many influencing factors of electricity coal prices and the nonlinearity and multiple time lags are difficult to model， a data-driven medium and short-term electricity coal price forecasting method based on feature transformation and LSTM was proposed. In order to fully excavate the electricity coal price law contained in the massive data， the feature transformation method of different time scale granularity information was proposed. In order to solve the problem of over-fitting caused by multiple variables and small samples， the main influencing factors of medium and short-term coal prices were screened based on chi-square analysis and correlation coefficient. Based on the LSTM neural network， the feature translation correlation analysis method was used to determine the hysteresis of different influencing feature sequences， and the information redundancy in the model was optimized by the main analytic method， and on this basis， a deep learning model based on feature trends was formed. The years of historical data and comparative analysis with various models show the effectiveness and accuracy of this model.

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Error Control of Delay Prediction in Railway Sections Under State Space

ZHANG Lu-kai， FENG Xue-song

2021, 42 (4): 494-501. DOI: 10.12068/j.issn.1005-3026.2021.04.006

Abstract ( 437 )

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Considering the cascading effect of information between sections， an analysis framework of train delay prediction error control in state space was proposed. The fitting regression method was used to process the operating statistics to determine the ordinary differential equations. According to the modern control theory， a linear quadratic regulator was designed to reduce the error， and it provides reasonable support for the proposed method through deduction. The dual-temperature simulated annealing algorithm was designed to obtain the optimized parameters of the regulator， and the simulation calculation was realized in combination with the SIMULINK environment. Numerical experiment results show that compared with the traditional Bayesian network prediction method， the proposed state space analysis method has different degrees of improvement on various error performance indicators， it has obvious advantages in calculation indicators such as average error value， data demand and computing time.

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Underdetermined Blind Source Separation Based on OS-SASP Algorithm

JI Ce， ZHANG Huan， GENG Rong， LI Bo-qun

2021, 42 (4): 501-508. DOI: 10.12068/j.issn.1005-3026.2021.04.007

Abstract ( 515 )

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A sparse adaptive subspace pursuit based on the optimal support(OS-SASP)algorithm was proposed to deal with the problem of underdetermined blind source separation based on sparse component analysis. By introducing the idea of self-adaptation， the dependence of the traditional subspace pursuit(SP)algorithm on sparsity was overcome. At the same time， the size of the minimum support set was determined by the energy concentration characteristic of discrete cosine transform before the start of iteration. Further， the optimal support set was obtained by calculating the union of the minimum support sets. And the combination of the optimal support set and the candidate set in the joint iteration was used to locate the best atom， so as to improve the source signal′s restore accuracy. The simulation results showed that the OS-SASP algorithm can achieve promising performance in the underdetermined blind source recovery of the one-dimensional sparse signals and speech signals.

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Bayesian Network Parameter Learning Method Based on Transfer Learning

WANG Shu， GUAN Zhan-xu， WANG Jing， SUN Xiao-hui

2021, 42 (4): 509-515. DOI: 10.12068/j.issn.1005-3026.2021.04.008

Abstract ( 689 )

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In order to solve the problem that there are many restrictions on the source domain and the target domain in the process of Bayesian network parameter transfer， a unified framework based on Bayesian network parameter transfer learning was proposed under the condition of considering multiple information forms of source domain and target domain. The method considers the role of source domain structure and data volume in the migration. On the basis of structural similarity， the influence of alternative source domain data volume on parameter migration was discussed. The balance coefficient related to the target domain data was introduced in the migration process. According to the balance coefficient， the target domain data was linked with the migration process to realize the automatic adjustment of the balance coefficient. The Asia network verifies the accuracy of the method in this paper.

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Adaptive Range-Gated 3D Imaging Based on Distributed Compressed Sensing

ZHANG Na， WANG Lu， CHENG Jun-na， TIAN Ji-rong

2021, 42 (4): 516-523. DOI: 10.12068/j.issn.1005-3026.2021.04.009

Abstract ( 528 )

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Based on the correlation between time slices of range-gated imaging， a distributed compressed sensing 3D imaging method was proposed， which solved the conflict between a large amount of data and hardware storage performance in 3D imaging. According to the correlation， a distributed compression model based on the joint sparse model was constructed to assist the reconstruction of partial time slices. An adaptive range-gated method was designed， and the gated time was adaptively adjusted according to the set threshold， without distance prior information， which increases system flexibility. The results show that when the average sampling rate is 0.15， the imaging quality of this method is 11.124dB higher than that of the traditional method， and the average error of imaging distance is reduced by 6.240. The distributed imaging method can effectively reduce the collection of time slice redundant information， providing a new idea for range-gated 3D imaging.

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Spatial Information Network Restoration Strategy Based on Improved Genetic Algorithm

LIU Jun， YANG Qing-wen， WANG Jin-tao， LIU Hua-wei

2021, 42 (4): 524-530. DOI: 10.12068/j.issn.1005-3026.2021.04.010

Abstract ( 410 )

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Due to the high dynamics and limited resources of space network， its reliability is faced with severely tested， and a reasonable risk assessment and performance recovery plan was urgently needed. For the elastic recovery strategy of spatial information network， the repair order of damaged components was determined by the recovery strategy based on the improved genetic algorithm， so as to speed up the elastic recovery. The network topology control method was adopted to reduce the importance of damaged key nodes and the loss of network elasticity. The experiment simulates the loss of network resilience with different recovery strategies under different amounts of recovery resources. The results show that the two schemes have better recovery performances when recovery resources are limited and scarce.

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MIT Image Reconstruction Method Based on Simulated Annealing Particle Swarm Algorithm

YANG Dan， LU Tian， GUO Wen-xin， WANG Xu

2021, 42 (4): 531-537. DOI: 10.12068/j.issn.1005-3026.2021.04.011

Abstract ( 485 )

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In order to improve the ill-posed inverse problem and improve the quality of image reconstruction， a MIT image reconstruction method based on simulated annealing and particle swarm optimization was proposed. According to the dimensions of the Hessian matrix， a Tikhonov and NOSER hybrid multi-parameter regularization algorithm was constructed. The simulated annealing algorithm and particle swarm algorithm were combined， the objective function was constructed by the generalized cross criterion， and the regularized multi-parameter optimization was performed.The results show that not only the proposed method effectively overcomes the instability of the numerical solution of the MIT reconstructed image and enhances the anti-noise performance， but also the quality of the obtained reconstructed image is better than that of Tikhonov regularization and hybrid regularization algorithms， which provides a theoretical reference for the application of MIT technology.

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Research on Thermodynamics and Wear Resistance of In-situ NbC Reinforced YCF102 Cladding Layer

XI Wen-chao， SONG Bo-xue， LIANG Ying-dong， YU Tian-biao

2021, 42 (4): 538-543. DOI: 10.12068/j.issn.1005-3026.2021.04.012

Abstract ( 465 )

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The difficulty of cladding layer performance to meet the specific process requirements has become one of the key factors limiting the development of laser cladding. In order to solve this problem， the in-situ NbC reinforced YCF102 cladding layer was prepared on the 45# steel substrate， and the thermodynamic analysis was carried out. The microstructure and composition were analyzed and researched by XRD， SEM and EDS. The microhardness and wear resistance of the cladding layer were researched systematically. The results showed that the change of laser power has a significant effect on the reaction degree of the in-situ reaction in the laser cladding process， and the laser power that is too large or too small will inhibit the in-situ reaction.The main morphology of NbC particles formed in the in-situ YCF102 cladding layer is quadrilateral and petal shaped. When the laser power is 525W， the in-situ NbC reinforced YCF102 cladding layer has higher microhardness and better wear resistance.

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Wheel Gamma Degradation Process Based on Copula Function

LYU Hao， JIN Xiong-cheng， LIN Lu-yang

2021, 42 (4): 544-550. DOI: 10.12068/j.issn.1005-3026.2021.04.013

Abstract ( 448 )

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The wear process of the wheel flange and the rolling circle diameter was described by the Gamma random process， and the method of calculating the reliability of the wheel flange degradation and the rolling circle diameter degradation was studied by using the Copula function and the fourth-order moment method， and the dynamic indexes of the train at different stages were obtained by dynamics software simulation. The reliability of the wheel degradation process with a rotation cycle of 200，000 km and the sensitivity of the wheel diameter degradation process were studied. The correctness of the method was verified by Monte Carlo simulation (MCS).The results showed that the reliability of wheels reaching the expected life is high when the rotation cycle is 200，000 km， and the reliability calculated based on the Copula function correlation failure degradation model is higher than that calculated by the independent failure model. The sensitivity study of the wheel diameter degradation reliability model indicates that the scheme with less reduction of wheel diameter should be selected during the rotation repair.

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Genesis of Dolostone in Du’an Formation of Youjiang Basin and Its Geological Significance

ZHANG Yong-li， MIAO Zhuo-wei， GONG En-pu， ZHANG Qian

2021, 42 (4): 550-560. DOI: 10.12068/j.issn.1005-3026.2021.04.014

Abstract ( 762 )

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Taking the Dujie section as an example， the sedimentary environment analysis and petrological analysis were carried out to further improve the research level on the dolomites of the Lower Carboniferous Du’an Formation in the Youjiang Basin. The dolostone was formed in the Sabkha model of the syngenetic and peneogenetic stages， and was transformed by burial dolomitization in the epigenetic stage. The dolostone stratum of the Du’an Formation， the bonded limestone stratum in the intertidal zone and the grainstone-packstone stratum in the shallow subtidal zone constitute the tidal-flat carbonate rock meter-scale sequence， which provids sedimentological evidence for the development of the Late Paleozoic glaciation in the Serpukhovian.

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Influence of Wave Velocity Range on Accuracy of PSO Location Algorithm

LI Yuan-hui ，CHEN Zhi-yang， XU Shi-da

2021, 42 (4): 561-566. DOI: 10.12068/j.issn.1005-3026.2021.04.015

Abstract ( 407 )

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The accuracy of the known wave-speed acoustic emission positioning algorithm is highly restricted by the accuracy of the initial wave speed test， an acoustic emission location algorithm was developed based on the particle swarm optimization (PSO) algorithm no need to pretesting wave velocity. The fitness function was constructed based on the time difference received by the sensor， and the function was solved by the algorithm to obtain the acoustic emission source position and wave velocity. The influence of the difference of different wave speed assignment ranges and the difference ratio (φ) between the upper and lower bounds of different wave speed assignment ranges and the real wave speed value on the accuracy of the algorithm was studied. Then， a lead-off test was carried out to compare and analyze the location accuracy of the PSO algorithm and the simplex algorithm. The results show that the PSO algorithm location error is less than 10% under different wave velocity ranges and different φ values. When the wave velocity assignment range difference is 2000m/s and φ is 1， the algorithm accuracy is the highest. The positioning accuracy of the algorithm in this paper is significantly better than the traditional simplex positioning algorithm.

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Research on Applicability of the Mohr-Wedge Criterion Including Rock Critical State

ZHANG Jing， REN Feng-yu， HE Rong-xing， OUYANG Zhi-hua

2021, 42 (4): 567-575. DOI: 10.12068/j.issn.1005-3026.2021.04.016

Abstract ( 458 )

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The Mohr-Wedge (MW) strength criterion is a theoretical formula， which is derived based on the rock wedge failure mechanics model and the partial differential equation related to the principal stresses. The MW criterion can be easily understood by using the dimensional analysis to arrange the multiple parameters with corresponding physical meanings. To analyze the applicability of the MW criterion including the rock critical state， the Mohr-Coulomb criterion， the Hoek-Brown criterion and the exponential criterion were selected as the comparison objects， and the average absolute error MAE was used as the evaluation index in order to quantitatively compare the accuracy of the four criteria in predicting rock strength. The results show that when the confining pressure is less than the rock critical state confining pressure σ_○cr-M， the MW criterion has certain applicability. When the confining pressure is greater than σ_○cr-M， the rock strength predicted by the four criteria is different due to the different rock critical state confining pressure. Therefore， a method to predict rock strength under different rock critical state confining pressures was proposed， which can provide some reference for choosing the value of rock critical state confining pressure.

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Safety Integrity Evaluation of High Temperature Molten Metal Operation

WU Ya-ju ， XU Kai-li， WANG Ruo-jun ， XU Xiao-hu

2021, 42 (4): 576-581. DOI: 10.12068/j.issn.1005-3026.2021.04.017

Abstract ( 514 )

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In order to ensure the safety of high temperature molten metal operation in metallurgy industry， the concept of safety integrity of safety-related systems in IEC 61508 was extended to high temperature molten metal operation system， and a safety integrity evaluation method for high temperature molten metal operation based on Bayesian networks Noisy-or model was proposed. A safety integrity evaluation model for high temperature molten metal operations was established， which includes human factors， material factors， environmental factors and management factors. The prior probability of each root node of the Bayesian network was determined by the fuzzy number of fuzzy theory. In order to reduce the amount of calculation and uncertainty， the Noisy-or model was used to determine the conditional probability， and the synergistic effect of each intermediate node on the safety and integrity of the operation was considered. The results show that the evaluation model causal reasoning can determine the safety integrity level of high temperature molten metal operations， and diagnostic reasoning can also determine its sensitive factors， providing guidance for the formulation of safety measures.

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Research on Risk Contagion of China′s Real Estate Industry and Banking Industry Based on Copula Function

YUAN Ying， LIU Rui， XU Bo

2021, 42 (4): 582-588. DOI: 10.12068/j.issn.1005-3026.2021.04.018

Abstract ( 515 )

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Aiming at the non-linear， dynamic time-varying complex relationship between the real estate industry and the banking industry， taking the daily data from 2005-01-04 to 2018-12-28 as the research sample， the dynamic time-varying Copula function was used to test the nonlinear interdependence and the risk contagion between China′s real estate industry and the banking industry， and three contagion channels were explored based on financial association theory and behavioral finance theory. The results showed that there is a non-linear and asymmetric dependent structure between China′s real estate industry and banking industry. Compared with the non-crisis period， the two industries′ tail dependence is significantly increased during the financial crisis， so there is a risk of contagion. The results of the contagion channel research showed that liquidity and investor sentiment are the channels of risk contagion between China′s real estate industry and banking industry while information association is not the channel of risk contagion between them.

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Impact of OFDI Reverse Technology Spillover on China’s Export Competitiveness:An Empirical Analysis from Perspective of Technological Gap

NING Ye， CUI Xin-xin， WANG Jin-ting

2021, 42 (4): 589-597. DOI: 10.12068/j.issn.1005-3026.2021.04.019

Abstract ( 599 )

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OFDI reverse technology spillover is an important way to transform the comparative advantage of China’s export products from labor cost advantage to technological advantage， increase the added value of products and enhance China’s export competitiveness.Using the panel data from China’s provinces， municipalities， and autonomous regions from 2003 to 2017， a threshold-free regression model of OFDI reverse technology spillovers and export competitiveness and a technology gap threshold regression model were established to investigate the relationship between OFDI reverse technology spillover and China’s export competitiveness.The results show that OFDI reverse technology spillover has a positive effect on export competitiveness， technological gap has an impact on the relationship between the two， the above relationship has significant regional differences.

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Spatial-Temporal Evolution of Human-Land Relationship in Liaoning’s City Groups Based on Fractal Theory

WANG Yu-feng， CAO Hong-jun

2021, 42 (4): 598-603. DOI: 10.12068/j.issn.1005-3026.2021.04.020

Abstract ( 523 )

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In response to the problems in the development of Liaoning urban agglomeration， the allometric growth model and urban economic development model were constructed from urban population， land urbanization， gross national product， social fixed investment， etc.， and a long-term study on the human-land relationship of Liaoning urban agglomeration was carried out by using DMSP， VIIRS night light data and urban economic data. The human-land urbanization and economic development level of prefecture-level cities were measured， and the targeted evaluations were made. The results showed that the human-land relationship of Liaoning urban agglomeration is mainly affected by the development of heavy industry economy and resource-based cities. Among them， the development of Shenyang City tends to be flat， while the development of such cities as Huludao and Dandong tends to be three-dimensional. For cities with better economic development， the extensive expansion of urban construction land should be prevented， and for cities with lagging economic development， the employment opportunities should be created to attract population gathering. The research results have certain reference value for the future urbanization development of Liaoning urban agglomeration.

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Cloning and Expression Analysis of SOC1 Homologue Gene in Argyranthemum Frutescens

MA Yue-ping， HU Jing

2021, 42 (4): 604-608. DOI: 10.12068/j.issn.1005-3026.2021.04.021

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SOC1 is one of crucial genes in integrating several pathway signals to initiate the transition of flowering. The SOC1 homologue gene AfSOC1 was identified and cloned from Argyranthemum frutescens using RT-PCR and its expression patterns were characterized using qRT-PCR. The results show that AfSOC1 gene consists of a 648-bp open reading frame and encodes a putative protein of 216 amino acids， which is 63.1% identical to SOC1 in Arabidopsis and 62.1% to DEFH68 in Antirrhinum. The putative protein sequences have a typical MADS-box， K-box domain and typical SOC1 motif DVETELFIGP. AfSOC1 was expressed at highly levels in leaves and flower bud. Its expression signals were also detected in shoot， stems， and flowers. Phylogenetic analysis showed that AfSOC1 was most closely related to dicotyledon SOC1-like than to monocotyledon. These results laid a foundation for us to understand the mechanism of AfSOC1 in regulation flowering.

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