Path planning for recovery is studied on the engineering background of double unmanned surface vehicles(USVs)towing oil booms for oil spill recovery.Given the influence of obstacles on the sea,the improved artificial ...Path planning for recovery is studied on the engineering background of double unmanned surface vehicles(USVs)towing oil booms for oil spill recovery.Given the influence of obstacles on the sea,the improved artificial potential field(APF)method is used for path planning.For addressing the two problems of unreachable target and local minimum in the APF,three improved algorithms are proposed by combining the motion performance constraints of the double USV system.These algorithms are then combined as the final APF-123 algorithm for oil spill recovery.Multiple sets of simulation tests are designed according to the flaws of the APF and the process of oil spill recovery.Results show that the proposed algorithms can ensure the system’s safety in tracking oil spills in a complex environment,and the speed is increased by more than 40%compared with the APF method.展开更多
Because ice-high foundation soil is widely distributed in permafrost regions,the correct preparation of ice-high specimens is of critical interest in engineering design for foundation stability.Past research has shown...Because ice-high foundation soil is widely distributed in permafrost regions,the correct preparation of ice-high specimens is of critical interest in engineering design for foundation stability.Past research has shown that the uniaxial compression strength of ice-high frozen soils changes as the ice or total water content increases; the differences of different methods of specimen preparation are analyzed here and the advantages and disadvantages of them are presented.It is confirmed that the role of crushed ice is significantly different from that of naturally frozen ice in frozen soils,and the size and amount of crushed ice will influence the strength and deformation mechanism of frozen soils.Therefore,it is strongly recommended that when a ice-high specimen is artificially prepared,the ice should be frozen through natural means and not be replaced with crushed ice.展开更多
A new analytical method using Back-Propagation (BP) artificial neural network and kinetic spectrophotometry for simultaneous determination of iron and magnesium in tap water, the Yellow River water and seawater is est...A new analytical method using Back-Propagation (BP) artificial neural network and kinetic spectrophotometry for simultaneous determination of iron and magnesium in tap water, the Yellow River water and seawater is established. By conditional experiments, the optimum analytical conditions and parameters are obtained. Levenberg-Marquart (L-M) algorithm is used for calculation in BP neural network. The topological structure of three-layer BP ANN network architecture is chosen as 15-16-2 (nodes). The initial value of gradient coefficient μ is fixed at 0.001 and the increase factor and reduction factor of μ take the default values of the system. The data are processed by computers with our own programs written in MATLAB 7.0. The relative standard deviation of the calculated results for iron and manganese is 2.30% and 2.67% respectively. The results of standard addition method show that for the tap water, the recoveries of iron and manganese are in the ranges of 98.0%-104.3% and 96.5%-104.5%, and the RSD is in the range of 0.23%-0.98%; for the Yellow River water (Lijin district of Shandong Province), the recoveries of iron and manganese are in the ranges of 96.0%-101.0% and 98.7%-104.2%, and the RSD is in the range of 0.13%-2.52%; for the seawater in Qingdao offshore, the recoveries of iron and manganese are in the ranges of 95.3%-104.8% and 95.3%-104.7%, and the RSD is in the range of 0.14%-2.66%. It is found that 21 common cations and anions do not interfere with the determination of iron and manganese under the optimum experimental conditions. This method exhibits good reproducibility and high accuracy in the determination of iron and manganese and can be used for the simultaneous determination of iron and manganese in tap water and natural water. By using the established ANN- catalytic spectrophotometric method, the iron and manganese concentrations of the surface seawater at 11 sites in Qingdao offshore are determined and the level distribution maps of iron and manganese are drawn.展开更多
The method of artificial potential field has obvious advantages among the robot path planning methods including simple structure,small amount of calculation and relatively mature in theory.This paper puts forward the&...The method of artificial potential field has obvious advantages among the robot path planning methods including simple structure,small amount of calculation and relatively mature in theory.This paper puts forward the"Integral method"focusing on solving the problem of local minimization.The method analyses the distribution of obstructions in a given environment and regards adjacent obstacles as a whole,By changing the parameters of the repulsive force field,robots can quickly get out of the minimum point and move to the target point.This paper uses the Simurosot platform to carry on the simulation experiment on the improved artificial potential field method,which projects a feasible path successfully and verifies this method.展开更多
Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distribu...Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.展开更多
This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube s...This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model;the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties;and finally,an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables.The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability.As a result,the obtained approximate function can be used as an alternative to the specific analysis process in c-φslope reliability analyses.展开更多
The artificial compression method (ACM) that is generally used to capture the contact discontinuity in nonviscous flows is used here in the simulation of quasi-geostrophic ideal frontogenesis in two dimensions. A comp...The artificial compression method (ACM) that is generally used to capture the contact discontinuity in nonviscous flows is used here in the simulation of quasi-geostrophic ideal frontogenesis in two dimensions. A comparison is made among the result of the ACM, the simulation result of Cullen, and the exact solution of the semi-geostrophic equations. The simulated front in this paper is more prominent than Cullen′s and is much closer to the exact solution.展开更多
Tsunami ran-up height is a significant parameter for dimensions of coastal structures. In the present study, tsunami run-up heights are estimated by three different Artificial Neural Network （ANN） models, i.e. Feed ...Tsunami ran-up height is a significant parameter for dimensions of coastal structures. In the present study, tsunami run-up heights are estimated by three different Artificial Neural Network （ANN） models, i.e. Feed Forward Back Propagation （FFBP）, Radial Basis Functions （RBF） and Generalized Regression Neural Network （GRNN）. As the input for the ANN configuration, the wave height （H） values are employed. It is shown that the tsunami ran-up height values are closely approximated with all of the applied ANN methods. The ANN estimations are slightly superior to those of the empirical equation. It can be seen that the ANN applications are especially significant in the absence of adequate number of laboratory experiments. The results also prove that the available experiment data set can be extended with ANN simulations. This may be helpful to decrease the burden of the experimental studies and to supply results for comparisons.展开更多
Heavy metal pollution of soil has become one of the most common hazards in human development.The artificial freezing method,especially the progressive freezing method,can reduce heavy metal pollutants in the soil and ...Heavy metal pollution of soil has become one of the most common hazards in human development.The artificial freezing method,especially the progressive freezing method,can reduce heavy metal pollutants in the soil and promises to be an effective in-situ treatment of contaminated sites.This study analyzes the freezing purification mechanism of heavy metal contaminants in saturated sand and identifies three main factors that impact the effects of purification:freezing rate,initial concentration,and diffusion coefficient.Moreover,one-dimensional freezing tests are carried out by different freezing modes.The experimental results show that the heavy metal chromium could only be removed effectively with a slow freezing rate.By optimizing the freezing mode and freezing rate,a long section of soil was frozen and purified,with the maximum purification rate reaching 65.8%.This study shows that it is feasible to treat contaminated saturated sand by a gradual-cooling freezing method.展开更多
In this paper,an approach is developed to optimize the quality of the training samples in the conventional Artificial Neural Network(ANN)by incorporating expert knowledge in the means of constructing expert-rule sampl...In this paper,an approach is developed to optimize the quality of the training samples in the conventional Artificial Neural Network(ANN)by incorporating expert knowledge in the means of constructing expert-rule samples from rules in an expert system,and through training by using these samples,an ANN based on expert-knowledge is further developed.The method is introduced into the field of quantitative identification of potential seismic sources on the basis of the rules in an expert system.Then it is applied to the quantitative identification of the potential seismic sources in Beijing and its adjacent area.The result indicates that the expert rule based on ANN method can well incorporate and represent the expert knowledge in the rules in an expert system,and the quality of the samples and the efficiency of training and the accuracy of the result are optimized.展开更多
For accurate trajectory tracking and obstacle avoidance in finite time of a nonholonomic mobile robot,a trajectory tracking controller based on global fast terminal sliding mode method is proposed,which has the advant...For accurate trajectory tracking and obstacle avoidance in finite time of a nonholonomic mobile robot,a trajectory tracking controller based on global fast terminal sliding mode method is proposed,which has the advantages of chattering-free and adjustable convergence time.First of all,the kinematics model of the robot is established in mobile carrier coordinates.Secondly,the global structure including terminal attractor and exponential convergence of the fast terminal sliding mode trajectory tracking controller is proved by Lyapunov stability theory,ensuring that the trajectory and heading angle tracking error converges to a smaller zero range in finite time.Finally,the artificial potential field obstacle avoidance method is introduced to make the robot not only track the reference trajectory strictly,but also avoid the obstacles.The simulation results show that the proposed method can achieve a stable tracking control in finite time for a given reference trajectory.展开更多
Purpose–This study purposes to study the influence of artificial freezing on the liquefaction characteristics of Nanjing sand,as well as its mechanism.Design/methodology/approach–was studied through dynamic triaxial...Purpose–This study purposes to study the influence of artificial freezing on the liquefaction characteristics of Nanjing sand,as well as its mechanism.Design/methodology/approach–was studied through dynamic triaxial tests by means of the GDS dynamic triaxial system on Nanjing sand extensively discovered in the middle and lower reaches of the Yangtze River under seismic load and metro train vibration load,respectively,and potential hazards of the two loads to the freezing construction of Nanjing sand were also identified in the tests.Findings–The results show that under both seismic load and metro train vibration load,freeze-thaw cycles will significantly reduce the stiffness and liquefaction resistance of Nanjing sand,especially in the first freezethaw cycle;the more freeze-thaw cycles,the worse structural behaviors of silty-fine sand,and the easier to liquefy;freeze-thaw cycles will increase the sensitivity of Nanjing sand’s dynamic pore pressure to dynamic load response;the lower the freezing temperature and the effective confining pressure,the worse the liquefaction resistance of Nanjing sand after freeze-thaw cycles;compared to the metro train vibration load,the seismic load in Nanjing is potentially less dangerous to freezing construction of Nanjing sand.Originality/value–The research results are helpful to the construction of the artificial ground freezing of the subway crossing passage in the lower reaches of the Yangtze River and to ensure the construction safety of the subway tunnel and its crossing passage.展开更多
Freeze-sealing pipe roof method is applied in the Gongbei tunnel,which causes the ground surface uplift induced by frost heave.A frost heaving prediction approach based on the coefficient of cold expansion is proposed...Freeze-sealing pipe roof method is applied in the Gongbei tunnel,which causes the ground surface uplift induced by frost heave.A frost heaving prediction approach based on the coefficient of cold expansion is proposed to simulate the ground deformation of the Gongbei tunnel.The coefficient of cold expansion in the model and the frost heaving rate from the frost heave test under the hydration condition can achieve a good correspondence making the calculation result closer to the actual engineering.The ground surface uplift along the lateral and longitudinal direction are respectively analyzed and compared with the field measured data to validate the model.The results show that a good agreement between the frost heaving prediction model and the field measured data verifies the rationality and applicability of the proposed model.The maximum uplift of the Gongbei tunnel appears at the center of the model,gradually decreasing along with the lateral and longitudinal directions.The curve in the lateral direction presents a normal distribution due to the influence of the constraint of two sides,while the one along the lateral direction shapes like a parabola with the opening downward due to the temperature field distribution.The model provides a reference for frost heaving engineering calculation.展开更多
Heterogeneous unmanned aerial vehicle(UAV)swarms have garnered significant attention from researchers worldwide due to their remarkable flexibility,diverse mission capabilities,and wide-ranging potential applications....Heterogeneous unmanned aerial vehicle(UAV)swarms have garnered significant attention from researchers worldwide due to their remarkable flexibility,diverse mission capabilities,and wide-ranging potential applications.Mission planning stands at the core of UAV swarm operations,requiring consideration of various factors including mission environment,requirements,and inherent characteristics.In this paper,we investigate the model of the cooperative tasking problem in heterogeneous UAV swarms.We provide a comprehensive review of artificial intelligence algorithms applied in UAV swarm mission planning,analyzing their strengths and weaknesses in multi-UAV cooperative environments.By discussing these key techniques and their practical applications,the article highlights future research trends and challenges.This review serves as a valuable reference for understanding the current state of AI algorithm applications in heterogeneous UAV swarm task assignments.展开更多
Three experiments are carried out for earthquake monitoring using electromagnetic （EM） methods in recent years. Some earthquakes occurred in chance of the measurement time period for each experiment and the anomalie...Three experiments are carried out for earthquake monitoring using electromagnetic （EM） methods in recent years. Some earthquakes occurred in chance of the measurement time period for each experiment and the anomalies were recorded before the shocks. The observation at a site 20 km away from the epicenter of Zhangbei Ms6.2 earthquake in 1998 shows that the apparent resistivity decreases in the strike direction before and/or during the earthquake and the resistivity increases in the decline direction. This anomalous variation in apparent resistivity accounts for about 20%. The apparent resistivities at a site in the epicentral area decrease in the strike and decline directions before and/or during the earthquake and increase after shocks. The experiments using artificial electromagnetic signals with super low frequency carried out in 1999 show that the resolution and stability of electric and magnetic spectra are improved. The spectra of electric and magnetic fields and apparent resistivity at the Baodi station began to anomalously change two days before the Qian＇an earthquake with 120 km distant to the station. The anomalous variation of electric and magnetic spectra is about twice as great as normal variation and the apparent resistivity changes by about 20%. The measurements in active seismic area of Yunnan province in the year 2005 indicate that the electric and magnetic spectra anomalously change by one order before the Taoyuan earthquake about 100 km away from the observatories. But the measurements at the sites in Beijing area 2 000 km away from the epicenter do not show any anomaly.展开更多
Landslide displacement prediction can enhance the efficacy of landslide monitoring system,and the prediction of the periodic displacement is particularly challenging.In the previous studies,static regression models(e....Landslide displacement prediction can enhance the efficacy of landslide monitoring system,and the prediction of the periodic displacement is particularly challenging.In the previous studies,static regression models(e.g.,support vector machine(SVM))were mostly used for predicting the periodic displacement.These models may have bad performances,when the dynamic features of landslide triggers are incorporated.This paper proposes a method for predicting the landslide displacement in a dynamic manner,based on the gated recurrent unit(GRU)neural network and complete ensemble empirical decomposition with adaptive noise(CEEMDAN).The CEEMDAN is used to decompose the training data,and the GRU is subsequently used for predicting the periodic displacement.Implementation procedures of the proposed method were illustrated by a case study in the Caojiatuo landslide area,and SVM was also adopted for the periodic displacement prediction.This case study shows that the predictors obtained by SVM are inaccurate,as the landslide displacement is in a pronouncedly step-wise manner.By contrast,the accuracy can be significantly improved using the dynamic predictive method.This paper reveals the significance of capturing the dynamic features of the inputs in the training process,when the machine learning models are adopted to predict the landslide displacement.展开更多
In this paper, we focus on circle formation control of multi-agent systems （MAS） with a leader. The circle formation is achieved based on the lead-following and the artificial potential field method. A distributed c...In this paper, we focus on circle formation control of multi-agent systems （MAS） with a leader. The circle formation is achieved based on the lead-following and the artificial potential field method. A distributed control law is given to make a group of agents form a circle and consequently achieve an expected angle. Finally, simulation results show that the proposed circle formation strategies are effective.展开更多
The purpose of this paper is to develop a general control method for swarm robot formation control. Firstly, an attraction-segment leader-follower formation graph is presented for formation representations. The model ...The purpose of this paper is to develop a general control method for swarm robot formation control. Firstly, an attraction-segment leader-follower formation graph is presented for formation representations. The model of swarm robot systems is described. According to the results and two kinds of artificial moments defined as leader-attraction moment and follower-attraction moment, a novel artificial moment method is proposed for swarm robot formation control. The principle of the method is introduced and the motion controller of robots is designed. Finally, the stability of the formation control system is proved. The simulations show that both the formation representation graph and the formation control method are valid and feasible.展开更多
The artificial boundary method is one of the most popular and effective numerical methods tor solving partial differential equations on unbounded domains, with more than thirty years development. The artificiM boundar...The artificial boundary method is one of the most popular and effective numerical methods tor solving partial differential equations on unbounded domains, with more than thirty years development. The artificiM boundary method has reached maturity in recent years. It has been applied to various problems in scientific and engineering computations, and the theoretical issues such as the convergence and error estimates of the artificial boundary method have been solved gradually. This paper reviews the development and discusses different forms of the artificial boundary method.展开更多
基金Supported by the National Natural Science Foundation of China (Grant No. 52071097)Hainan Provincial Natural Science Foundation of China (Grant No. 522MS162)Research Fund from Science and Technology on Underwater Vehicle Technology Laboratory (Grant No. 2021JCJQ-SYSJJ-LB06910)。
文摘Path planning for recovery is studied on the engineering background of double unmanned surface vehicles(USVs)towing oil booms for oil spill recovery.Given the influence of obstacles on the sea,the improved artificial potential field(APF)method is used for path planning.For addressing the two problems of unreachable target and local minimum in the APF,three improved algorithms are proposed by combining the motion performance constraints of the double USV system.These algorithms are then combined as the final APF-123 algorithm for oil spill recovery.Multiple sets of simulation tests are designed according to the flaws of the APF and the process of oil spill recovery.Results show that the proposed algorithms can ensure the system’s safety in tracking oil spills in a complex environment,and the speed is increased by more than 40%compared with the APF method.
基金supported by the Excellent National Key Laboratory Special Fund of China (No.41023003)the National Natural Science Foundation of China (No.41101068)+1 种基金the National Key Basic Research Program of China (973 Program) (No.2012CB026102)the project of the State Key Laboratory of Frozen Soil Engineering (No.SKLFSE-ZT-07)
文摘Because ice-high foundation soil is widely distributed in permafrost regions,the correct preparation of ice-high specimens is of critical interest in engineering design for foundation stability.Past research has shown that the uniaxial compression strength of ice-high frozen soils changes as the ice or total water content increases; the differences of different methods of specimen preparation are analyzed here and the advantages and disadvantages of them are presented.It is confirmed that the role of crushed ice is significantly different from that of naturally frozen ice in frozen soils,and the size and amount of crushed ice will influence the strength and deformation mechanism of frozen soils.Therefore,it is strongly recommended that when a ice-high specimen is artificially prepared,the ice should be frozen through natural means and not be replaced with crushed ice.
文摘A new analytical method using Back-Propagation (BP) artificial neural network and kinetic spectrophotometry for simultaneous determination of iron and magnesium in tap water, the Yellow River water and seawater is established. By conditional experiments, the optimum analytical conditions and parameters are obtained. Levenberg-Marquart (L-M) algorithm is used for calculation in BP neural network. The topological structure of three-layer BP ANN network architecture is chosen as 15-16-2 (nodes). The initial value of gradient coefficient μ is fixed at 0.001 and the increase factor and reduction factor of μ take the default values of the system. The data are processed by computers with our own programs written in MATLAB 7.0. The relative standard deviation of the calculated results for iron and manganese is 2.30% and 2.67% respectively. The results of standard addition method show that for the tap water, the recoveries of iron and manganese are in the ranges of 98.0%-104.3% and 96.5%-104.5%, and the RSD is in the range of 0.23%-0.98%; for the Yellow River water (Lijin district of Shandong Province), the recoveries of iron and manganese are in the ranges of 96.0%-101.0% and 98.7%-104.2%, and the RSD is in the range of 0.13%-2.52%; for the seawater in Qingdao offshore, the recoveries of iron and manganese are in the ranges of 95.3%-104.8% and 95.3%-104.7%, and the RSD is in the range of 0.14%-2.66%. It is found that 21 common cations and anions do not interfere with the determination of iron and manganese under the optimum experimental conditions. This method exhibits good reproducibility and high accuracy in the determination of iron and manganese and can be used for the simultaneous determination of iron and manganese in tap water and natural water. By using the established ANN- catalytic spectrophotometric method, the iron and manganese concentrations of the surface seawater at 11 sites in Qingdao offshore are determined and the level distribution maps of iron and manganese are drawn.
文摘The method of artificial potential field has obvious advantages among the robot path planning methods including simple structure,small amount of calculation and relatively mature in theory.This paper puts forward the"Integral method"focusing on solving the problem of local minimization.The method analyses the distribution of obstructions in a given environment and regards adjacent obstacles as a whole,By changing the parameters of the repulsive force field,robots can quickly get out of the minimum point and move to the target point.This paper uses the Simurosot platform to carry on the simulation experiment on the improved artificial potential field method,which projects a feasible path successfully and verifies this method.
文摘Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.
基金financially supported by the National Natural Science Foundation of China(Grant No.51278217)
文摘This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model;the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties;and finally,an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables.The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability.As a result,the obtained approximate function can be used as an alternative to the specific analysis process in c-φslope reliability analyses.
基金The project was supported by the Nutional Key Planning Development Project for Basic Research (G199903280l)the Key Innovition Project of the Chinese Academy of Sciences (KZCX2-208).
文摘The artificial compression method (ACM) that is generally used to capture the contact discontinuity in nonviscous flows is used here in the simulation of quasi-geostrophic ideal frontogenesis in two dimensions. A comparison is made among the result of the ACM, the simulation result of Cullen, and the exact solution of the semi-geostrophic equations. The simulated front in this paper is more prominent than Cullen′s and is much closer to the exact solution.
文摘Tsunami ran-up height is a significant parameter for dimensions of coastal structures. In the present study, tsunami run-up heights are estimated by three different Artificial Neural Network （ANN） models, i.e. Feed Forward Back Propagation （FFBP）, Radial Basis Functions （RBF） and Generalized Regression Neural Network （GRNN）. As the input for the ANN configuration, the wave height （H） values are employed. It is shown that the tsunami ran-up height values are closely approximated with all of the applied ANN methods. The ANN estimations are slightly superior to those of the empirical equation. It can be seen that the ANN applications are especially significant in the absence of adequate number of laboratory experiments. The results also prove that the available experiment data set can be extended with ANN simulations. This may be helpful to decrease the burden of the experimental studies and to supply results for comparisons.
基金supported by Major State Basic Research Development Program(Grant No.2012CB026103)111 Project of China(Grant No.B14021)+1 种基金National Natural Science Foundation of China(Grant No.51104146,Grant No.41271096)Open Fund of State Key Laboratory of Frozen Soil Engineering(Grant No.SKLFSE201704)。
文摘Heavy metal pollution of soil has become one of the most common hazards in human development.The artificial freezing method,especially the progressive freezing method,can reduce heavy metal pollutants in the soil and promises to be an effective in-situ treatment of contaminated sites.This study analyzes the freezing purification mechanism of heavy metal contaminants in saturated sand and identifies three main factors that impact the effects of purification:freezing rate,initial concentration,and diffusion coefficient.Moreover,one-dimensional freezing tests are carried out by different freezing modes.The experimental results show that the heavy metal chromium could only be removed effectively with a slow freezing rate.By optimizing the freezing mode and freezing rate,a long section of soil was frozen and purified,with the maximum purification rate reaching 65.8%.This study shows that it is feasible to treat contaminated saturated sand by a gradual-cooling freezing method.
文摘In this paper,an approach is developed to optimize the quality of the training samples in the conventional Artificial Neural Network(ANN)by incorporating expert knowledge in the means of constructing expert-rule samples from rules in an expert system,and through training by using these samples,an ANN based on expert-knowledge is further developed.The method is introduced into the field of quantitative identification of potential seismic sources on the basis of the rules in an expert system.Then it is applied to the quantitative identification of the potential seismic sources in Beijing and its adjacent area.The result indicates that the expert rule based on ANN method can well incorporate and represent the expert knowledge in the rules in an expert system,and the quality of the samples and the efficiency of training and the accuracy of the result are optimized.
基金National Natural Science Foundation of China(No.61673042)Shanxi Province Science Foundation for Youths(No.201701D221123)。
文摘For accurate trajectory tracking and obstacle avoidance in finite time of a nonholonomic mobile robot,a trajectory tracking controller based on global fast terminal sliding mode method is proposed,which has the advantages of chattering-free and adjustable convergence time.First of all,the kinematics model of the robot is established in mobile carrier coordinates.Secondly,the global structure including terminal attractor and exponential convergence of the fast terminal sliding mode trajectory tracking controller is proved by Lyapunov stability theory,ensuring that the trajectory and heading angle tracking error converges to a smaller zero range in finite time.Finally,the artificial potential field obstacle avoidance method is introduced to make the robot not only track the reference trajectory strictly,but also avoid the obstacles.The simulation results show that the proposed method can achieve a stable tracking control in finite time for a given reference trajectory.
基金supported by the National Natural Science Foundation of China(Grant No.U41702299).
文摘Purpose–This study purposes to study the influence of artificial freezing on the liquefaction characteristics of Nanjing sand,as well as its mechanism.Design/methodology/approach–was studied through dynamic triaxial tests by means of the GDS dynamic triaxial system on Nanjing sand extensively discovered in the middle and lower reaches of the Yangtze River under seismic load and metro train vibration load,respectively,and potential hazards of the two loads to the freezing construction of Nanjing sand were also identified in the tests.Findings–The results show that under both seismic load and metro train vibration load,freeze-thaw cycles will significantly reduce the stiffness and liquefaction resistance of Nanjing sand,especially in the first freezethaw cycle;the more freeze-thaw cycles,the worse structural behaviors of silty-fine sand,and the easier to liquefy;freeze-thaw cycles will increase the sensitivity of Nanjing sand’s dynamic pore pressure to dynamic load response;the lower the freezing temperature and the effective confining pressure,the worse the liquefaction resistance of Nanjing sand after freeze-thaw cycles;compared to the metro train vibration load,the seismic load in Nanjing is potentially less dangerous to freezing construction of Nanjing sand.Originality/value–The research results are helpful to the construction of the artificial ground freezing of the subway crossing passage in the lower reaches of the Yangtze River and to ensure the construction safety of the subway tunnel and its crossing passage.
基金supported by the financial support from National Natural Science Foundation of China(No.51478340)Natural Science Foundation of Jiangsu Province(No.BK20200707)+4 种基金The Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.20KJB560029)China Postdoctoral Science Foundation(No.2020M671670)Key Laboratory of Soft Soils and Geoenvironmental Engineering(Zhejiang University)Ministry of Education(No.2020P04)the support above is gratefully acknowledged.
文摘Freeze-sealing pipe roof method is applied in the Gongbei tunnel,which causes the ground surface uplift induced by frost heave.A frost heaving prediction approach based on the coefficient of cold expansion is proposed to simulate the ground deformation of the Gongbei tunnel.The coefficient of cold expansion in the model and the frost heaving rate from the frost heave test under the hydration condition can achieve a good correspondence making the calculation result closer to the actual engineering.The ground surface uplift along the lateral and longitudinal direction are respectively analyzed and compared with the field measured data to validate the model.The results show that a good agreement between the frost heaving prediction model and the field measured data verifies the rationality and applicability of the proposed model.The maximum uplift of the Gongbei tunnel appears at the center of the model,gradually decreasing along with the lateral and longitudinal directions.The curve in the lateral direction presents a normal distribution due to the influence of the constraint of two sides,while the one along the lateral direction shapes like a parabola with the opening downward due to the temperature field distribution.The model provides a reference for frost heaving engineering calculation.
文摘Heterogeneous unmanned aerial vehicle(UAV)swarms have garnered significant attention from researchers worldwide due to their remarkable flexibility,diverse mission capabilities,and wide-ranging potential applications.Mission planning stands at the core of UAV swarm operations,requiring consideration of various factors including mission environment,requirements,and inherent characteristics.In this paper,we investigate the model of the cooperative tasking problem in heterogeneous UAV swarms.We provide a comprehensive review of artificial intelligence algorithms applied in UAV swarm mission planning,analyzing their strengths and weaknesses in multi-UAV cooperative environments.By discussing these key techniques and their practical applications,the article highlights future research trends and challenges.This review serves as a valuable reference for understanding the current state of AI algorithm applications in heterogeneous UAV swarm task assignments.
基金supported by the National Natural Science Foundation of China (Grant No. 40534023)Public Professional Program of Earth-quake
文摘Three experiments are carried out for earthquake monitoring using electromagnetic （EM） methods in recent years. Some earthquakes occurred in chance of the measurement time period for each experiment and the anomalies were recorded before the shocks. The observation at a site 20 km away from the epicenter of Zhangbei Ms6.2 earthquake in 1998 shows that the apparent resistivity decreases in the strike direction before and/or during the earthquake and the resistivity increases in the decline direction. This anomalous variation in apparent resistivity accounts for about 20%. The apparent resistivities at a site in the epicentral area decrease in the strike and decline directions before and/or during the earthquake and increase after shocks. The experiments using artificial electromagnetic signals with super low frequency carried out in 1999 show that the resolution and stability of electric and magnetic spectra are improved. The spectra of electric and magnetic fields and apparent resistivity at the Baodi station began to anomalously change two days before the Qian＇an earthquake with 120 km distant to the station. The anomalous variation of electric and magnetic spectra is about twice as great as normal variation and the apparent resistivity changes by about 20%. The measurements in active seismic area of Yunnan province in the year 2005 indicate that the electric and magnetic spectra anomalously change by one order before the Taoyuan earthquake about 100 km away from the observatories. But the measurements at the sites in Beijing area 2 000 km away from the epicenter do not show any anomaly.
基金The authors appreciate the financial support provided by the Natural Science Foundation of China(No.41807294)This study was also financially supported by China Geological Survey Project(Nos.DD20190716 and 0001212020CC60002)。
文摘Landslide displacement prediction can enhance the efficacy of landslide monitoring system,and the prediction of the periodic displacement is particularly challenging.In the previous studies,static regression models(e.g.,support vector machine(SVM))were mostly used for predicting the periodic displacement.These models may have bad performances,when the dynamic features of landslide triggers are incorporated.This paper proposes a method for predicting the landslide displacement in a dynamic manner,based on the gated recurrent unit(GRU)neural network and complete ensemble empirical decomposition with adaptive noise(CEEMDAN).The CEEMDAN is used to decompose the training data,and the GRU is subsequently used for predicting the periodic displacement.Implementation procedures of the proposed method were illustrated by a case study in the Caojiatuo landslide area,and SVM was also adopted for the periodic displacement prediction.This case study shows that the predictors obtained by SVM are inaccurate,as the landslide displacement is in a pronouncedly step-wise manner.By contrast,the accuracy can be significantly improved using the dynamic predictive method.This paper reveals the significance of capturing the dynamic features of the inputs in the training process,when the machine learning models are adopted to predict the landslide displacement.
基金supported by the National Natural Science Foundation of China(No.61233002)the Fundamental Research Funds for the Central Universities(No.N120404019)
文摘In this paper, we focus on circle formation control of multi-agent systems （MAS） with a leader. The circle formation is achieved based on the lead-following and the artificial potential field method. A distributed control law is given to make a group of agents form a circle and consequently achieve an expected angle. Finally, simulation results show that the proposed circle formation strategies are effective.
基金the National Natural Science Foundation of China (Grant No.60574010)Programs for Liaoning Excellent Talents (Grant No.2006R31)+1 种基金for Liaoning Innovation Group In University (Grant No.2007T082)State Key Laboratory of Robotics and System (HIT)
文摘The purpose of this paper is to develop a general control method for swarm robot formation control. Firstly, an attraction-segment leader-follower formation graph is presented for formation representations. The model of swarm robot systems is described. According to the results and two kinds of artificial moments defined as leader-attraction moment and follower-attraction moment, a novel artificial moment method is proposed for swarm robot formation control. The principle of the method is introduced and the motion controller of robots is designed. Finally, the stability of the formation control system is proved. The simulations show that both the formation representation graph and the formation control method are valid and feasible.
基金supported by National National Science Foundation of China(Grant No.10971116)FRG of Hong Kong Baptist University(Grant No.FRG1/11-12/051)
文摘The artificial boundary method is one of the most popular and effective numerical methods tor solving partial differential equations on unbounded domains, with more than thirty years development. The artificiM boundary method has reached maturity in recent years. It has been applied to various problems in scientific and engineering computations, and the theoretical issues such as the convergence and error estimates of the artificial boundary method have been solved gradually. This paper reviews the development and discusses different forms of the artificial boundary method.
