Due to the significant effect of abnormal arrivals on localization accuracy,a novel acoustic emission(AE)source localization method using clustering detection to eliminate abnormal arrivals is proposed in the paper.Fi...Due to the significant effect of abnormal arrivals on localization accuracy,a novel acoustic emission(AE)source localization method using clustering detection to eliminate abnormal arrivals is proposed in the paper.Firstly,iterative weight estimation is utilized to obtain accurate equation residuals.Secondly,according to the distribution of equation residuals,clustering detection is used to identify and exclude abnormal arrivals.Thirdly,the AE source coordinate is recalculated with remaining normal arrivals.Experimental results of pencil-lead breaks indicate that the proposed method can achieve a better localization result with and without abnormal arrivals.The results of simulation tests further demonstrate that the proposed method possesses higher localization accuracy and robustness under different anomaly ratios and scales;even with abnormal arrivals as high as 30%,the proposed localization method still holds a correct detection rate of 91.85%.展开更多
We consider a variant of M/M/1 where customers arrive singly or in pairs. Each single and one member of each pair is called primary;the other member of each pair is called secondary. Each primary joins the queue upon ...We consider a variant of M/M/1 where customers arrive singly or in pairs. Each single and one member of each pair is called primary;the other member of each pair is called secondary. Each primary joins the queue upon arrival. Each secondary is delayed in a separate area, and joins the queue when “pushed” by the next arriving primary. Thus each secondary joins the queue followed immediately by the next primary. This arrival/delay mechanism appears to be new in queueing theory. Our goal is to obtain the steady-state probability density function (pdf) of the workload, and related quantities of interest. We utilize a typical sample path of the workload process as a physical guide, and simple level crossing theorems, to derive model equations for the steady-state pdf. A potential application is to the processing of electronic signals with error free components and components that require later confirmation before joining the queue. The confirmation is the arrival of the next signal.展开更多
Tourism is one of the major contributors to foreign exchange earnings to Zambia and world economy. Annual International tourist arrivals in Zambia from 1995 to 2014 are considered in this paper. In this study we evalu...Tourism is one of the major contributors to foreign exchange earnings to Zambia and world economy. Annual International tourist arrivals in Zambia from 1995 to 2014 are considered in this paper. In this study we evaluated the model performance of Auto-Regressive Integrated Moving Average (ARIMA) and Holt Winters exponential smoothing (HWES). The error indicators: Mean percentage error (MPE), Mean absolute error (MAE), Mean absolute scaled error (MASE), Root-mean-square error (RMSE) and Mean absolute percentage error (MAPE) showed that HWES is an appropriate model with reasonable forecast accuracy. The HWES (α = 1, β = 0.1246865) showed smallest error than those of the ARIMA (0, 1, 2) models. Hence, the HWES (α = 1, β = 0.1246865) can be used to model annual international tourist arrivals in Zambia. Further, forecasting results give a gradual increase in annual international tourist arrivals of about 42% by 2024. Accurate forecasts are key to new investors and Policymakers. The Zambian government should use such forecasts in formulating policies and making strategies that will promote the tourism industry.展开更多
The Singapore Tourism Board announced on February 13 that the Chinese mainland held onto its rank as Singapore’s top visitor arrival source market for a second year.
Respecting the on-time-delivery (OTD) for manufacturing orders is mandatory. This depends, however, on the probability distribution of incoming order rate. The case of non-equal distribution, such as aggregated arriva...Respecting the on-time-delivery (OTD) for manufacturing orders is mandatory. This depends, however, on the probability distribution of incoming order rate. The case of non-equal distribution, such as aggregated arrivals, may compromise the observance of on-time supplies for some orders. The purpose of this paper is to evaluate the conditions of post-optimality for stochastic order rate governed production systems in order to observe OTD. Instead of a heuristic or a simulative exploration, a Cartesian-based approach is applied to developing the necessary and sufficient mathematical condition to solve the problem statement. The research result demonstrates that increasing </span><span style="font-family:Verdana;">speed of throughput reveals a latent capacity, which allows arrival orders </span><span style="font-family:Verdana;">above capacity limits to be backlog-buffered and rescheduled for OTD, exploiting the virtual manufacturing elasticity inherent to all production systems to increase OTD reliability of non JIT-based production systems.展开更多
A risk model with Markovian arrivals and tax payments is considered.When the insurer is in a profitable situation,the insurer may pay a certain proportion of the premium income as tax payments.First,the Laplace transf...A risk model with Markovian arrivals and tax payments is considered.When the insurer is in a profitable situation,the insurer may pay a certain proportion of the premium income as tax payments.First,the Laplace transform of the time to cross a certain level before ruin is discussed.Second,explicit formulas for a generalized Gerber-Shiu function are established in terms of the'original'Gerber-Shiu function without tax and the Laplace transform of the first passage time before ruin.Finally,the differential equations satisfied by the expected accumulated discounted tax payments until ruin are derived.An explicit expression for the discounted tax payments is also given.展开更多
Mobile location using angle of arrival (AOA) measurements has received considerable attention. This paper presents an approximation of maximum likelihood estimator (MLE) for localizing a source based on AOA measur...Mobile location using angle of arrival (AOA) measurements has received considerable attention. This paper presents an approximation of maximum likelihood estimator (MLE) for localizing a source based on AOA measurements. By introducing an intermediate variable, the nonlinear equations relating AOA estimates can be transformed into a set of equations which are linear in the unknown parameters. It is an approximate realization of the MLE. Simulations show that the proposed algorithm outperforms the previous contribution.展开更多
A single-server queueing system with preemptive access is considered.Each customer has one attempt to enter the system at its working interval[0,T].As soon as the customer request enters the system,the server immediat...A single-server queueing system with preemptive access is considered.Each customer has one attempt to enter the system at its working interval[0,T].As soon as the customer request enters the system,the server immediately starts the service.But when the next request arrives in the system,the previous one leaves the system even he has not finished his service yet.We study a non-cooperative game in which the customers wish to maximize their probability of obtaining service within a certain period of time.We characterize the Nash equilibrium and the price of anarchy,which is defined as the ratio between the optimal and equilibrium social utility.Two models are considered.In the first model the number of players is fixed,while in the second it is random and obeys the Poisson distribution.We demonstrate that there exists a unique symmetric equilibrium for both models.Finally,we calculate the price of anarchy for both models and show that the price of anarchy is not monotone with respect to the number of customers.展开更多
An approach of separating individual wave arrivals for a dipole logging is presented. The branch points are treated as a type of logarithm and the Riemann surface structure of the multivalued function is studied, that...An approach of separating individual wave arrivals for a dipole logging is presented. The branch points are treated as a type of logarithm and the Riemann surface structure of the multivalued function is studied, that is, the displacement potential within the borehole. Based on the theoretical analysis, the complex poles contributing to the wave field on various Riemann sheets are investigated in detail for the case of a fast formation. It is shown that poles on Riemann sheet (0,0) are real and form branches of modes with dispersion. Mathematically, it is demonstrated that the flexural mode has no cutoff frequency, which is different from the traditional point of view. Poles on other relevant Riemann sheets are complex and form many branches on the complex frequency-wavenumber plane. Further investigation on the pole and branch cut contributions indicates that the vertical branch cut integration method has limitations in separating wave arrivals. By properly taking into account the complex poles on various Riemann sheets together with branch cut integrations, wave arrivals are separated from the full wave-forms effectively for both the fast and slow formation models. Specially, there are complex poles on Riemann sheet (0,-1) in the vicinity of the compressional branch cut for a slow formation with a large Poisson's ratio, which have small imaginary parts and contribute a lot to the p-wave arrival.展开更多
Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current...Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current arrival picking methods.Thus,a real-time arrival picking method of MS signals is constructed based on a convolutional-recurrent neural network(CRNN).This method fully utilizes the advantages of convolutional layers and gated recurrent units(GRU)in extracting short-and long-term features,in order to create a precise and lightweight arrival picking structure.Then,the synthetic signals with field noises are used to evaluate the hyperparameters of the CRNN model and obtain an optimal CRNN model.The actual operation on various devices indicates that compared with the U-Net method,the CRNN method achieves faster arrival picking with less performance consumption.An application of large underground caverns in the Yebatan hydropower station(YBT)project shows that compared with the short-term average/long-term average(STA/LTA),Akaike information criterion(AIC)and U-Net methods,the CRNN method has the highest accuracy within four sampling points,which is 87.44%for P-wave and 91.29%for S-wave,respectively.The sum of mean absolute errors(MAESUM)of the CRNN method is 4.22 sampling points,which is lower than that of the other methods.Among the four methods,the MS sources location calculated based on the CRNN method shows the best consistency with the actual failure,which occurs at the junction of the shaft and the second gallery.Thus,the proposed method can pick up P-and S-arrival accurately and rapidly,providing a reference for rock failure analysis and evaluation in engineering applications.展开更多
Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the leak.However,due to the complexity and variability of the mari...Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the leak.However,due to the complexity and variability of the marine environment,the signals collected by hydrophone contain a variety of noises,which makes it challenging to extract useful signals for localization.To solve this problem,a hydrophone denoising algorithm is proposed based on variational modal decomposition(VMD)with grey wolf optimization.First,the average envelope entropy is used as the fitness function of the grey wolf optimizer to find the optimal solution for the parameters K andα.Afterward,the VMD algorithm decomposes the original signal parameters to obtain the intrinsic mode functions(IMFs).Subsequently,the number of interrelationships between each IMF and the original signal was calculated,the threshold value was set,and the noise signal was removed to calculate the time difference using the valid signal obtained by reconstruction.Finally,the arrival time difference is used to locate the origin of the leak.The localization accuracy of the method in finding leaks is investigated experimentally by constructing a simulated leak test rig,and the effectiveness and feasibility of the method are verified.展开更多
Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suf...Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.展开更多
Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based ...Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.展开更多
The prediction of the Baidu index for tourism demand has been increasingly focused on by scholars.However,few studies have evaluated the predictive power of the Baidu index for hotel guest arrivals in fine granularity...The prediction of the Baidu index for tourism demand has been increasingly focused on by scholars.However,few studies have evaluated the predictive power of the Baidu index for hotel guest arrivals in fine granularity at the micro level.Taking Guilin as a case study,we use the OLS regression method to quantitatively investigate the forecasting power of the Baidu index for daily hotel guest arrivals and to comprehensively evaluate the performance of the forecasting model and to optimize the forecasting model by deeply mining the hidden characteristics of tourism flow in a special case study.The contributions of this papermainly have threefold:first,to the best of our knowledge,based on the actual full-example of daily hotel guest check-in data in fine granularity,we evaluated the predictive power of the Baidu index by comparison of 5 forecasting models for the first time.Second,we proposed two metrics for forecasting:the trend forecasting index and the forecasting stability index.Finally,we introduce a kind of punishment strategy to optimize forecasting models based on the potential pattern of research objects.展开更多
The use of traditional positioning technologies, such as GPS and wireless local positioning, rely on un- derlying infrastructure. However, in a subway environment, such positioning systems are not available for the po...The use of traditional positioning technologies, such as GPS and wireless local positioning, rely on un- derlying infrastructure. However, in a subway environment, such positioning systems are not available for the position- ing tasks, such as the detection of the train arrivals for the passengers in the train. An alternative approach is to exploit the contextual information available in the mobile devices of subway riders to detect train arrivals. To this end, we pro- pose to exploit multiple contextual features extracted from the mobile devices of subway riders to precisely detecting train arrivals. Following this line, we first investigate poten- tial contextual features which may be effective to detect train arrivals according to the observations from 3D accelerome- ters and GSM radio. Furthermore, we propose to explore the maximum entropy (MaxEnt) model for training a train ar- rival detector by learning the correlation between contextual features and train arrivals. Finally, we perform extensive ex- periments on several real-world data sets collected from two major subway lines in the Beijing subway system. Experi- mental results validate both the effectiveness and efficiency of the proposed approach.展开更多
基金financial support provided by the National Natural Science Foundation of China(Grant No.41772313)Hunan Science and Technology Planning Project(Grant No.2019RS3001).
文摘Due to the significant effect of abnormal arrivals on localization accuracy,a novel acoustic emission(AE)source localization method using clustering detection to eliminate abnormal arrivals is proposed in the paper.Firstly,iterative weight estimation is utilized to obtain accurate equation residuals.Secondly,according to the distribution of equation residuals,clustering detection is used to identify and exclude abnormal arrivals.Thirdly,the AE source coordinate is recalculated with remaining normal arrivals.Experimental results of pencil-lead breaks indicate that the proposed method can achieve a better localization result with and without abnormal arrivals.The results of simulation tests further demonstrate that the proposed method possesses higher localization accuracy and robustness under different anomaly ratios and scales;even with abnormal arrivals as high as 30%,the proposed localization method still holds a correct detection rate of 91.85%.
文摘We consider a variant of M/M/1 where customers arrive singly or in pairs. Each single and one member of each pair is called primary;the other member of each pair is called secondary. Each primary joins the queue upon arrival. Each secondary is delayed in a separate area, and joins the queue when “pushed” by the next arriving primary. Thus each secondary joins the queue followed immediately by the next primary. This arrival/delay mechanism appears to be new in queueing theory. Our goal is to obtain the steady-state probability density function (pdf) of the workload, and related quantities of interest. We utilize a typical sample path of the workload process as a physical guide, and simple level crossing theorems, to derive model equations for the steady-state pdf. A potential application is to the processing of electronic signals with error free components and components that require later confirmation before joining the queue. The confirmation is the arrival of the next signal.
文摘Tourism is one of the major contributors to foreign exchange earnings to Zambia and world economy. Annual International tourist arrivals in Zambia from 1995 to 2014 are considered in this paper. In this study we evaluated the model performance of Auto-Regressive Integrated Moving Average (ARIMA) and Holt Winters exponential smoothing (HWES). The error indicators: Mean percentage error (MPE), Mean absolute error (MAE), Mean absolute scaled error (MASE), Root-mean-square error (RMSE) and Mean absolute percentage error (MAPE) showed that HWES is an appropriate model with reasonable forecast accuracy. The HWES (α = 1, β = 0.1246865) showed smallest error than those of the ARIMA (0, 1, 2) models. Hence, the HWES (α = 1, β = 0.1246865) can be used to model annual international tourist arrivals in Zambia. Further, forecasting results give a gradual increase in annual international tourist arrivals of about 42% by 2024. Accurate forecasts are key to new investors and Policymakers. The Zambian government should use such forecasts in formulating policies and making strategies that will promote the tourism industry.
文摘The Singapore Tourism Board announced on February 13 that the Chinese mainland held onto its rank as Singapore’s top visitor arrival source market for a second year.
文摘Respecting the on-time-delivery (OTD) for manufacturing orders is mandatory. This depends, however, on the probability distribution of incoming order rate. The case of non-equal distribution, such as aggregated arrivals, may compromise the observance of on-time supplies for some orders. The purpose of this paper is to evaluate the conditions of post-optimality for stochastic order rate governed production systems in order to observe OTD. Instead of a heuristic or a simulative exploration, a Cartesian-based approach is applied to developing the necessary and sufficient mathematical condition to solve the problem statement. The research result demonstrates that increasing </span><span style="font-family:Verdana;">speed of throughput reveals a latent capacity, which allows arrival orders </span><span style="font-family:Verdana;">above capacity limits to be backlog-buffered and rescheduled for OTD, exploiting the virtual manufacturing elasticity inherent to all production systems to increase OTD reliability of non JIT-based production systems.
基金Supported by the National Natural Science Foundation of China(10971230,11171179)the Natural Science Foundation of Shandong Province(ZR2010AQ015)the Tianyuan Fund for Mathematics(11126232)
文摘A risk model with Markovian arrivals and tax payments is considered.When the insurer is in a profitable situation,the insurer may pay a certain proportion of the premium income as tax payments.First,the Laplace transform of the time to cross a certain level before ruin is discussed.Second,explicit formulas for a generalized Gerber-Shiu function are established in terms of the'original'Gerber-Shiu function without tax and the Laplace transform of the first passage time before ruin.Finally,the differential equations satisfied by the expected accumulated discounted tax payments until ruin are derived.An explicit expression for the discounted tax payments is also given.
文摘Mobile location using angle of arrival (AOA) measurements has received considerable attention. This paper presents an approximation of maximum likelihood estimator (MLE) for localizing a source based on AOA measurements. By introducing an intermediate variable, the nonlinear equations relating AOA estimates can be transformed into a set of equations which are linear in the unknown parameters. It is an approximate realization of the MLE. Simulations show that the proposed algorithm outperforms the previous contribution.
基金supported by the Russian Science Foundation(No.22-11-20015,https://rscf.ru/project/22-11-20015/)jointly with support of the authorities of the Republic of Karelia with funding from the Venture Investment Foundation of the Republic of Karelia.Also the research was supported by the National Natural Science Foundation of China(No.72171126).
文摘A single-server queueing system with preemptive access is considered.Each customer has one attempt to enter the system at its working interval[0,T].As soon as the customer request enters the system,the server immediately starts the service.But when the next request arrives in the system,the previous one leaves the system even he has not finished his service yet.We study a non-cooperative game in which the customers wish to maximize their probability of obtaining service within a certain period of time.We characterize the Nash equilibrium and the price of anarchy,which is defined as the ratio between the optimal and equilibrium social utility.Two models are considered.In the first model the number of players is fixed,while in the second it is random and obeys the Poisson distribution.We demonstrate that there exists a unique symmetric equilibrium for both models.Finally,we calculate the price of anarchy for both models and show that the price of anarchy is not monotone with respect to the number of customers.
基金Supported by the National Natural Science Foundation of China (Grant No.10534040)
文摘An approach of separating individual wave arrivals for a dipole logging is presented. The branch points are treated as a type of logarithm and the Riemann surface structure of the multivalued function is studied, that is, the displacement potential within the borehole. Based on the theoretical analysis, the complex poles contributing to the wave field on various Riemann sheets are investigated in detail for the case of a fast formation. It is shown that poles on Riemann sheet (0,0) are real and form branches of modes with dispersion. Mathematically, it is demonstrated that the flexural mode has no cutoff frequency, which is different from the traditional point of view. Poles on other relevant Riemann sheets are complex and form many branches on the complex frequency-wavenumber plane. Further investigation on the pole and branch cut contributions indicates that the vertical branch cut integration method has limitations in separating wave arrivals. By properly taking into account the complex poles on various Riemann sheets together with branch cut integrations, wave arrivals are separated from the full wave-forms effectively for both the fast and slow formation models. Specially, there are complex poles on Riemann sheet (0,-1) in the vicinity of the compressional branch cut for a slow formation with a large Poisson's ratio, which have small imaginary parts and contribute a lot to the p-wave arrival.
基金We acknowledge the funding support from National Natural Science Foundation of China(Grant No.42077263).
文摘Accurately picking P-and S-wave arrivals of microseismic(MS)signals in real-time directly influences the early warning of rock mass failure.A common contradiction between accuracy and computation exists in the current arrival picking methods.Thus,a real-time arrival picking method of MS signals is constructed based on a convolutional-recurrent neural network(CRNN).This method fully utilizes the advantages of convolutional layers and gated recurrent units(GRU)in extracting short-and long-term features,in order to create a precise and lightweight arrival picking structure.Then,the synthetic signals with field noises are used to evaluate the hyperparameters of the CRNN model and obtain an optimal CRNN model.The actual operation on various devices indicates that compared with the U-Net method,the CRNN method achieves faster arrival picking with less performance consumption.An application of large underground caverns in the Yebatan hydropower station(YBT)project shows that compared with the short-term average/long-term average(STA/LTA),Akaike information criterion(AIC)and U-Net methods,the CRNN method has the highest accuracy within four sampling points,which is 87.44%for P-wave and 91.29%for S-wave,respectively.The sum of mean absolute errors(MAESUM)of the CRNN method is 4.22 sampling points,which is lower than that of the other methods.Among the four methods,the MS sources location calculated based on the CRNN method shows the best consistency with the actual failure,which occurs at the junction of the shaft and the second gallery.Thus,the proposed method can pick up P-and S-arrival accurately and rapidly,providing a reference for rock failure analysis and evaluation in engineering applications.
基金financially supported by the National Key Research and Development Program of China(Grant No.2022YFC2806102)the National Natural Science Foundation of China(Grant Nos.52171287,52325107)+2 种基金High Tech Ship Research Project of Ministry of Industry and Information Technology(Grant Nos.2023GXB01-05-004-03,GXBZH2022-293)the Science Foundation for Distinguished Young Scholars of Shandong Province(Grant No.ZR2022JQ25)the Taishan Scholars Project(Grant No.tsqn201909063)。
文摘Leakages from subsea oil and gas equipment cause substantial economic losses and damage to marine ecosystem,so it is essential to locate the source of the leak.However,due to the complexity and variability of the marine environment,the signals collected by hydrophone contain a variety of noises,which makes it challenging to extract useful signals for localization.To solve this problem,a hydrophone denoising algorithm is proposed based on variational modal decomposition(VMD)with grey wolf optimization.First,the average envelope entropy is used as the fitness function of the grey wolf optimizer to find the optimal solution for the parameters K andα.Afterward,the VMD algorithm decomposes the original signal parameters to obtain the intrinsic mode functions(IMFs).Subsequently,the number of interrelationships between each IMF and the original signal was calculated,the threshold value was set,and the noise signal was removed to calculate the time difference using the valid signal obtained by reconstruction.Finally,the arrival time difference is used to locate the origin of the leak.The localization accuracy of the method in finding leaks is investigated experimentally by constructing a simulated leak test rig,and the effectiveness and feasibility of the method are verified.
基金National Natural Science Foundation of China(61973037)National 173 Program Project(2019-JCJQ-ZD-324)。
文摘Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.
基金supported by the National Natural Science Foundation of China(No.51279033).
文摘Underwater direction of arrival(DOA)estimation has always been a very challenging theoretical and practical problem.Due to the serious non-stationary,non-linear,and non-Gaussian characteristics,machine learning based DOA estimation methods trained on simulated Gaussian noised array data cannot be directly applied to actual underwater DOA estimation tasks.In order to deal with this problem,environmental data with no target echoes can be employed to analyze the non-Gaussian components.Then,the obtained information about non-Gaussian components can be used to whiten the array data.Based on these considerations,a novel practical sonar array whitening method was proposed.Specifically,based on a weak assumption that the non-Gaussian components in adjacent patches with and without target echoes are almost the same,canonical cor-relation analysis(CCA)and non-negative matrix factorization(NMF)techniques are employed for whitening the array data.With the whitened array data,machine learning based DOA estimation models trained on simulated Gaussian noised datasets can be used to perform underwater DOA estimation tasks.Experimental results illustrated that,using actual underwater datasets for testing with known machine learning based DOA estimation models,accurate and robust DOA estimation performance can be achieved by using the proposed whitening method in different underwater con-ditions.
基金supported by the research on key technology of tourism destination safety warning and its application demonstration granted by No.Guike AB17195028technology development of tourist safety warning system for smart scenic spot and virtual spatiotemporal reconstruction of special culture and its application demonstration granted by No.20170220research on sustainable utility technology integration of Longji terrace landscape resources and tourism industry demonstration granted by No.20180102-2,Guangxi natural science fund by No.2018GXNSFAA138209.
文摘The prediction of the Baidu index for tourism demand has been increasingly focused on by scholars.However,few studies have evaluated the predictive power of the Baidu index for hotel guest arrivals in fine granularity at the micro level.Taking Guilin as a case study,we use the OLS regression method to quantitatively investigate the forecasting power of the Baidu index for daily hotel guest arrivals and to comprehensively evaluate the performance of the forecasting model and to optimize the forecasting model by deeply mining the hidden characteristics of tourism flow in a special case study.The contributions of this papermainly have threefold:first,to the best of our knowledge,based on the actual full-example of daily hotel guest check-in data in fine granularity,we evaluated the predictive power of the Baidu index by comparison of 5 forecasting models for the first time.Second,we proposed two metrics for forecasting:the trend forecasting index and the forecasting stability index.Finally,we introduce a kind of punishment strategy to optimize forecasting models based on the potential pattern of research objects.
文摘The use of traditional positioning technologies, such as GPS and wireless local positioning, rely on un- derlying infrastructure. However, in a subway environment, such positioning systems are not available for the position- ing tasks, such as the detection of the train arrivals for the passengers in the train. An alternative approach is to exploit the contextual information available in the mobile devices of subway riders to detect train arrivals. To this end, we pro- pose to exploit multiple contextual features extracted from the mobile devices of subway riders to precisely detecting train arrivals. Following this line, we first investigate poten- tial contextual features which may be effective to detect train arrivals according to the observations from 3D accelerome- ters and GSM radio. Furthermore, we propose to explore the maximum entropy (MaxEnt) model for training a train ar- rival detector by learning the correlation between contextual features and train arrivals. Finally, we perform extensive ex- periments on several real-world data sets collected from two major subway lines in the Beijing subway system. Experi- mental results validate both the effectiveness and efficiency of the proposed approach.