A method utilizing variable depth increments during incremental forming was proposed and then optimized based on numerical simulation and intelligent algorithm.Initially,a finite element method(FEM) model was set up a...A method utilizing variable depth increments during incremental forming was proposed and then optimized based on numerical simulation and intelligent algorithm.Initially,a finite element method(FEM) model was set up and then experimentally verified.And the relation between depth increment and the minimum thickness tmin as well as its location was analyzed through the FEM model.Afterwards,the variation of depth increments was defined.The designed part was divided into three areas according to the main deformation mechanism,with Di(i=1,2) representing the two dividing locations.And three different values of depth increment,Δzi(i=1,2,3) were utilized for the three areas,respectively.Additionally,an orthogonal test was established to research the relation between the five process parameters(D and Δz) and tmin as well as its location.The result shows that Δz2 has the most significant influence on the thickness distribution for the corresponding area is the largest one.Finally,a single evaluating indicator,taking into account of both tmin and its location,was formatted with a linear weighted model.And the process parameters were optimized through a genetic algorithm integrated with an artificial neural network based on the evaluating index.The result shows that the proposed algorithm is satisfactory for the optimization of variable depth increment.展开更多
In practical applications, the system observation error is widespread. If the observation equation of the system has not been verified or corrected under certain environmental conditions,the unknown system errors and ...In practical applications, the system observation error is widespread. If the observation equation of the system has not been verified or corrected under certain environmental conditions,the unknown system errors and filtering errors will come into being.The incremental observation equation is derived, which can eliminate the unknown observation errors effectively. Furthermore, an incremental Kalman smoother is presented. Moreover, a weighted measurement fusion incremental Kalman smoother applying the globally optimal weighted measurement fusion algorithm is given.The simulation results show their effectiveness and feasibility.展开更多
Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as (event-bas...Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as (event-based) incremental updating (E-BIU) is proposed in this paper. At first, the relationship among the events, spatial changes and the database operations is analyzed, then a total architecture of E-BIU implementation is designed, which includes an event queue, three managers and two sets of rules, each component is presented in detail. The process of the E-BIU of master STDB is described successively. An example of building’s incremental updating is given to illustrate this approach at the end. The result shows that E-BIU is an efficient automatic updating approach for master STDB.展开更多
A new incremental support vector machine （SVM） algorithm is proposed which is based on multiple kernel learning. Through introducing multiple kernel learning into the SVM incremental learning, large scale data set l...A new incremental support vector machine （SVM） algorithm is proposed which is based on multiple kernel learning. Through introducing multiple kernel learning into the SVM incremental learning, large scale data set learning problem can be solved effectively. Furthermore, different punishments are adopted in allusion to the training subset and the acquired support vectors, which may help to improve the performance of SVM. Simulation results indicate that the proposed algorithm can not only solve the model selection problem in SVM incremental learning, but also improve the classification or prediction precision.展开更多
In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of ind...In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of independent variables （the microwave power, the acting time and the rotational frequency） for microwave drying of selenium-rich slag. The optimum operating conditions obtained from the quadratic form of the RSM are： the microwave power of 14.97 kW, the acting time of 89.58 min, the rotational frequency of 10.94 Hz, and the temperature of 136.407 ℃. The relative dehydration rate of 97.1895% is obtained. Under the optimum operating conditions, the incremental improved BP neural network prediction model can predict the drying process results and different effects on the results of the independent variables. The verification experiments demonstrate the prediction accuracy of the network, and the mean squared error is 0.16. The optimized results indicate that RSM can optimize the experimental conditions within much more broad range by considering the combination of factors and the neural network model can predict the results effectively and provide the theoretical guidance for the follow-up production process.展开更多
The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the t...The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the traditional PID control has been proven not sufficient and capable for this particular petro-chemical process.In this work,an incremental multivariable predictive functional control(IMPFC) algorithm was proposed with less online computation,great precision and fast response.An incremental transfer function matrix model was set up through the step-response data,and predictive outputs were deduced with the theory of single-value optimization.The results show that the method can optimize the incremental control variable and reject the constraint of the incremental control variable with the positional predictive functional control algorithm,and thereby making the control variable smoother.The predictive output error and future set-point were approximated by a polynomial,which can overcome the problem under the model mismatch and make the predictive outputs track the reference trajectory.Then,the design of incremental multivariable predictive functional control was studied.Simulation and application results show that the proposed control strategy is effective and feasible to improve control performance and robustness of process.展开更多
In order to investigate the process of incremental sheet forming (ISF) through both experimental and numerical approaches, a three-dimensional elasto-plastic finite element model (FEM) was developed to simulate the pr...In order to investigate the process of incremental sheet forming (ISF) through both experimental and numerical approaches, a three-dimensional elasto-plastic finite element model (FEM) was developed to simulate the process and the simulated results were compared with those of experiment. The results of numerical simulations, such as the strain history and distribution, the stress state and distribution, sheet thickness distribution, etc, were discussed in details, and the influences of process parameters on these results were also analyzed. The simulated results of the radial strain and the thickness distribution are in good agreement with experimental results. The simulations reveal that the deformation is localized around the tool and constantly remains close to a plane strain state. With decreasing depth step, increasing tool diameter and wall inclination angle, the axial stress reduces, leading to less thinning and more homogeneous plastic strain and thickness distribution. During ISF, the plastic strain increases stepwise under the action of the tool. Each increase in plastic strain is accompanied by hydrostatic pressure, which explains why obtainable deformation using ISF exceeds the forming limits of conventional sheet forming.展开更多
Path planning of a mobile robot in the presence of multiple moving obstacles is found to be a complicated problem.A planning algorithm capable of negotiating both static and moving obstacles in an unpredictable(on-lin...Path planning of a mobile robot in the presence of multiple moving obstacles is found to be a complicated problem.A planning algorithm capable of negotiating both static and moving obstacles in an unpredictable(on-line)environment is proposed.The proposed incremental algorithm plans the path by considering the quadrants in which the current positions of obstacles as well as target are situated.Also,the governing equations for the shortest path are derived.The proposed mathematical model describes the motion(satisfying constraints of the mobile robot)along a collision-free path.Further,the algorithm is applicable to dynamic environments with fixed or moving targets.Simulation results show the effectiveness of the proposed algorithm.Comparison of results with the improved artificial potential field(iAPF)algorithm shows that the proposed algorithm yields shorter path length with less computation time.展开更多
The criteria for evaluation of train derailment were studied. The worldwide commonly used evaluation criteria for wheel derailment were summarized and their main problems were pointed out. The mechanism of train derai...The criteria for evaluation of train derailment were studied. The worldwide commonly used evaluation criteria for wheel derailment were summarized and their main problems were pointed out. The mechanism of train derailment was expounded on the basis of system dynamics stability concept. And the energy increment criteria were proposed to evaluate train derailment. By applying the criteria, the calculated results concerning 6 cases of freight train derailment on tangent railway line and 6 cases of freight train derailment on bridge were obtained, which are all in agreement with the practical situation. The safety, comfort and stability results concerning 3 cases of freight train running on bridge were analyzed. In addition, the running speed limits of freight train on the Yanconggou and Donggou bridge in the Beijing-Tonghua railway line of 50km/h and 60km/h, respectively, were proposed. And the running speed of freight train on the Nanjing Yangtze River Bridge can reach 70km/h.展开更多
In this present paper, a deterministic lot size model is developed for deteriorating items with incremental quantity discounts. It is assumed that shortages are permitted to occur and fully backlogged. A simple solut...In this present paper, a deterministic lot size model is developed for deteriorating items with incremental quantity discounts. It is assumed that shortages are permitted to occur and fully backlogged. A simple solution procedure is shown for determining the optimal order lot size and the optimal order cycle. A numerical example is used to illustrate how the solution procedure works.展开更多
The scheme for tracking maneuvering target based on neural fuzzy network with incremental neural learning is proposed. When tracked target maneuver occurs, the scheme can detect maneuver immediately and estimate the m...The scheme for tracking maneuvering target based on neural fuzzy network with incremental neural learning is proposed. When tracked target maneuver occurs, the scheme can detect maneuver immediately and estimate the maneuver value accurately , then the tracking filter can be compensated correctly and duly by the estimated maneuver value. When environment changes, neural fuzzy network with incremental neural learning （INL-SONFIN） can find its optimal structure and parameters automatically to adopt to changed environment. So, it always produce estimated output very close to the true maneuver value that leads to good tracking performance and avoids misstracking. Simulation results show that the performance is superior to the traditional schemes and the scheme can fit changed dynamic environment to track maneuvering target accurately and duly.展开更多
The closed loop control model was built up for compensating the springback and enhancing the work piece precision.A coupled closed loop algorithm and a finite element method were developed to simulate and correct the ...The closed loop control model was built up for compensating the springback and enhancing the work piece precision.A coupled closed loop algorithm and a finite element method were developed to simulate and correct the springback of incremental sheet forming.A three-dimensional finite element model was established for simulation of springback in incremental sheet forming process.The closed loop algorithm of trajectory profile for the incremental sheet forming based on the wavelet transform combined with fast Fourier transform was constructed.The profile of processing tool path of shallow dishing with spherical surface was designed on the basis of the profile correction algorithm.The result shows that the algorithm can predict an ideal profile of processing track,and the springback error of incremental sheet forming is eliminated effectively.It has good convergence efficiency,and can improve the workpiece dimensional accuracy greatly.展开更多
Although multi-stage incremental sheet forming has always been adopted instead of single-stage forming to form parts with a steep wall angle or to achieve a high forming performance, it is largely dependent on empiric...Although multi-stage incremental sheet forming has always been adopted instead of single-stage forming to form parts with a steep wall angle or to achieve a high forming performance, it is largely dependent on empirical designs. In order to research multi-stage forming further, the effect of forming stages(n) and angle interval between the two adjacent stages(Δα) on thickness distribution was investigated. Firstly, a finite element method(FEM) model of multi-stage incremental forming was established and experimentally verified. Then, based on the proposed simulation model, different strategies were adopted to form a frustum of cone with wall angle of 30° to research the thickness distribution of multi-pass forming. It is proved that the minimum thickness increases largely and the variance of sheet thickness decreases significantly as the value of n grows. Further, with the increase of Δα, the minimum thickness increases initially and then decreases, and the optimal thickness distribution is achieved with Δα of 10°.Additionally, a formula is deduced to estimate the sheet thickness after multi-stage forming and proved to be effective. And the simulation results fit well with the experimental results.展开更多
A new incremental clustering framework is presented, the basis of which is the induction as inverted deduction. Induction is inherently risky because it is not truth-preserving. If the clustering is considered as an i...A new incremental clustering framework is presented, the basis of which is the induction as inverted deduction. Induction is inherently risky because it is not truth-preserving. If the clustering is considered as an induction process, the key to build a valid clustering is to minimize the risk of clustering. From the viewpoint of modal logic, the clustering can be described as Kripke frames and Kripke models which are reflexive and symmetric. Based on the theory of modal logic, its properties can be described by system B in syntax. Thus, the risk of clustering can be calculated by the deduction relation of system B and proximity induction theorem described. Since the new proposed framework imposes no additional restrictive conditions of clustering algorithm, it is therefore a universal framework. An incremental clustering algorithm can be easily constructed by this framework from any given nonincremental clustering algorithm. The experiments show that the lower the a priori risk is, the more effective this framework is. It can be demonstrated that this framework is generally valid.展开更多
A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on （fuzzy） cross-entropy（CE）. This algorithm is di...A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on （fuzzy） cross-entropy（CE）. This algorithm is divided into two parts： initial clustering process and incremental clustering process. The former calculates fuzzy cross-entropy or cross-entropy of one point relafive to others and a hierachical method based on cross-entropy is used for clustering static data sets. Moreover, it has the lower time complexity. The latter assigns new points to the suitable cluster by calculating membership of data point to existed centers based on the cross-entropy measure. Experimental compafisons show the proposed methood has lower time complexity than common methods in the large-scale data situations cr dynamic work environments.展开更多
A pressing technique has become available that might be useful for compressing granular explosives. If the height diameter ratio of the charge is unfavorable,the high quality charge can not be obtained with the common...A pressing technique has become available that might be useful for compressing granular explosives. If the height diameter ratio of the charge is unfavorable,the high quality charge can not be obtained with the common single action pressing. This paper presents incremental pressing technique, which can obtain the charge with higher overall density and more uniform density.展开更多
社交网络中,节点间存在多种关系类型,节点数量会随着时间的推移而变化,这种异质性和动态性给链路预测任务带来极大的挑战。因此,本文提出一种基于增量学习的社交网络链路预测方法(incremental learning social networks link prediction...社交网络中,节点间存在多种关系类型,节点数量会随着时间的推移而变化,这种异质性和动态性给链路预测任务带来极大的挑战。因此,本文提出一种基于增量学习的社交网络链路预测方法(incremental learning social networks link prediction,IL-SNLP)。通过对网络进行分层,使每一层网络只包含一种关系类型,以更好地获取节点在每种关系类型下的语义信息;针对网络的动态性,利用时序随机游走捕获社交网络中的局部结构信息和时序信息;针对增量数据,采用增量式更新随机游走策略对历史随机游走序列进行更新。通过增量式skip-gram模型从随机游走序列中提取新出现节点的特征,并进一步更新历史节点的特征;针对网络的异质性,采用概率模型提取不同关系类型之间的因果关系关联程度,并将其作用于每一层的节点特征,以改善不同关系层下节点特征表现能力;利用多层感知机构建节点相互感知器,挖掘节点间建立连接时的相互贡献,实现更高的链路预测准确率。实验结果表明,在3个真实的社交网络数据集上,IL-SNLP方法的ROC曲线下的面积(AUC)和F1分数比基线方法分别提高了10.08%~67.60%和1.76%~64.67%,提升了预测性能;对于增量数据,只需要少次迭代就能保持预测模型的性能,提高了模型训练的速度;与未采用增量学习技术的IL-SNLP−方法相比,IL-SNLP方法在时间效率上提升了30.78%~257.58%,显著缩短了模型的运行时长。展开更多
文摘A method utilizing variable depth increments during incremental forming was proposed and then optimized based on numerical simulation and intelligent algorithm.Initially,a finite element method(FEM) model was set up and then experimentally verified.And the relation between depth increment and the minimum thickness tmin as well as its location was analyzed through the FEM model.Afterwards,the variation of depth increments was defined.The designed part was divided into three areas according to the main deformation mechanism,with Di(i=1,2) representing the two dividing locations.And three different values of depth increment,Δzi(i=1,2,3) were utilized for the three areas,respectively.Additionally,an orthogonal test was established to research the relation between the five process parameters(D and Δz) and tmin as well as its location.The result shows that Δz2 has the most significant influence on the thickness distribution for the corresponding area is the largest one.Finally,a single evaluating indicator,taking into account of both tmin and its location,was formatted with a linear weighted model.And the process parameters were optimized through a genetic algorithm integrated with an artificial neural network based on the evaluating index.The result shows that the proposed algorithm is satisfactory for the optimization of variable depth increment.
基金supported by the National Natural Science Foundation of China(6110420961503126)
文摘In practical applications, the system observation error is widespread. If the observation equation of the system has not been verified or corrected under certain environmental conditions,the unknown system errors and filtering errors will come into being.The incremental observation equation is derived, which can eliminate the unknown observation errors effectively. Furthermore, an incremental Kalman smoother is presented. Moreover, a weighted measurement fusion incremental Kalman smoother applying the globally optimal weighted measurement fusion algorithm is given.The simulation results show their effectiveness and feasibility.
文摘Based on the relationship among the geographic events, spatial changes and the database operations, a new automatic (semi-automatic) incremental updating approach of spatio-temporal database (STDB) named as (event-based) incremental updating (E-BIU) is proposed in this paper. At first, the relationship among the events, spatial changes and the database operations is analyzed, then a total architecture of E-BIU implementation is designed, which includes an event queue, three managers and two sets of rules, each component is presented in detail. The process of the E-BIU of master STDB is described successively. An example of building’s incremental updating is given to illustrate this approach at the end. The result shows that E-BIU is an efficient automatic updating approach for master STDB.
基金supported by the National Natural Science Key Foundation of China(69974021)
文摘A new incremental support vector machine （SVM） algorithm is proposed which is based on multiple kernel learning. Through introducing multiple kernel learning into the SVM incremental learning, large scale data set learning problem can be solved effectively. Furthermore, different punishments are adopted in allusion to the training subset and the acquired support vectors, which may help to improve the performance of SVM. Simulation results indicate that the proposed algorithm can not only solve the model selection problem in SVM incremental learning, but also improve the classification or prediction precision.
基金Project(50734007) supported by the National Natural Science Foundation of China
文摘In the non-linear microwave drying process, the incremental improved back-propagation （BP） neural network and response surface methodology （RSM） were used to build a predictive model of the combined effects of independent variables （the microwave power, the acting time and the rotational frequency） for microwave drying of selenium-rich slag. The optimum operating conditions obtained from the quadratic form of the RSM are： the microwave power of 14.97 kW, the acting time of 89.58 min, the rotational frequency of 10.94 Hz, and the temperature of 136.407 ℃. The relative dehydration rate of 97.1895% is obtained. Under the optimum operating conditions, the incremental improved BP neural network prediction model can predict the drying process results and different effects on the results of the independent variables. The verification experiments demonstrate the prediction accuracy of the network, and the mean squared error is 0.16. The optimized results indicate that RSM can optimize the experimental conditions within much more broad range by considering the combination of factors and the neural network model can predict the results effectively and provide the theoretical guidance for the follow-up production process.
基金Project(61203021)supported by the National Natural Science Foundation of ChinaProject(2011216011)supported by the Scientific and Technological Program of Liaoning Province,China+2 种基金Project(2013020024)supported by the Natural Science Foundation of Liaoning Province,ChinaProject(2012BAF05B00)supported by the National Science and Technology Support Program,ChinaProject(LJQ2015061)supported by the Program for Liaoning Excellent Talents in Universities,China
文摘The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the traditional PID control has been proven not sufficient and capable for this particular petro-chemical process.In this work,an incremental multivariable predictive functional control(IMPFC) algorithm was proposed with less online computation,great precision and fast response.An incremental transfer function matrix model was set up through the step-response data,and predictive outputs were deduced with the theory of single-value optimization.The results show that the method can optimize the incremental control variable and reject the constraint of the incremental control variable with the positional predictive functional control algorithm,and thereby making the control variable smoother.The predictive output error and future set-point were approximated by a polynomial,which can overcome the problem under the model mismatch and make the predictive outputs track the reference trajectory.Then,the design of incremental multivariable predictive functional control was studied.Simulation and application results show that the proposed control strategy is effective and feasible to improve control performance and robustness of process.
基金Project(50175034) supported by the National Natural Science Foundation of China
文摘In order to investigate the process of incremental sheet forming (ISF) through both experimental and numerical approaches, a three-dimensional elasto-plastic finite element model (FEM) was developed to simulate the process and the simulated results were compared with those of experiment. The results of numerical simulations, such as the strain history and distribution, the stress state and distribution, sheet thickness distribution, etc, were discussed in details, and the influences of process parameters on these results were also analyzed. The simulated results of the radial strain and the thickness distribution are in good agreement with experimental results. The simulations reveal that the deformation is localized around the tool and constantly remains close to a plane strain state. With decreasing depth step, increasing tool diameter and wall inclination angle, the axial stress reduces, leading to less thinning and more homogeneous plastic strain and thickness distribution. During ISF, the plastic strain increases stepwise under the action of the tool. Each increase in plastic strain is accompanied by hydrostatic pressure, which explains why obtainable deformation using ISF exceeds the forming limits of conventional sheet forming.
文摘Path planning of a mobile robot in the presence of multiple moving obstacles is found to be a complicated problem.A planning algorithm capable of negotiating both static and moving obstacles in an unpredictable(on-line)environment is proposed.The proposed incremental algorithm plans the path by considering the quadrants in which the current positions of obstacles as well as target are situated.Also,the governing equations for the shortest path are derived.The proposed mathematical model describes the motion(satisfying constraints of the mobile robot)along a collision-free path.Further,the algorithm is applicable to dynamic environments with fixed or moving targets.Simulation results show the effectiveness of the proposed algorithm.Comparison of results with the improved artificial potential field(iAPF)algorithm shows that the proposed algorithm yields shorter path length with less computation time.
基金Project(50078006) supported by the National Natural Science Foundation of China project ( 2001G029+1 种基金 2003G043)supported by the Foundation of the Science and Technology Section of the Railway Bureau of China project (2001053300
文摘The criteria for evaluation of train derailment were studied. The worldwide commonly used evaluation criteria for wheel derailment were summarized and their main problems were pointed out. The mechanism of train derailment was expounded on the basis of system dynamics stability concept. And the energy increment criteria were proposed to evaluate train derailment. By applying the criteria, the calculated results concerning 6 cases of freight train derailment on tangent railway line and 6 cases of freight train derailment on bridge were obtained, which are all in agreement with the practical situation. The safety, comfort and stability results concerning 3 cases of freight train running on bridge were analyzed. In addition, the running speed limits of freight train on the Yanconggou and Donggou bridge in the Beijing-Tonghua railway line of 50km/h and 60km/h, respectively, were proposed. And the running speed of freight train on the Nanjing Yangtze River Bridge can reach 70km/h.
文摘In this present paper, a deterministic lot size model is developed for deteriorating items with incremental quantity discounts. It is assumed that shortages are permitted to occur and fully backlogged. A simple solution procedure is shown for determining the optimal order lot size and the optimal order cycle. A numerical example is used to illustrate how the solution procedure works.
基金This project was supported by Spaceflight Support Fund ( HIT01) and the Spaceflight Science Project Group
文摘The scheme for tracking maneuvering target based on neural fuzzy network with incremental neural learning is proposed. When tracked target maneuver occurs, the scheme can detect maneuver immediately and estimate the maneuver value accurately , then the tracking filter can be compensated correctly and duly by the estimated maneuver value. When environment changes, neural fuzzy network with incremental neural learning （INL-SONFIN） can find its optimal structure and parameters automatically to adopt to changed environment. So, it always produce estimated output very close to the true maneuver value that leads to good tracking performance and avoids misstracking. Simulation results show that the performance is superior to the traditional schemes and the scheme can fit changed dynamic environment to track maneuvering target accurately and duly.
基金Project(50175034) supported by the National Natural Science Foundation of China
文摘The closed loop control model was built up for compensating the springback and enhancing the work piece precision.A coupled closed loop algorithm and a finite element method were developed to simulate and correct the springback of incremental sheet forming.A three-dimensional finite element model was established for simulation of springback in incremental sheet forming process.The closed loop algorithm of trajectory profile for the incremental sheet forming based on the wavelet transform combined with fast Fourier transform was constructed.The profile of processing tool path of shallow dishing with spherical surface was designed on the basis of the profile correction algorithm.The result shows that the algorithm can predict an ideal profile of processing track,and the springback error of incremental sheet forming is eliminated effectively.It has good convergence efficiency,and can improve the workpiece dimensional accuracy greatly.
基金Project(51005258) supported by the National Natural Science Foundation of ChinaProject(CDJZR12130065) supported by the Fundamental Research Funds for the Central Universities,China
文摘Although multi-stage incremental sheet forming has always been adopted instead of single-stage forming to form parts with a steep wall angle or to achieve a high forming performance, it is largely dependent on empirical designs. In order to research multi-stage forming further, the effect of forming stages(n) and angle interval between the two adjacent stages(Δα) on thickness distribution was investigated. Firstly, a finite element method(FEM) model of multi-stage incremental forming was established and experimentally verified. Then, based on the proposed simulation model, different strategies were adopted to form a frustum of cone with wall angle of 30° to research the thickness distribution of multi-pass forming. It is proved that the minimum thickness increases largely and the variance of sheet thickness decreases significantly as the value of n grows. Further, with the increase of Δα, the minimum thickness increases initially and then decreases, and the optimal thickness distribution is achieved with Δα of 10°.Additionally, a formula is deduced to estimate the sheet thickness after multi-stage forming and proved to be effective. And the simulation results fit well with the experimental results.
基金supported by the National High-Tech Research and Development Program of China(2006AA12A106).
文摘A new incremental clustering framework is presented, the basis of which is the induction as inverted deduction. Induction is inherently risky because it is not truth-preserving. If the clustering is considered as an induction process, the key to build a valid clustering is to minimize the risk of clustering. From the viewpoint of modal logic, the clustering can be described as Kripke frames and Kripke models which are reflexive and symmetric. Based on the theory of modal logic, its properties can be described by system B in syntax. Thus, the risk of clustering can be calculated by the deduction relation of system B and proximity induction theorem described. Since the new proposed framework imposes no additional restrictive conditions of clustering algorithm, it is therefore a universal framework. An incremental clustering algorithm can be easily constructed by this framework from any given nonincremental clustering algorithm. The experiments show that the lower the a priori risk is, the more effective this framework is. It can be demonstrated that this framework is generally valid.
文摘A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on （fuzzy） cross-entropy（CE）. This algorithm is divided into two parts： initial clustering process and incremental clustering process. The former calculates fuzzy cross-entropy or cross-entropy of one point relafive to others and a hierachical method based on cross-entropy is used for clustering static data sets. Moreover, it has the lower time complexity. The latter assigns new points to the suitable cluster by calculating membership of data point to existed centers based on the cross-entropy measure. Experimental compafisons show the proposed methood has lower time complexity than common methods in the large-scale data situations cr dynamic work environments.
文摘A pressing technique has become available that might be useful for compressing granular explosives. If the height diameter ratio of the charge is unfavorable,the high quality charge can not be obtained with the common single action pressing. This paper presents incremental pressing technique, which can obtain the charge with higher overall density and more uniform density.
文摘社交网络中,节点间存在多种关系类型,节点数量会随着时间的推移而变化,这种异质性和动态性给链路预测任务带来极大的挑战。因此,本文提出一种基于增量学习的社交网络链路预测方法(incremental learning social networks link prediction,IL-SNLP)。通过对网络进行分层,使每一层网络只包含一种关系类型,以更好地获取节点在每种关系类型下的语义信息;针对网络的动态性,利用时序随机游走捕获社交网络中的局部结构信息和时序信息;针对增量数据,采用增量式更新随机游走策略对历史随机游走序列进行更新。通过增量式skip-gram模型从随机游走序列中提取新出现节点的特征,并进一步更新历史节点的特征;针对网络的异质性,采用概率模型提取不同关系类型之间的因果关系关联程度,并将其作用于每一层的节点特征,以改善不同关系层下节点特征表现能力;利用多层感知机构建节点相互感知器,挖掘节点间建立连接时的相互贡献,实现更高的链路预测准确率。实验结果表明,在3个真实的社交网络数据集上,IL-SNLP方法的ROC曲线下的面积(AUC)和F1分数比基线方法分别提高了10.08%~67.60%和1.76%~64.67%,提升了预测性能;对于增量数据,只需要少次迭代就能保持预测模型的性能,提高了模型训练的速度;与未采用增量学习技术的IL-SNLP−方法相比,IL-SNLP方法在时间效率上提升了30.78%~257.58%,显著缩短了模型的运行时长。
