When multiple LCC-HVDC transmission lines are densely fed into a receiving AC system,voltage dips can easily propagate in the power system,resulting in multiple LCC commutation failures simultaneously.The VSC-HVDC can...When multiple LCC-HVDC transmission lines are densely fed into a receiving AC system,voltage dips can easily propagate in the power system,resulting in multiple LCC commutation failures simultaneously.The VSC-HVDC can be used to divide the receiving sys-tem into several interconnected sub-partitions and improve the voltage support capability of the receiving system.Compared with asyn-chronous interconnection,which completely separates the receiving systems with VSC-HVDC,incomplete segmentation with an AC connection is a more pertinent segmenting method for multilayer complex regional power grids.To analyze the voltage support capability of the VSC in incomplete segmentation,a micro-incremental model of the VSC was established,the operating impedance of the VSC was calculated,and the voltage support function of the VSC was quantified.The effect of the fault on the system short-circuit capacity was analyzed,and a calculation method for the multi-infeed short-circuit ratio in an incompletely segmented scenario was obtained.A VSC-segmented model of a two-infeed DC system was built on the EMTDC/PSCAD simulation platform,and the validity of the micro-increment model and accuracy of the proposed conclusions were verified.展开更多
In functional data analysis,the collected data are often assumed to be fully observed on the domain.However,in dealing with real data(for example,environmental pollution data),we are often faced with the scenario that...In functional data analysis,the collected data are often assumed to be fully observed on the domain.However,in dealing with real data(for example,environmental pollution data),we are often faced with the scenario that some functional data are fully observed on dense lattice while others are incompletely observed.In this paper,we propose a method for testing equivalence of mean functions of two samples under this scenario.Some asymptotic results of the proposed methods are established.The proposed test is employed to analyze an environmental pollution study in Liuzhou City of China.Simulations show that the proposed test has a good control of the type-I error,and is more powerful than the complete case test in most cases.展开更多
This paper presents a method for state simplification in incompletely specified sequential machines. The new method adopts Inclusive-OR operation of column vectors for multi-level output matrix E_k! Compared with othe...This paper presents a method for state simplification in incompletely specified sequential machines. The new method adopts Inclusive-OR operation of column vectors for multi-level output matrix E_k! Compared with other algorithms in use, this method is theoretically more strict, while its structure is simple and the results obtained are accurate.展开更多
Objective:To compare the clinical efficacy of mifepristone-misoprostol medical management versus surgical curettage for first-trimester missed miscarriage,and to establish evidence-based sonographic cutoff values pred...Objective:To compare the clinical efficacy of mifepristone-misoprostol medical management versus surgical curettage for first-trimester missed miscarriage,and to establish evidence-based sonographic cutoff values predictive of incomplete abortion requiring surgical intervention.Methods:We retrospectively analyzed a cohort of 702 women diagnosed with first-trimester missed miscarriage between January 2020 and May 2023.Demographic characteristics and ultrasound parameters were systematically recorded.Receiver operating characteristic(ROC)curve analysis was performed to establish optimal sonographic cutoff values for predicting incomplete abortion requiring surgical intervention.Results:146 patients received medical treatment(mifepristone and misoprostol)and 556 underwent surgical curettage.At the 1-month follow-up,the medical group showed significantly greater endometrial thickness and longer postoperative bleeding duration than the surgical group(P<0.05).The menstrual volume reduction rate(23.56%)was significantly lower in the medical group than in the surgical group.The incomplete abortion rate was higher in the medical group(17.12%,25/146)than in the surgical group(2.88%,16/556).Among the medical group,14 patients(9.59%)required curettage due to incomplete abortion,while 11 cases resolved spontaneously after prolonged medication.ROC curve analysis identified two cut-off values indicating the need for surgical intervention:endometrial thickness>1.21 cm at 24 h post-medical abortion,and residual mass diameter>0.95 cm at 7 days post-medical abortion.Conclusions:Medical management of first-trimester missed miscarriage using mifepristone-misoprostol demonstrates comparable efficacy to surgical curettage.An endometrial thickness>1.21 cm at 24 h or residual tissue diameter>0.95 cm at 7 days post-medical abortion should prompt consideration of incomplete abortion.展开更多
Asia’s unhealed wounds and incomplete justice of WWII.WHILE Europe commemorated Nazi Germany’s defeat during the World War II in May 1945,few acknowledged that the war raged on for several more months in Asia,claimi...Asia’s unhealed wounds and incomplete justice of WWII.WHILE Europe commemorated Nazi Germany’s defeat during the World War II in May 1945,few acknowledged that the war raged on for several more months in Asia,claiming millions more lives before Japan officially signed the instrument of surrender on September 2,1945.展开更多
The widespread usage of rechargeable batteries in portable devices,electric vehicles,and energy storage systems has underscored the importance for accurately predicting their lifetimes.However,data scarcity often limi...The widespread usage of rechargeable batteries in portable devices,electric vehicles,and energy storage systems has underscored the importance for accurately predicting their lifetimes.However,data scarcity often limits the accuracy of prediction models,which is escalated by the incompletion of data induced by the issues such as sensor failures.To address these challenges,we propose a novel approach to accommodate data insufficiency through achieving external information from incomplete data samples,which are usually discarded in existing studies.In order to fully unleash the prediction power of incomplete data,we have investigated the Multiple Imputation by Chained Equations(MICE)method that diversifies the training data through exploring the potential data patterns.The experimental results demonstrate that the proposed method significantly outperforms the baselines in the most considered scenarios while reducing the prediction root mean square error(RMSE)by up to 18.9%.Furthermore,we have also observed that the penetration of incomplete data benefits the explainability of the prediction model through facilitating the feature selection.展开更多
High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelations...High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelationships among intricate variable patterns.Accordingly,this study proposes a Mogrifier gate recurrent unit-D(Mog-GRU-D)model to address the com-bat target intention prediction issue under the incomplete infor-mation condition.The proposed model directly processes miss-ing data while reducing the independence between inputs and output states.A total of 1200 samples from twelve continuous moments are captured through the combat simulation system,each of which consists of seven dimensional features.To bench-mark the experiment,a missing valued dataset has been gener-ated by randomly removing 20%of the original data.Extensive experiments demonstrate that the proposed model obtains the state-of-the-art performance with an accuracy of 73.25%when dealing with incomplete information.This study provides possi-ble interpretations for the principle of target interactive mecha-nism,highlighting the model’s effectiveness in potential air war-fare implementation.展开更多
The accurate identification and diagnosis of chemical process faults are crucial for ensuring the safe and stable operation of production plants.The current hot topic in industrial process fault diagnosis research is ...The accurate identification and diagnosis of chemical process faults are crucial for ensuring the safe and stable operation of production plants.The current hot topic in industrial process fault diagnosis research is data-driven methods.Most of the existing fault diagnosis methods focus on a single shallow or deep learning model.This paper proposes a novel hybrid fault diagnosis method to fully utilize various features to improve the accuracy of fault diagnosis.Furthermore,the method addresses the issue of incomplete data,which has been largely overlooked in the majority of existing research.Firstly,the variable data is effectively fitted using orthogonal non-negative matrix tri-factorization,and the missing data in the matrix is solved to construct a complete production condition relationship.Next,the support vector machine model and the deep residual contraction network model are trained in parallel to prediagnose process faults by mining linear and non-linear interaction features.Finally,a novel mapping relationship is established between the result and model levels using the multi-layer perceptron algorithm to complete the final diagnosis and evaluation of the fault.To demonstrate the effectiveness of the proposed method,we conducted extensive comparative experiments on the Tennessee Eastman dataset and the ethylene plant cracking unit dataset.The experimental results show that the method has advantages in different evaluation metrics.展开更多
Post-colonoscopic colorectal cancer(PCCRC),also known as interval CRC,is defined as CRC diagnosed more than six months after a colonoscopy in which no cancer was detected.It typically arises from missed lesions or inc...Post-colonoscopic colorectal cancer(PCCRC),also known as interval CRC,is defined as CRC diagnosed more than six months after a colonoscopy in which no cancer was detected.It typically arises from missed lesions or incomplete resections and is now recognized as one of the most reliable quality indicators for assessing colonoscopy performance.With an incidence rate of 3.6%to 9.3%,PCCRC remains a significant concern,highlighting the limitations of colonoscopy in CRC screening—not only in terms of diagnostic accuracy but also in its preventive role and effectiveness in treating lesions.A range of clinical,endoscopic,and biological factors has been associated with an increased risk of PCCRC.Identifying these factors can help stratify high-risk patients,enabling earlier detection and improving preventive strategies for interval CRC.Reducing PCCRC should be a top priority for every endoscopy unit.While technological advancements will enhance polyp detection,minimize missed lesions,prevent incomplete resections,and improve overall procedural quality,the most impactful strategy remains internal self-assessment within each unit.This review should evaluate key performance metrics,including cecal intubation rate,adenoma detection rate,withdrawal time,PCCRC incidence,and incomplete resections—both at the individual endoscopist level and across the entire unit.展开更多
In this paper,a distributed adaptive dynamic programming(ADP)framework based on value iteration is proposed for multi-player differential games.In the game setting,players have no access to the information of others&#...In this paper,a distributed adaptive dynamic programming(ADP)framework based on value iteration is proposed for multi-player differential games.In the game setting,players have no access to the information of others'system parameters or control laws.Each player adopts an on-policy value iteration algorithm as the basic learning framework.To deal with the incomplete information structure,players collect a period of system trajectory data to compensate for the lack of information.The policy updating step is implemented by a nonlinear optimization problem aiming to search for the proximal admissible policy.Theoretical analysis shows that by adopting proximal policy searching rules,the approximated policies can converge to a neighborhood of equilibrium policies.The efficacy of our method is illustrated by three examples,which also demonstrate that the proposed method can accelerate the learning process compared with the centralized learning framework.展开更多
Dear Editor,This letter presents a novel latent factorization model for high dimensional and incomplete (HDI) tensor, namely the neural Tucker factorization (Neu Tuc F), which is a generic neural network-based latent-...Dear Editor,This letter presents a novel latent factorization model for high dimensional and incomplete (HDI) tensor, namely the neural Tucker factorization (Neu Tuc F), which is a generic neural network-based latent-factorization-of-tensors model under the Tucker decomposition framework.展开更多
A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black backg...A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.展开更多
A thorough investigation was carried out to the pond resources of a county, and Grossman-Hart-Moore （GHM） incomplete contract theory was used to do the economic analysis on the idle pond resources. The result indica...A thorough investigation was carried out to the pond resources of a county, and Grossman-Hart-Moore （GHM） incomplete contract theory was used to do the economic analysis on the idle pond resources. The result indicated that with the deepening of market-oriented economy, the human asset specificity under the incomplete contract had distorted the investment incentives to the governance of ponds that corresponding policies were required to govern the idle ponds.展开更多
The tetrameric neodymium-silsesquioxane cage complex,{[(i-C_4H_9)_7(Si_7O_(12))Nd])4NaCl},was prepared and used as precursor for the polymerization of isoprene.When activated by AlEt_3 in the presence of TMSCl,this PO...The tetrameric neodymium-silsesquioxane cage complex,{[(i-C_4H_9)_7(Si_7O_(12))Nd])4NaCl},was prepared and used as precursor for the polymerization of isoprene.When activated by AlEt_3 in the presence of TMSCl,this POSS-Nd complex (POSS=polyhedral oligomeric silsesquioxane) shows a moderate activity for the polymerization,and the effects of different ratios of Al/Nd,Cl/Nd and time on the polymerization were investigated.Moreover,The POSS-Nd complex may serve as models for the silica-supported rare earth cat...展开更多
A new favorable iterative algorithm named as PBiCGSTAB （preconditioned bi-conjugate gradient stabilized） algorithm is presented for solving large sparse complex systems. Based on the orthogonal list, the special tec...A new favorable iterative algorithm named as PBiCGSTAB （preconditioned bi-conjugate gradient stabilized） algorithm is presented for solving large sparse complex systems. Based on the orthogonal list, the special technique of only storing non-zero elements is carried out. The incomplete LU factorization without fill-ins is adopted to reduce the condition number of the coefficient matrix. The BiCGSTAB algorithm is extended from the real system to the complex system and it is used to solve the preconditioned complex linear equations. The locked-rotor state of a single-sided linear induction machine is simulated by the software programmed with the finite element method and the PBiCGSTAB algorithm. Then the results are compared with those from the commercial software ANSYS, showing the validation of the proposed software. The iterative steps required for the proposed algorithm are reduced to about one-third, when compared to the BiCG method, therefore the algorithm is fast.展开更多
To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID co...To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID controller. To overcome the disadvantages of the integral performance criteria in the frequency domain such as IAE, ISE, and ITSE, a new performance criterion in the time domain is proposed. The optimization procedures employing the DE algorithm to search the optimal or near optimal PID controller parameters of a control system are demonstrated in detail. Three typical control systems are chosen to test and evaluate the adaptation and robustness of the proposed DE-PID controller. The simulation results show that the proposed approach has superior features of easy implementation, stable convergence characteristic, and good computational efficiency. Compared with the ZN, GA, and ASA, the proposed design method is indeed more efficient and robust in improving the step response of a control system.展开更多
For the fault detection and diagnosis problem in largescale industrial systems, there are two important issues： the missing data samples and the non-Gaussian property of the data. However, most of the existing data-d...For the fault detection and diagnosis problem in largescale industrial systems, there are two important issues： the missing data samples and the non-Gaussian property of the data. However, most of the existing data-driven methods cannot be able to handle both of them. Thus, a new Bayesian network classifier based fault detection and diagnosis method is proposed. At first, a non-imputation method is presented to handle the data incomplete samples, with the property of the proposed Bayesian network classifier, and the missing values can be marginalized in an elegant manner. Furthermore, the Gaussian mixture model is used to approximate the non-Gaussian data with a linear combination of finite Gaussian mixtures, so that the Bayesian network can process the non-Gaussian data in an effective way. Therefore, the entire fault detection and diagnosis method can deal with the high-dimensional incomplete process samples in an efficient and robust way. The diagnosis results are expressed in the manner of probability with the reliability scores. The proposed approach is evaluated with a benchmark problem called the Tennessee Eastman process. The simulation results show the effectiveness and robustness of the proposed method in fault detection and diagnosis for large-scale systems with missing measurements.展开更多
This paper conducts a survey on iterative learn-ing control(ILC)with incomplete information and associated control system design,which is a frontier of the ILC field.The incomplete information,including passive and ac...This paper conducts a survey on iterative learn-ing control(ILC)with incomplete information and associated control system design,which is a frontier of the ILC field.The incomplete information,including passive and active types,can cause data loss or fragment due to various factors.Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection,storage,transmission,and processing,such as data dropouts,delays,disordering,and limited transmission bandwidth.Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied,such as sampling and quantization.This survey emphasizes two aspects:the first one is how to guarantee good learning performance and tracking performance with passive incomplete data,and the second is how to balance the control performance index and data demand by active means.The promising research directions along this topic are also addressed,where data robustness is highly emphasized.This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance,quantitatively,and promote further developments of ILC theory.展开更多
基金supported by the State Grid Science and Technology Project 5108-202218280A-2-87-XG.
文摘When multiple LCC-HVDC transmission lines are densely fed into a receiving AC system,voltage dips can easily propagate in the power system,resulting in multiple LCC commutation failures simultaneously.The VSC-HVDC can be used to divide the receiving sys-tem into several interconnected sub-partitions and improve the voltage support capability of the receiving system.Compared with asyn-chronous interconnection,which completely separates the receiving systems with VSC-HVDC,incomplete segmentation with an AC connection is a more pertinent segmenting method for multilayer complex regional power grids.To analyze the voltage support capability of the VSC in incomplete segmentation,a micro-incremental model of the VSC was established,the operating impedance of the VSC was calculated,and the voltage support function of the VSC was quantified.The effect of the fault on the system short-circuit capacity was analyzed,and a calculation method for the multi-infeed short-circuit ratio in an incompletely segmented scenario was obtained.A VSC-segmented model of a two-infeed DC system was built on the EMTDC/PSCAD simulation platform,and the validity of the micro-increment model and accuracy of the proposed conclusions were verified.
基金supported by National Natural Science Foundation of China(11561006,11861014)Natural Science Foundation of Guangxi(2018GXNSFAA281145)Social Science Foundation Project of Jilin for Doctoral and Youth Support(2019c24).
文摘In functional data analysis,the collected data are often assumed to be fully observed on the domain.However,in dealing with real data(for example,environmental pollution data),we are often faced with the scenario that some functional data are fully observed on dense lattice while others are incompletely observed.In this paper,we propose a method for testing equivalence of mean functions of two samples under this scenario.Some asymptotic results of the proposed methods are established.The proposed test is employed to analyze an environmental pollution study in Liuzhou City of China.Simulations show that the proposed test has a good control of the type-I error,and is more powerful than the complete case test in most cases.
文摘This paper presents a method for state simplification in incompletely specified sequential machines. The new method adopts Inclusive-OR operation of column vectors for multi-level output matrix E_k! Compared with other algorithms in use, this method is theoretically more strict, while its structure is simple and the results obtained are accurate.
基金supported by National Natural Science Foundation of China(Project approval number 82201825).
文摘Objective:To compare the clinical efficacy of mifepristone-misoprostol medical management versus surgical curettage for first-trimester missed miscarriage,and to establish evidence-based sonographic cutoff values predictive of incomplete abortion requiring surgical intervention.Methods:We retrospectively analyzed a cohort of 702 women diagnosed with first-trimester missed miscarriage between January 2020 and May 2023.Demographic characteristics and ultrasound parameters were systematically recorded.Receiver operating characteristic(ROC)curve analysis was performed to establish optimal sonographic cutoff values for predicting incomplete abortion requiring surgical intervention.Results:146 patients received medical treatment(mifepristone and misoprostol)and 556 underwent surgical curettage.At the 1-month follow-up,the medical group showed significantly greater endometrial thickness and longer postoperative bleeding duration than the surgical group(P<0.05).The menstrual volume reduction rate(23.56%)was significantly lower in the medical group than in the surgical group.The incomplete abortion rate was higher in the medical group(17.12%,25/146)than in the surgical group(2.88%,16/556).Among the medical group,14 patients(9.59%)required curettage due to incomplete abortion,while 11 cases resolved spontaneously after prolonged medication.ROC curve analysis identified two cut-off values indicating the need for surgical intervention:endometrial thickness>1.21 cm at 24 h post-medical abortion,and residual mass diameter>0.95 cm at 7 days post-medical abortion.Conclusions:Medical management of first-trimester missed miscarriage using mifepristone-misoprostol demonstrates comparable efficacy to surgical curettage.An endometrial thickness>1.21 cm at 24 h or residual tissue diameter>0.95 cm at 7 days post-medical abortion should prompt consideration of incomplete abortion.
文摘Asia’s unhealed wounds and incomplete justice of WWII.WHILE Europe commemorated Nazi Germany’s defeat during the World War II in May 1945,few acknowledged that the war raged on for several more months in Asia,claiming millions more lives before Japan officially signed the instrument of surrender on September 2,1945.
文摘The widespread usage of rechargeable batteries in portable devices,electric vehicles,and energy storage systems has underscored the importance for accurately predicting their lifetimes.However,data scarcity often limits the accuracy of prediction models,which is escalated by the incompletion of data induced by the issues such as sensor failures.To address these challenges,we propose a novel approach to accommodate data insufficiency through achieving external information from incomplete data samples,which are usually discarded in existing studies.In order to fully unleash the prediction power of incomplete data,we have investigated the Multiple Imputation by Chained Equations(MICE)method that diversifies the training data through exploring the potential data patterns.The experimental results demonstrate that the proposed method significantly outperforms the baselines in the most considered scenarios while reducing the prediction root mean square error(RMSE)by up to 18.9%.Furthermore,we have also observed that the penetration of incomplete data benefits the explainability of the prediction model through facilitating the feature selection.
基金supported by the Aeronautical Science Foundation of China(2020Z023053002).
文摘High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelationships among intricate variable patterns.Accordingly,this study proposes a Mogrifier gate recurrent unit-D(Mog-GRU-D)model to address the com-bat target intention prediction issue under the incomplete infor-mation condition.The proposed model directly processes miss-ing data while reducing the independence between inputs and output states.A total of 1200 samples from twelve continuous moments are captured through the combat simulation system,each of which consists of seven dimensional features.To bench-mark the experiment,a missing valued dataset has been gener-ated by randomly removing 20%of the original data.Extensive experiments demonstrate that the proposed model obtains the state-of-the-art performance with an accuracy of 73.25%when dealing with incomplete information.This study provides possi-ble interpretations for the principle of target interactive mecha-nism,highlighting the model’s effectiveness in potential air war-fare implementation.
文摘The accurate identification and diagnosis of chemical process faults are crucial for ensuring the safe and stable operation of production plants.The current hot topic in industrial process fault diagnosis research is data-driven methods.Most of the existing fault diagnosis methods focus on a single shallow or deep learning model.This paper proposes a novel hybrid fault diagnosis method to fully utilize various features to improve the accuracy of fault diagnosis.Furthermore,the method addresses the issue of incomplete data,which has been largely overlooked in the majority of existing research.Firstly,the variable data is effectively fitted using orthogonal non-negative matrix tri-factorization,and the missing data in the matrix is solved to construct a complete production condition relationship.Next,the support vector machine model and the deep residual contraction network model are trained in parallel to prediagnose process faults by mining linear and non-linear interaction features.Finally,a novel mapping relationship is established between the result and model levels using the multi-layer perceptron algorithm to complete the final diagnosis and evaluation of the fault.To demonstrate the effectiveness of the proposed method,we conducted extensive comparative experiments on the Tennessee Eastman dataset and the ethylene plant cracking unit dataset.The experimental results show that the method has advantages in different evaluation metrics.
文摘Post-colonoscopic colorectal cancer(PCCRC),also known as interval CRC,is defined as CRC diagnosed more than six months after a colonoscopy in which no cancer was detected.It typically arises from missed lesions or incomplete resections and is now recognized as one of the most reliable quality indicators for assessing colonoscopy performance.With an incidence rate of 3.6%to 9.3%,PCCRC remains a significant concern,highlighting the limitations of colonoscopy in CRC screening—not only in terms of diagnostic accuracy but also in its preventive role and effectiveness in treating lesions.A range of clinical,endoscopic,and biological factors has been associated with an increased risk of PCCRC.Identifying these factors can help stratify high-risk patients,enabling earlier detection and improving preventive strategies for interval CRC.Reducing PCCRC should be a top priority for every endoscopy unit.While technological advancements will enhance polyp detection,minimize missed lesions,prevent incomplete resections,and improve overall procedural quality,the most impactful strategy remains internal self-assessment within each unit.This review should evaluate key performance metrics,including cecal intubation rate,adenoma detection rate,withdrawal time,PCCRC incidence,and incomplete resections—both at the individual endoscopist level and across the entire unit.
基金supported by the Aeronautical Science Foundation of China(20220001057001)an Open Project of the National Key Laboratory of Air-based Information Perception and Fusion(202437)
文摘In this paper,a distributed adaptive dynamic programming(ADP)framework based on value iteration is proposed for multi-player differential games.In the game setting,players have no access to the information of others'system parameters or control laws.Each player adopts an on-policy value iteration algorithm as the basic learning framework.To deal with the incomplete information structure,players collect a period of system trajectory data to compensate for the lack of information.The policy updating step is implemented by a nonlinear optimization problem aiming to search for the proximal admissible policy.Theoretical analysis shows that by adopting proximal policy searching rules,the approximated policies can converge to a neighborhood of equilibrium policies.The efficacy of our method is illustrated by three examples,which also demonstrate that the proposed method can accelerate the learning process compared with the centralized learning framework.
基金supported by the National Natural Science Foundation of China(62272078)Chongqing Natural Science Foundation(CSTB2023NSCQ-LZX0069)the Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN202300210)
文摘Dear Editor,This letter presents a novel latent factorization model for high dimensional and incomplete (HDI) tensor, namely the neural Tucker factorization (Neu Tuc F), which is a generic neural network-based latent-factorization-of-tensors model under the Tucker decomposition framework.
基金Project supported by the National Natural Science Foundation ofChina (No. 60008001) and the Natural Science Foundation of Zhe-jiang Province (No. 300297), China
文摘A machine vision system was developed to inspect the quality of rice seeds. Five varieties of Jinyou402, Shanyou10, Zhongyou207, Jiayou and IIyou were evaluated. The images of both sides of rice seed with black background and white background were acquired with the image processing system for identifying external features of rice seeds. Five image sets consisting of 600 original images each were obtained. Then a digital image processing algorithm based on Hough transform was developed to inspect the rice seeds with incompletely closed glumes. The algorithm was implemented with all image sets using a Matlab 6.5 procedure. The results showed that the algorithm achieved an average accuracy of 96% for normal seeds, 92% for seeds with fine fissure and 87% for seeds with incompletely closed glumes. The algorithm was proved to be applicable to different seed varieties and insensitive to the color of the background.
基金Supported by the Key Interdisciplinary Studies on "Resources,Environment and Recycling Economy" of Beijing,China (033000541212002)~~
文摘A thorough investigation was carried out to the pond resources of a county, and Grossman-Hart-Moore （GHM） incomplete contract theory was used to do the economic analysis on the idle pond resources. The result indicated that with the deepening of market-oriented economy, the human asset specificity under the incomplete contract had distorted the investment incentives to the governance of ponds that corresponding policies were required to govern the idle ponds.
基金supported by the National Natural Science Foundation(No.20674071)the Special Funds for MajorState Basic Research Projects(No.2005CB623802).
文摘The tetrameric neodymium-silsesquioxane cage complex,{[(i-C_4H_9)_7(Si_7O_(12))Nd])4NaCl},was prepared and used as precursor for the polymerization of isoprene.When activated by AlEt_3 in the presence of TMSCl,this POSS-Nd complex (POSS=polyhedral oligomeric silsesquioxane) shows a moderate activity for the polymerization,and the effects of different ratios of Al/Nd,Cl/Nd and time on the polymerization were investigated.Moreover,The POSS-Nd complex may serve as models for the silica-supported rare earth cat...
文摘A new favorable iterative algorithm named as PBiCGSTAB （preconditioned bi-conjugate gradient stabilized） algorithm is presented for solving large sparse complex systems. Based on the orthogonal list, the special technique of only storing non-zero elements is carried out. The incomplete LU factorization without fill-ins is adopted to reduce the condition number of the coefficient matrix. The BiCGSTAB algorithm is extended from the real system to the complex system and it is used to solve the preconditioned complex linear equations. The locked-rotor state of a single-sided linear induction machine is simulated by the software programmed with the finite element method and the PBiCGSTAB algorithm. Then the results are compared with those from the commercial software ANSYS, showing the validation of the proposed software. The iterative steps required for the proposed algorithm are reduced to about one-third, when compared to the BiCG method, therefore the algorithm is fast.
基金the National Natural Science Foundation of China (60375001)the Scientific Research Foundation of Hunan Provincial Education Department (05B016).
文摘To determine the optimal or near optimal parameters of PID controller with incomplete derivation, a novel design method based on differential evolution （DE） algorithm is presented. The controller is called DE-PID controller. To overcome the disadvantages of the integral performance criteria in the frequency domain such as IAE, ISE, and ITSE, a new performance criterion in the time domain is proposed. The optimization procedures employing the DE algorithm to search the optimal or near optimal PID controller parameters of a control system are demonstrated in detail. Three typical control systems are chosen to test and evaluate the adaptation and robustness of the proposed DE-PID controller. The simulation results show that the proposed approach has superior features of easy implementation, stable convergence characteristic, and good computational efficiency. Compared with the ZN, GA, and ASA, the proposed design method is indeed more efficient and robust in improving the step response of a control system.
基金supported by the National Natural Science Foundation of China(61202473)the Fundamental Research Funds for Central Universities(JUSRP111A49)+1 种基金"111 Project"(B12018)the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘For the fault detection and diagnosis problem in largescale industrial systems, there are two important issues： the missing data samples and the non-Gaussian property of the data. However, most of the existing data-driven methods cannot be able to handle both of them. Thus, a new Bayesian network classifier based fault detection and diagnosis method is proposed. At first, a non-imputation method is presented to handle the data incomplete samples, with the property of the proposed Bayesian network classifier, and the missing values can be marginalized in an elegant manner. Furthermore, the Gaussian mixture model is used to approximate the non-Gaussian data with a linear combination of finite Gaussian mixtures, so that the Bayesian network can process the non-Gaussian data in an effective way. Therefore, the entire fault detection and diagnosis method can deal with the high-dimensional incomplete process samples in an efficient and robust way. The diagnosis results are expressed in the manner of probability with the reliability scores. The proposed approach is evaluated with a benchmark problem called the Tennessee Eastman process. The simulation results show the effectiveness and robustness of the proposed method in fault detection and diagnosis for large-scale systems with missing measurements.
基金supported by the National Natural Science Foundation of China(61673045)Beijing Natural Science Foundation(4152040)
文摘This paper conducts a survey on iterative learn-ing control(ILC)with incomplete information and associated control system design,which is a frontier of the ILC field.The incomplete information,including passive and active types,can cause data loss or fragment due to various factors.Passive incomplete information refers to incomplete data and information caused by practical system limitations during data collection,storage,transmission,and processing,such as data dropouts,delays,disordering,and limited transmission bandwidth.Active incomplete information refers to incomplete data and information caused by man-made reduction of data quantity and quality on the premise that the given objective is satisfied,such as sampling and quantization.This survey emphasizes two aspects:the first one is how to guarantee good learning performance and tracking performance with passive incomplete data,and the second is how to balance the control performance index and data demand by active means.The promising research directions along this topic are also addressed,where data robustness is highly emphasized.This survey is expected to improve understanding of the restrictive relationship and trade-off between incomplete data and tracking performance,quantitatively,and promote further developments of ILC theory.
