The accurate estimation of lithium battery state of health(SOH)plays an important role in the health management of battery systems.In order to improve the prediction accuracy of SOH,this paper proposes a stochastic co...The accurate estimation of lithium battery state of health(SOH)plays an important role in the health management of battery systems.In order to improve the prediction accuracy of SOH,this paper proposes a stochastic configuration network based on a multi-converged black-winged kite search algorithm,called SBKA-CLSCN.Firstly,the indirect health index(HI)of the battery is extracted by combining it with Person correlation coefficients in the battery charging and discharging cycle point data.Secondly,to address the problem that the black-winged kite optimization algorithm(BKA)falls into the local optimum problem and improve the convergence speed,the Sine chaotic black-winged kite search algorithm(SBKA)is designed,which mainly utilizes the Sine mapping and the golden-sine strategy to enhance the algorithm’s global optimality search ability;secondly,the Cauchy distribution and Laplace regularization techniques are used in the SCN model,which is referred to as CLSCN,thereby improving the model’s overall search capability and generalization ability.Finally,the performance of SBKA and SBKA-CLSCN is evaluated using eight benchmark functions and the CALCE battery dataset,respectively,and compared in comparison with the Long Short-Term Memory(LSTM)model and the Gated Recurrent Unit(GRU)model,and the experimental results demonstrate the feasibility and effectiveness of the SBKA-CLSCN algorithm.展开更多
To improve the generalization performance and prediction accuracy of the stochastic configuration network(SCN)model,a novel SCN modeling method is proposed.First,the first-and second-order directional derivatives of t...To improve the generalization performance and prediction accuracy of the stochastic configuration network(SCN)model,a novel SCN modeling method is proposed.First,the first-and second-order directional derivatives of the hidden layer output matrix are calculated.The key factors extracted from the directional derivatives are linearly added to the original hidden layer output matrix to formulate a new hidden layer output matrix.Second,a spatial angle adaptive supervisory mechanism is established to improve the quality of the parameter configuration of the hidden layer nodes.The experimental results show that the proposed method improves the generalization performance and prediction accuracy.This work is a beneficial exploration of the standard SCN algorithm.展开更多
As a production quality index of hematite grinding process,particle size(PS)is hard to be measured in real time.To achieve the PS estimation,this paper proposes a novel data driven model of PS using stochastic configu...As a production quality index of hematite grinding process,particle size(PS)is hard to be measured in real time.To achieve the PS estimation,this paper proposes a novel data driven model of PS using stochastic configuration network(SCN)with robust technique,namely,robust SCN(RSCN).Firstly,this paper proves the universal approximation property of RSCN with weighted least squares technique.Secondly,three robust algorithms are presented by employing M-estimation with Huber loss function,M-estimation with interquartile range(IQR)and nonparametric kernel density estimation(NKDE)function respectively to set the penalty weight.Comparison experiments are first carried out based on the UCI standard data sets to verify the effectiveness of these methods,and then the data-driven PS model based on the robust algorithms are established and verified.Experimental results show that the RSCN has an excellent performance for the PS estimation.展开更多
The characters of the intelligent substation communication network structure are analyzed in the paper. Combining existing integrated automation substation hardware circuit and VLAN (Virtual Local Area Network) resear...The characters of the intelligent substation communication network structure are analyzed in the paper. Combining existing integrated automation substation hardware circuit and VLAN (Virtual Local Area Network) research foundation to optimize the network configuration. In accordance with IEC61850 standard, the network is partitioned into several VLANs based on the Tag VLAN division method of ID address. Real-time communication packets between GOOSE networks, SV (sampling information) networks, and switches use 802.1Q protocol headers to distinguish these packets. Finally, OPNET simulation software was used to simulate and verify the simplified dual-star topology. The results demonstrate that the delay and traffic bandwidth meet the requirements of actual substation operation standards. Compared with ordinary single-star networks, the reliability is greatly improved and the effectiveness is improved.展开更多
Synchronization of networked phase oscillators depends essentially on the correlation between the topological structure of the graph and the dynamical property of the elements. We propose the concept of ＇reduced freq...Synchronization of networked phase oscillators depends essentially on the correlation between the topological structure of the graph and the dynamical property of the elements. We propose the concept of ＇reduced frequency＇, a measure which can quantify natural frequencies of each pair of oscillators. Then we introduce an evolving network whose linking rules are controlled by its own dynamical property. The simulation results indicate that when the linking probability positively correlates with the reduced frequency, the network undergoes a first-order phase transition. Meanwhile, we discuss the circumstance under which an explosive synchronization can be ignited. The numerical results show that the peculiar butterfly shape correlation between frequencies and degrees of the nodes contributes to an explosive synchronization transition.展开更多
Configuration errors are proved to be the main reasons for network interruption and anomalies.Many researchers have paid their attention to configuration analysis and provisioning,but few works focus on understanding ...Configuration errors are proved to be the main reasons for network interruption and anomalies.Many researchers have paid their attention to configuration analysis and provisioning,but few works focus on understanding the configuration evolution.In this paper,we uncover the configuration evolution of an operational IP backbone based on the weekly reports gathered from January 2006 to January 2013.We find that rate limiting and launching routes for new customers are configured most frequently.In addition,we conduct an analysis of network failures and find that link failures are the main causes for network failures.We suggest that we should configure redundant links for the links which are easy to break down.At last,according to the analysis results,we illustrate how to provide semi-automated configuration for rate limiting and adding customers.展开更多
The exploitation of Wireless Sensor Networks (WSN) is constrained by limited power, low computing power and storage and short-range radio transmission. Many routing protocols respecting these constraints were develope...The exploitation of Wireless Sensor Networks (WSN) is constrained by limited power, low computing power and storage and short-range radio transmission. Many routing protocols respecting these constraints were developed but, it still lacks formal and standardized solutions being able to help in their configuration. The configuration management that responds to this concern is very important in this type of network. It consists of the definition of data models to configure and is very necessary for the good network performance. Tangible results were obtained in traditional networks with the emergence of NETCONF and YANG standards, but on the best of our humble knowledge there are none yet in WSNs. We propose in this paper wsn-routing-protocol, a YANG data model for routing protocols configuration in WSNs. Following our model, we propose two YANG configuration data models based on the latter: they are respectively aodv for AODV and rpl for RPL.展开更多
There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capaci...There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.展开更多
Deployable mechanism with preferable deployable performance,strong expansibility,and lightweight has attracted much attention because of their potential in aerospace.A basic deployable pyramid unit with good deployabi...Deployable mechanism with preferable deployable performance,strong expansibility,and lightweight has attracted much attention because of their potential in aerospace.A basic deployable pyramid unit with good deployability and expandability is proposed to construct a sizeable deployable mechanism.Firstly,the basic unit folding principle and expansion method is proposed.The configuration synthesis method of adding constraint chains of spatial closed-loop mechanism is used to synthesize the basic unit.Then,the degree of freedom of the basic unit is analyzed using the screw theory and the link dismantling method.Next,the three-dimensional models of the pyramid unit,expansion unit,and array unit are established,and the folding motion simulation analysis is carried out.Based on the number of components,weight reduction rate,and deployable rate,the performance characteristics of the three types of mechanisms are described in detail.Finally,prototypes of the pyramid unit,combination unit,and expansion unit are developed to verify further the correctness of the configuration synthesis based on the pyramid.The proposed deployable mechanism provides aference for the design and application of antennas with a large aperture,high deployable rate,and lightweight.It has a good application prospect in the aerospace field.展开更多
With the expansion of network services,large-scale networks have progressively become common.The network status changes rapidly in response to customer needs and configuration changes,so network configuration changes ...With the expansion of network services,large-scale networks have progressively become common.The network status changes rapidly in response to customer needs and configuration changes,so network configuration changes are also very frequent.However,no matter what changes,the network must ensure the correct conditions,such as isolating tenants from each other or guaranteeing essential services.Once changes occur,it is necessary to verify the after-changed network.Whereas,for the verification of large-scale network configuration changes,many current verifiers show poor efficiency.In order to solve the problem ofmultiple global verifications caused by frequent updates of local configurations in large networks,we present a fast configuration updates verification tool,FastCUV,for distributed control planes.FastCUV aims to enhance the efficiency of distributed control plane verification for medium and large networks while ensuring correctness.This paper presents a method to determine the network range affected by the configuration change.We present a flow model and graph structure to facilitate the design of verification algorithms and speed up verification.Our scheme verifies the network area affected by obtaining the change of the Forwarding Information Base(FIB)before and after.FastCUV supports rich network attributes,meanwhile,has high efficiency and correctness performance.After experimental verification and result analysis,our method outperforms the state-of-the-art method to a certain extent.展开更多
Nowadays,ensuring thequality of networkserviceshas become increasingly vital.Experts are turning toknowledge graph technology,with a significant emphasis on entity extraction in the identification of device configurat...Nowadays,ensuring thequality of networkserviceshas become increasingly vital.Experts are turning toknowledge graph technology,with a significant emphasis on entity extraction in the identification of device configurations.This research paper presents a novel entity extraction method that leverages a combination of active learning and attention mechanisms.Initially,an improved active learning approach is employed to select the most valuable unlabeled samples,which are subsequently submitted for expert labeling.This approach successfully addresses the problems of isolated points and sample redundancy within the network configuration sample set.Then the labeled samples are utilized to train the model for network configuration entity extraction.Furthermore,the multi-head self-attention of the transformer model is enhanced by introducing the Adaptive Weighting method based on the Laplace mixture distribution.This enhancement enables the transformer model to dynamically adapt its focus to words in various positions,displaying exceptional adaptability to abnormal data and further elevating the accuracy of the proposed model.Through comparisons with Random Sampling(RANDOM),Maximum Normalized Log-Probability(MNLP),Least Confidence(LC),Token Entrop(TE),and Entropy Query by Bagging(EQB),the proposed method,Entropy Query by Bagging and Maximum Influence Active Learning(EQBMIAL),achieves comparable performance with only 40% of the samples on both datasets,while other algorithms require 50% of the samples.Furthermore,the entity extraction algorithm with the Adaptive Weighted Multi-head Attention mechanism(AW-MHA)is compared with BILSTM-CRF,Mutil_Attention-Bilstm-Crf,Deep_Neural_Model_NER and BERT_Transformer,achieving precision rates of 75.98% and 98.32% on the two datasets,respectively.Statistical tests demonstrate the statistical significance and effectiveness of the proposed algorithms in this paper.展开更多
This paper aims to reduce the communication cost of the distributed learning algorithm for stochastic configuration networks (SCNs), in which information exchange between the learning agents is conducted only at a tri...This paper aims to reduce the communication cost of the distributed learning algorithm for stochastic configuration networks (SCNs), in which information exchange between the learning agents is conducted only at a trigger time. For this purpose, we propose the communication-censored distributed learning algorithm for SCN, namely ADMMM-SCN-ET, by introducing the event-triggered communication mechanism to the alternating direction method of multipliers (ADMM). To avoid unnecessary information transmissions, each learning agent is equipped with a trigger function. Only if the event-trigger error exceeds a specified threshold and meets the trigger condition, the agent will transmit the variable information to its neighbors and update its state in time. The simulation results show that the proposed algorithm can effectively reduce the communication cost for training decentralized SCNs and save communication resources.展开更多
The first tier of automotive manufacturers has faced to pressures about move,modify,updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor compan...The first tier of automotive manufacturers has faced to pressures about move,modify,updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements,it has to require absolutely lead time to re-wiring of physical interface for production equipment,needs for change existing program and test over again.For prepare this constraints,it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M(Man,Machine,Material, Method)group management which is supports from WSN (Wireless Sensor Network)of the open embedded device called M2M(Machine to Machine)and major functions of middleware including point manager for real-time device communication,real-time data management,Standard API (Application Program Interface)and application template management.To be application system to RMS (Reconfigurable Manufacturing System)for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.展开更多
Deep stochastic configuration networks(DSCNs)produce redundant hidden nodes and connections during training,which complicates their model structures.Aiming at the above problems,this paper proposes a double pruning st...Deep stochastic configuration networks(DSCNs)produce redundant hidden nodes and connections during training,which complicates their model structures.Aiming at the above problems,this paper proposes a double pruning structure design algorithm for DSCNs based on mutual information and relevance.During the training process,the mutual information algorithm is used to calculate and sort the importance scores of the nodes in each hidden layer in a layer-by-layer manner,the node pruning rate of each layer is set according to the depth of the DSCN at the current time,the nodes that contribute little to the model are deleted,and the network-related parameters are updated.When the model completes the configuration procedure,the correlation evaluation strategy is used to sort the global connection weights and delete insignificance connections;then,the network parameters are updated after pruning is completed.The experimental results show that the proposed structure design method can effectively compress the scale of a DSCN model and improve its modeling speed;the model accuracy loss is small,and fine-tuning for accuracy restoration is not needed.The obtained DSCN model has certain application value in the field of regression analysis.展开更多
For accurate prediction of nitrogen oxides(NOx) concentration during the municipal solid waste incineration(MSWI) process, in this paper, a prediction modeling method based on a sparse regularization stochastic config...For accurate prediction of nitrogen oxides(NOx) concentration during the municipal solid waste incineration(MSWI) process, in this paper, a prediction modeling method based on a sparse regularization stochastic configuration network is proposed. The method combines Drop Connect regularization with L1 regularization. Based on the L1 regularization constraint stochastic configuration network output weights, Drop Connect regularization is applied to the input weights to introduce sparsity. A probability decay strategy based on network residuals is designed to address situations where the Drop Connect fixed drop probability affects model convergence. Finally, the generated sparse stochastic configuration network is used to establish the model, and is validated through experiments with standard datasets and actual data from an MSWI plant in Beijing. The experimental results prove that this modeling method exhibits high-precision prediction and generalization ability while effectively simplifying the model structure, which enables accurate prediction of NOx concentration.展开更多
Public transportation network reorganisation can be a key measure in designing more efficient networks and increasing the number of passengers. To date, several authors have proposed models for the “transit route net...Public transportation network reorganisation can be a key measure in designing more efficient networks and increasing the number of passengers. To date, several authors have proposed models for the “transit route network design problem” (TRNDP), and many of them use a transit assignment model as one component. However, not all models have considered the “common lines problem,” which is an essential feature in transit network assignment and is based on the concept that the fastest way to get to a destination is to take the first vehicle arriving among an “attractive” set of lines. Thus, we sought to reveal the features of considering the common lines problem by comparing results with and without considering the problem in a transit assignment model. For comparison, a model similar to a previous one was used, formulated as a bi-level optimisation problem, the upper problem of which is described as a multi-objective problem. As a result, although the solutions with and without considering the common lines showed almost the same Pareto front, we confirmed that a more direct service is provided if the common lines problem is considered whereas a less direct service is provided if it is not. With a small network case study, we found that considering the common lines problem in the TRNDP is important as it allows operators to provide more direct services.展开更多
The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor comp...The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements, it has to require absolutely lead time to re-wiring of physical interface for production equipment, needs for change existing program and test over again. For prepare this constraints, it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M (Man, Machine, Material, Method) group management which is supports from WSN (Wireless Sensor Network) of the open embedded device called M2M (Machine to Machine) and major functions of middleware including point manager for real-time device communication, real-time data management, Standard API (Application Program Interface) and application template management. To be application system to RMS (Reconfigurable Manufacturing System) for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.展开更多
With the challenges brought by the expansion of network scale,as well as the diversity of the equipments and the complexity of network protocols,many self-configurable systems have been proposed combining formal speci...With the challenges brought by the expansion of network scale,as well as the diversity of the equipments and the complexity of network protocols,many self-configurable systems have been proposed combining formal specification and model finding techniques.In this paper,we pay more attention to formal specifications of network information,i.e.,exploring principles and algorithm to map network information(topology,devices and status,etc.) to Alloy specifications.We first model network information in relational form,which is easy to realize because of the structured feature of network information in nature.Then we map the relational data to Alloy specifications according to our novel data mapping principles and algorithm.Based on the transition of relational data,it is possible to automatically map network information to Alloy specifications.We evaluate our data mapping principles and algorithm by applying them to a practical application scenario.The results illustrate that we can find a model for the task within a tolerant time interval,which implies that our novel approach can convert relational data to Alloy specifications correctly and efficiently.展开更多
NTP is nowadays the most widely used distributed network time protocol, which aims at synchronizing the clocks of computers in a network and keeping the accuracy and validation of the time information which is transmi...NTP is nowadays the most widely used distributed network time protocol, which aims at synchronizing the clocks of computers in a network and keeping the accuracy and validation of the time information which is transmitted in the network. Without automatic configuration mechanism, the stability and flexibility of the synchronization network built upon NTP protocol are not satisfying. P2P’s resource discovery mechanism is used to look for time sources in a synchronization network, and according to the network environment and node’s quality, the synchronization network is constructed dynamically.展开更多
文摘The accurate estimation of lithium battery state of health(SOH)plays an important role in the health management of battery systems.In order to improve the prediction accuracy of SOH,this paper proposes a stochastic configuration network based on a multi-converged black-winged kite search algorithm,called SBKA-CLSCN.Firstly,the indirect health index(HI)of the battery is extracted by combining it with Person correlation coefficients in the battery charging and discharging cycle point data.Secondly,to address the problem that the black-winged kite optimization algorithm(BKA)falls into the local optimum problem and improve the convergence speed,the Sine chaotic black-winged kite search algorithm(SBKA)is designed,which mainly utilizes the Sine mapping and the golden-sine strategy to enhance the algorithm’s global optimality search ability;secondly,the Cauchy distribution and Laplace regularization techniques are used in the SCN model,which is referred to as CLSCN,thereby improving the model’s overall search capability and generalization ability.Finally,the performance of SBKA and SBKA-CLSCN is evaluated using eight benchmark functions and the CALCE battery dataset,respectively,and compared in comparison with the Long Short-Term Memory(LSTM)model and the Gated Recurrent Unit(GRU)model,and the experimental results demonstrate the feasibility and effectiveness of the SBKA-CLSCN algorithm.
基金supported by the National Natural Science Foundation of China(62373017).
文摘To improve the generalization performance and prediction accuracy of the stochastic configuration network(SCN)model,a novel SCN modeling method is proposed.First,the first-and second-order directional derivatives of the hidden layer output matrix are calculated.The key factors extracted from the directional derivatives are linearly added to the original hidden layer output matrix to formulate a new hidden layer output matrix.Second,a spatial angle adaptive supervisory mechanism is established to improve the quality of the parameter configuration of the hidden layer nodes.The experimental results show that the proposed method improves the generalization performance and prediction accuracy.This work is a beneficial exploration of the standard SCN algorithm.
基金Projects(61603393,61741318)supported in part by the National Natural Science Foundation of ChinaProject(BK20160275)supported by the Natural Science Foundation of Jiangsu Province,China+1 种基金Project(2015M581885)supported by the Postdoctoral Science Foundation of ChinaProject(PAL-N201706)supported by the Open Project Foundation of State Key Laboratory of Synthetical Automation for Process Industries of Northeastern University,China
文摘As a production quality index of hematite grinding process,particle size(PS)is hard to be measured in real time.To achieve the PS estimation,this paper proposes a novel data driven model of PS using stochastic configuration network(SCN)with robust technique,namely,robust SCN(RSCN).Firstly,this paper proves the universal approximation property of RSCN with weighted least squares technique.Secondly,three robust algorithms are presented by employing M-estimation with Huber loss function,M-estimation with interquartile range(IQR)and nonparametric kernel density estimation(NKDE)function respectively to set the penalty weight.Comparison experiments are first carried out based on the UCI standard data sets to verify the effectiveness of these methods,and then the data-driven PS model based on the robust algorithms are established and verified.Experimental results show that the RSCN has an excellent performance for the PS estimation.
文摘The characters of the intelligent substation communication network structure are analyzed in the paper. Combining existing integrated automation substation hardware circuit and VLAN (Virtual Local Area Network) research foundation to optimize the network configuration. In accordance with IEC61850 standard, the network is partitioned into several VLANs based on the Tag VLAN division method of ID address. Real-time communication packets between GOOSE networks, SV (sampling information) networks, and switches use 802.1Q protocol headers to distinguish these packets. Finally, OPNET simulation software was used to simulate and verify the simplified dual-star topology. The results demonstrate that the delay and traffic bandwidth meet the requirements of actual substation operation standards. Compared with ordinary single-star networks, the reliability is greatly improved and the effectiveness is improved.
基金Supported by the Open Fund from Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing under Grant No 2015CSOBDP0101the National Natural Science Foundation of China under Grant No11162019
文摘Synchronization of networked phase oscillators depends essentially on the correlation between the topological structure of the graph and the dynamical property of the elements. We propose the concept of ＇reduced frequency＇, a measure which can quantify natural frequencies of each pair of oscillators. Then we introduce an evolving network whose linking rules are controlled by its own dynamical property. The simulation results indicate that when the linking probability positively correlates with the reduced frequency, the network undergoes a first-order phase transition. Meanwhile, we discuss the circumstance under which an explosive synchronization can be ignited. The numerical results show that the peculiar butterfly shape correlation between frequencies and degrees of the nodes contributes to an explosive synchronization transition.
基金supported by the National Natural Science Foundation of China under Grant Nos.61602105 and 61572123China Postdoctoral Science Foundation under Grant Nos.2016M601323+1 种基金the Fundamental Research Funds for the Central Universities Project under Grant No.N150403007CERNET Innovation Project under Grant No.NGII20160126
文摘Configuration errors are proved to be the main reasons for network interruption and anomalies.Many researchers have paid their attention to configuration analysis and provisioning,but few works focus on understanding the configuration evolution.In this paper,we uncover the configuration evolution of an operational IP backbone based on the weekly reports gathered from January 2006 to January 2013.We find that rate limiting and launching routes for new customers are configured most frequently.In addition,we conduct an analysis of network failures and find that link failures are the main causes for network failures.We suggest that we should configure redundant links for the links which are easy to break down.At last,according to the analysis results,we illustrate how to provide semi-automated configuration for rate limiting and adding customers.
文摘The exploitation of Wireless Sensor Networks (WSN) is constrained by limited power, low computing power and storage and short-range radio transmission. Many routing protocols respecting these constraints were developed but, it still lacks formal and standardized solutions being able to help in their configuration. The configuration management that responds to this concern is very important in this type of network. It consists of the definition of data models to configure and is very necessary for the good network performance. Tangible results were obtained in traditional networks with the emergence of NETCONF and YANG standards, but on the best of our humble knowledge there are none yet in WSNs. We propose in this paper wsn-routing-protocol, a YANG data model for routing protocols configuration in WSNs. Following our model, we propose two YANG configuration data models based on the latter: they are respectively aodv for AODV and rpl for RPL.
基金supported by State Grid Corporation Limited Science and Technology Project Funding(Contract No.SGCQSQ00YJJS2200380).
文摘There is instability in the distributed energy storage cloud group end region on the power grid side.In order to avoid large-scale fluctuating charging and discharging in the power grid environment and make the capacitor components showa continuous and stable charging and discharging state,a hierarchical time-sharing configuration algorithm of distributed energy storage cloud group end region on the power grid side based on multi-scale and multi feature convolution neural network is proposed.Firstly,a voltage stability analysis model based onmulti-scale and multi feature convolution neural network is constructed,and the multi-scale and multi feature convolution neural network is optimized based on Self-OrganizingMaps(SOM)algorithm to analyze the voltage stability of the cloud group end region of distributed energy storage on the grid side under the framework of credibility.According to the optimal scheduling objectives and network size,the distributed robust optimal configuration control model is solved under the framework of coordinated optimal scheduling at multiple time scales;Finally,the time series characteristics of regional power grid load and distributed generation are analyzed.According to the regional hierarchical time-sharing configuration model of“cloud”,“group”and“end”layer,the grid side distributed energy storage cloud group end regional hierarchical time-sharing configuration algorithm is realized.The experimental results show that after applying this algorithm,the best grid side distributed energy storage configuration scheme can be determined,and the stability of grid side distributed energy storage cloud group end region layered timesharing configuration can be improved.
基金Supported by National Natural Science Foundation of China(Grant No.52075467)Jiangsu Provincial Natural Science Foundation of China(Grant No.BK20220649)+1 种基金Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Grant No.23KJB460010)Jiangsu Provincial Key R&D Project(Grant No.BE2022062).
文摘Deployable mechanism with preferable deployable performance,strong expansibility,and lightweight has attracted much attention because of their potential in aerospace.A basic deployable pyramid unit with good deployability and expandability is proposed to construct a sizeable deployable mechanism.Firstly,the basic unit folding principle and expansion method is proposed.The configuration synthesis method of adding constraint chains of spatial closed-loop mechanism is used to synthesize the basic unit.Then,the degree of freedom of the basic unit is analyzed using the screw theory and the link dismantling method.Next,the three-dimensional models of the pyramid unit,expansion unit,and array unit are established,and the folding motion simulation analysis is carried out.Based on the number of components,weight reduction rate,and deployable rate,the performance characteristics of the three types of mechanisms are described in detail.Finally,prototypes of the pyramid unit,combination unit,and expansion unit are developed to verify further the correctness of the configuration synthesis based on the pyramid.The proposed deployable mechanism provides aference for the design and application of antennas with a large aperture,high deployable rate,and lightweight.It has a good application prospect in the aerospace field.
基金supported by the Fundamental Research Funds for the Central Universities(2021RC239)the Postdoctoral Science Foundation of China(2021 M690338)+3 种基金theHainan Provincial Natural Science Foundation of China(620RC562,2019RC096,620RC560)the Scientific Research Setup Fund of Hainan University(KYQD(ZR)1877)the Program of Hainan Association for Science and Technology Plans to Youth R&D Innovation(QCXM201910)the National Natural Science Foundation of China(61802092,62162021).
文摘With the expansion of network services,large-scale networks have progressively become common.The network status changes rapidly in response to customer needs and configuration changes,so network configuration changes are also very frequent.However,no matter what changes,the network must ensure the correct conditions,such as isolating tenants from each other or guaranteeing essential services.Once changes occur,it is necessary to verify the after-changed network.Whereas,for the verification of large-scale network configuration changes,many current verifiers show poor efficiency.In order to solve the problem ofmultiple global verifications caused by frequent updates of local configurations in large networks,we present a fast configuration updates verification tool,FastCUV,for distributed control planes.FastCUV aims to enhance the efficiency of distributed control plane verification for medium and large networks while ensuring correctness.This paper presents a method to determine the network range affected by the configuration change.We present a flow model and graph structure to facilitate the design of verification algorithms and speed up verification.Our scheme verifies the network area affected by obtaining the change of the Forwarding Information Base(FIB)before and after.FastCUV supports rich network attributes,meanwhile,has high efficiency and correctness performance.After experimental verification and result analysis,our method outperforms the state-of-the-art method to a certain extent.
基金supported by the National Key R&D Program of China(2019YFB2103202).
文摘Nowadays,ensuring thequality of networkserviceshas become increasingly vital.Experts are turning toknowledge graph technology,with a significant emphasis on entity extraction in the identification of device configurations.This research paper presents a novel entity extraction method that leverages a combination of active learning and attention mechanisms.Initially,an improved active learning approach is employed to select the most valuable unlabeled samples,which are subsequently submitted for expert labeling.This approach successfully addresses the problems of isolated points and sample redundancy within the network configuration sample set.Then the labeled samples are utilized to train the model for network configuration entity extraction.Furthermore,the multi-head self-attention of the transformer model is enhanced by introducing the Adaptive Weighting method based on the Laplace mixture distribution.This enhancement enables the transformer model to dynamically adapt its focus to words in various positions,displaying exceptional adaptability to abnormal data and further elevating the accuracy of the proposed model.Through comparisons with Random Sampling(RANDOM),Maximum Normalized Log-Probability(MNLP),Least Confidence(LC),Token Entrop(TE),and Entropy Query by Bagging(EQB),the proposed method,Entropy Query by Bagging and Maximum Influence Active Learning(EQBMIAL),achieves comparable performance with only 40% of the samples on both datasets,while other algorithms require 50% of the samples.Furthermore,the entity extraction algorithm with the Adaptive Weighted Multi-head Attention mechanism(AW-MHA)is compared with BILSTM-CRF,Mutil_Attention-Bilstm-Crf,Deep_Neural_Model_NER and BERT_Transformer,achieving precision rates of 75.98% and 98.32% on the two datasets,respectively.Statistical tests demonstrate the statistical significance and effectiveness of the proposed algorithms in this paper.
文摘This paper aims to reduce the communication cost of the distributed learning algorithm for stochastic configuration networks (SCNs), in which information exchange between the learning agents is conducted only at a trigger time. For this purpose, we propose the communication-censored distributed learning algorithm for SCN, namely ADMMM-SCN-ET, by introducing the event-triggered communication mechanism to the alternating direction method of multipliers (ADMM). To avoid unnecessary information transmissions, each learning agent is equipped with a trigger function. Only if the event-trigger error exceeds a specified threshold and meets the trigger condition, the agent will transmit the variable information to its neighbors and update its state in time. The simulation results show that the proposed algorithm can effectively reduce the communication cost for training decentralized SCNs and save communication resources.
基金supported by the Industry Foundation project from the Ministry of Knowledge Economy in the Korean Government.
文摘The first tier of automotive manufacturers has faced to pressures about move,modify,updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements,it has to require absolutely lead time to re-wiring of physical interface for production equipment,needs for change existing program and test over again.For prepare this constraints,it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M(Man,Machine,Material, Method)group management which is supports from WSN (Wireless Sensor Network)of the open embedded device called M2M(Machine to Machine)and major functions of middleware including point manager for real-time device communication,real-time data management,Standard API (Application Program Interface)and application template management.To be application system to RMS (Reconfigurable Manufacturing System)for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.
基金supported by the National Natural Science Foundation of China(62073006)the Beijing Natural Science Foundation of China(4212032)
文摘Deep stochastic configuration networks(DSCNs)produce redundant hidden nodes and connections during training,which complicates their model structures.Aiming at the above problems,this paper proposes a double pruning structure design algorithm for DSCNs based on mutual information and relevance.During the training process,the mutual information algorithm is used to calculate and sort the importance scores of the nodes in each hidden layer in a layer-by-layer manner,the node pruning rate of each layer is set according to the depth of the DSCN at the current time,the nodes that contribute little to the model are deleted,and the network-related parameters are updated.When the model completes the configuration procedure,the correlation evaluation strategy is used to sort the global connection weights and delete insignificance connections;then,the network parameters are updated after pruning is completed.The experimental results show that the proposed structure design method can effectively compress the scale of a DSCN model and improve its modeling speed;the model accuracy loss is small,and fine-tuning for accuracy restoration is not needed.The obtained DSCN model has certain application value in the field of regression analysis.
基金supported by the National Natural Science Foundation of China (62373017, 62073006)the Beijing Natural Science Foundation of China (4212032)。
文摘For accurate prediction of nitrogen oxides(NOx) concentration during the municipal solid waste incineration(MSWI) process, in this paper, a prediction modeling method based on a sparse regularization stochastic configuration network is proposed. The method combines Drop Connect regularization with L1 regularization. Based on the L1 regularization constraint stochastic configuration network output weights, Drop Connect regularization is applied to the input weights to introduce sparsity. A probability decay strategy based on network residuals is designed to address situations where the Drop Connect fixed drop probability affects model convergence. Finally, the generated sparse stochastic configuration network is used to establish the model, and is validated through experiments with standard datasets and actual data from an MSWI plant in Beijing. The experimental results prove that this modeling method exhibits high-precision prediction and generalization ability while effectively simplifying the model structure, which enables accurate prediction of NOx concentration.
文摘Public transportation network reorganisation can be a key measure in designing more efficient networks and increasing the number of passengers. To date, several authors have proposed models for the “transit route network design problem” (TRNDP), and many of them use a transit assignment model as one component. However, not all models have considered the “common lines problem,” which is an essential feature in transit network assignment and is based on the concept that the fastest way to get to a destination is to take the first vehicle arriving among an “attractive” set of lines. Thus, we sought to reveal the features of considering the common lines problem by comparing results with and without considering the problem in a transit assignment model. For comparison, a model similar to a previous one was used, formulated as a bi-level optimisation problem, the upper problem of which is described as a multi-objective problem. As a result, although the solutions with and without considering the common lines showed almost the same Pareto front, we confirmed that a more direct service is provided if the common lines problem is considered whereas a less direct service is provided if it is not. With a small network case study, we found that considering the common lines problem in the TRNDP is important as it allows operators to provide more direct services.
文摘The first tier of automotive manufacturers has faced to pressures about move, modify, updating tasks for manufacturing resources in production processes from demand response of production order sequence for motor company and process innovation purpose for productivity. For meets this requirements, it has to require absolutely lead time to re-wiring of physical interface for production equipment, needs for change existing program and test over again. For prepare this constraints, it needs studying an auto-configuration functions that build for both visibility and flexibility based on the 4M (Man, Machine, Material, Method) group management which is supports from WSN (Wireless Sensor Network) of the open embedded device called M2M (Machine to Machine) and major functions of middleware including point manager for real-time device communication, real-time data management, Standard API (Application Program Interface) and application template management. To be application system to RMS (Reconfigurable Manufacturing System) for rapidly response from various orders and model from motor company that is beginning to establishing the mapping of manufacturing resources of 4M using WSN.
基金supported by the National Science Foundation for Distinguished Young Scholars of China under Grant No.61225012 and No.71325002the Specialized Research Fund of the Doctoral Program of Higher Education for the Priority Development Areas under Grant No.20120042130003the Liaoning BaiQianWan Talents Program under Grant No.2013921068
文摘With the challenges brought by the expansion of network scale,as well as the diversity of the equipments and the complexity of network protocols,many self-configurable systems have been proposed combining formal specification and model finding techniques.In this paper,we pay more attention to formal specifications of network information,i.e.,exploring principles and algorithm to map network information(topology,devices and status,etc.) to Alloy specifications.We first model network information in relational form,which is easy to realize because of the structured feature of network information in nature.Then we map the relational data to Alloy specifications according to our novel data mapping principles and algorithm.Based on the transition of relational data,it is possible to automatically map network information to Alloy specifications.We evaluate our data mapping principles and algorithm by applying them to a practical application scenario.The results illustrate that we can find a model for the task within a tolerant time interval,which implies that our novel approach can convert relational data to Alloy specifications correctly and efficiently.
文摘NTP is nowadays the most widely used distributed network time protocol, which aims at synchronizing the clocks of computers in a network and keeping the accuracy and validation of the time information which is transmitted in the network. Without automatic configuration mechanism, the stability and flexibility of the synchronization network built upon NTP protocol are not satisfying. P2P’s resource discovery mechanism is used to look for time sources in a synchronization network, and according to the network environment and node’s quality, the synchronization network is constructed dynamically.
