最新刊期
卷 42 ， 期 12 ， 2014
- 摘要：Detecting functional modules from protein-protein interaction networks (PPINs) is an active research area with many practical applications.To date,multiple biological data sources are available such as gene expression data and gene ontology (GO).These data explain the biological roles of proteins from different views and provide additional information to alleviate false information in PPINs.This work focuses on extracting consistent information from diverse data sources.To address this problem,this work proposes a collective non-negative matrix factorization (CoNMF) method which efficiently integrates views of gene ontology,gene expression data and PPINs.In our method,the integration problem is reduced to optimimum approximations of multi-view data by the productions of their common matrix factor with basis matrices.As a result,the common matrix factor provides an intuitive interpretation of soft clustering.Extensive experiments show that CoNMF outperforms most of the baseline methods listed in the paper and is an effective method to extract functional modules in PPINs.关键词：Protein-protein interaction network;functional module detection;multiple data sources Integration;soft clustering3|1605|3更新时间：2025-07-16
- 摘要：To solve the problem of premature convergence,this paper presents a method of generating test cases based on orthogonal exploration and particle swarm optimization.First,singular value decomposition is used to estimate the evolution direction and drives the population towards orthogonal direction,so that our method can avoid searching those traversed areas so far and jump out of local optimum.Then,we change the velocity so that it is able to be consistent with the orthogonal direction,and as a result,the population can be affected continually,which can decrease the frequency of singular value decomposition and reduce the time consumption.Finally,the local search is used for the best particle in each generation.The experimental results show that our method has advantages in coverage,running time,and the number of generations.关键词：test case generation;particle swarm optimization;local search;singular value decomposition2|1634|6更新时间：2025-07-16
- 摘要：Aiming at the low efficiency of multi-topic crawling,the difference between built-in search engines (BSEs) and general search engines (GSEs) is investigated.The idea and method of dividing topic rules into atomic rules are proposed respectively,and three relations (equating relation,exchanging relation and containing relation) between atomic rules are analyzed.Based on atomic rule relations,the different allocation strategies for BSEs and GSEs are designed,which can not only improve the precision of topic-specific crawling,but also reduce crawling times.Furthermore,a method of sentence cluster-based relevance computing between topics and documents is proposed to solve the low precision problem of directly crawling information by atomic rules.We conduct an experiment with 138 topic rules (containing 8223 atomic rules),14 BSEs and 4 GSEs for evaluating the number of crawling information and related information in unit time.The results show that the proposed method offers more effective performances.关键词：multi-topic crawling;atomic rules;built-in search engines;general search engines;relevance computing2|1117|1更新时间：2025-07-16
- 摘要：The study of time series prediction is pervasive in various fields.We propose a cluster-based hidden Markov model to approach the multi-step prediction problem in time series.As multi-step time series prediction problem is not fully addressed from a system angle,we utilize the hidden state of hidden Markov model to represent the inner state of a time series production system.We also promote a cluster algorithm combining the temporal and similarity criteria to address the distance calculating issue in time series clustering.This non-trivial criterion proves effective in multi-step time series prediction.Through a non-parameter approximate method we estimate the inner hidden state distributes from every single state.And we also prove the correctness of an iteratively refinement of the cluster-based hidden Markov model(HMM).Experimental results on authentic data indicate the effectiveness and accuracy of this approach.关键词：time series;multi-step prediction;hidden Markov model(HMM);cluster2|3867|9更新时间：2025-07-16
- 摘要：Existing feature extraction algorithms are difficult to capture useful information from complex images.A feature extraction approach is proposed based on the weakly supervised learning with denoising restricted Boltzmann machine(RBM).First,a standard RBM is pre-trained in an unsupervised learning way,which provides a hierarchical mode with a visible layer and a hidden layer.Second,for the visible layer,a stochastic binary switch node is employed.And for the hidden layer,it is divided into foreground-hidden nodes and background-hidden nodes based on the score of each hidden node's activation values and times,thus we can achieve a binary mixture denoising RBMs.Finally,the pixel-wise denoising RBMs is trained by using small number label information and stochastic switch nodes through multiplicative interaction.The experimental results show that significant performance improvement is achieved with our proposed method.关键词：feature extraction;restricted Boltzmann machine(RBM);object recognition2|2425|3更新时间：2025-07-16
- 摘要：Roles minimization problem and its algorithm based on RBAC model are studied in this paper.Roles minimization problem is introduced into concept lattice model.The minimal set of roles,roles replacement and roles reduction are defined,and the corresponding theorems are proved.Based on this,the model of solving roles minimization problem based on roles replacement is created and a greedy algorithm is proposed.In this algorithm,the object concepts set is regarded as initial set,concetps in roles set are replaced and reducted by their parents one by one,and the minimal set of roles is solved by iteration in bottom-up way.Experiments show that the theory and the proposed algorithm are effective.关键词：formal concept analysis (FCA);concept lattice;RBAC;minimal set of roles2|1384|7更新时间：2025-07-16
- 摘要：The traditional iris recognition methods focused on extracting and matching local region characteristics,yet failing to consider the correlation of long-distance regions(non-local regions).The ordinal measures-based methods extracted the average gray-level values of non-local regions by Gaussan filtering and then ranked them,which unfortunately were not applicable to situations where regions are described by probability distributions.This paper presents a novel recognition method for tackling these shortcomings.The proposed method represents the texture characteristics of local regions using spatio-phase joint probability distributions,and further explores the associating relations between them.We concatenate the features of regions at varying positions to obtain the non-local associating descriptors for modeling their relations,among which we primarily study the recognition performance by associating two or three regions.During iris matching process,we consider the effectiveness of non-local region associating descriptors to exclude the effects of occlusion,highlights,noise and etc,and allow small translation of the associating descriptors to model local deformation of iris texture;finally we adopt a robust diffusion distance between histograms for descriptors comparison.We conduct experiments for iris verification and iris identification on three public databases,and experiments demonstrate that the proposed method is superior to the state-of-the-arts.关键词：iris verification and identification;spatio-phase joint distribution;non-local region associating2|1435|1更新时间：2025-07-16
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Face Image Recognition Method via Gabor Low-Rank Recovery Sparse Representation-Based Classification
摘要：To recognize the face images containing errors of illumination,expression,pose,occlusion,or contaminated by noise,we propose a face image recognition method via Gabor low-rank recovery sparse representation-based classification.In this method,we firstly obtain the error images of the training images using the low-rank matrix recovery algorithm,and then calculate the Gabor feature vectors of the training images and the corresponding error images via the Gabor transform algorithm.With these Gabor feature vectors,we constitute a Gabor feature dictionary.Based on the Gabor feature dictionary,we calculate the sparse representation coefficients of Gabor feature vector of the given test image.For each class,we use the sparse representation coefficients associated with the class and the Gabor feature dictionary to reconstruct the Gabor feature vector of the given test image.And then we calculate the reconstruction error between the Gabor feature vector and its approximation associated with the class.Based on the reconstruction errors associated with different class,we can accurately classify the given test image.Experimental results on CMU PIE,Extend Yale B and AR databases show that the proposed face image recognition method has a higher recognition rate and greater noise immunity.关键词：face image recognition;sparse representation;low-rank matrix recovery;Gabor transformation2|1316|8更新时间：2025-07-16 - 摘要：To overcome problems that malfunctions in the measurement system lead to degradation of performance of strong tracking filter (STF) and inherent disadvantages of STF,an adaptive square-root cubature Kalman filter (SRCKF) algorithm is proposed.With innovation covariance matching techniques an adaptive SRCKF is built,which is insensitive to measurement malfunctions.Strong tracking adaptive SRCKF views STF as the basic theory framework and makes adaptive SRCKF to replace extended Kalman filter (EKF),so it has the advantages of STF and adaptive SRCKF.In case of model uncertainty of system and measurement malfunctions,the proposed algorithm has strong robustness and high accuracy.Simulation results show the effectiveness of the presented algorithm.关键词：strong tracking filter;square-root cubature Kalman filter;adaptive filter;robust2|3413|15更新时间：2025-07-16
- 摘要：To enhance the approximation and generalization ability of classical artificial neural networks,a quantum-inspired neural network model,whose input of each dimension is a discrete sequence,is proposed.This model concludes three layers,in which the hidden layer consists of quantum-inspired neurons,and the output layer consists of common neurons.The quantum-inspired neuron consists of the quantum rotation gates and the multi-qubits controlled-rotation gates.By using the information feedback of target qubit from output to input in multi-qubits controlled-rotation gate,the overall memory of input sequences is realized.The output of quantum-inspired neuron is obtained from the entanglements of multi-qubits in controlled-rotation gates.The learning algorithm is designed in detail according to the basic principles of quantum computation.The characteristics of input sequence can be effectively obtained by way of "breadth" and "depth".The simulation results show that,when the input nodes and the length of the sequence satisfy a certain relations,the proposed model is obviously superior to the common artificial neural networks.关键词：quantum computation;quantum rotation gate;controlled-rotation gate;quantum-inspired neuron;quantum-inspired neural networks4|1645|3更新时间：2025-07-16
- 摘要：Based on 3-D graphics hardware accelerator and Z-Buffer technique,graphic electromagnetic computing (GRECO) algorithm can efficiently resolve blanking difficulties and visualization problems of traditional electromagnetic calculation procedures.Therefore,GRECO algorithm is considered as one of the most efficient methods to acquire characteristics of high-frequency and electricity large-sized target.However,there are disadvantages of traditional GRECO algorithm,as follows:normal vector of target cannot be extracted accurately,calculation accuracy is affected by screen resolution greatly and multiple reflections cannot be calculated directly.As a result,traditional GRECO algorithm is limited for this reason and cannot be used in some region widely.The traditional GRECO is improved in this paper,so that the geometric information of pixel can be extracted accurately.Technique of off-screen rendering based on frame buffer object (FBO) is used for improving the algorithm.Then the normal vector of target can be obtained precisely and effectively.Traditional discriminated method of facet pairs is improved by using area projection/physical optics to adapt the computation of RCS multiple scattering.关键词：radar cross section (RCS);graphical electromagnetic computing;multi-reflection;FBO;off-screen rendering2|1306|0更新时间：2025-07-16
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Reconstruction Algorithm for Compressed Sensing of Video Based on Joint Total Variation Minimization
摘要：The residual reconstruction algorithm,which performs prediction and compensation at the receiver side,is an efficient reconstruction algorithm for compressed sensing of video.However,the residual reconstruction algorithm doesn't make use of the sparsity prior of an image,and the performance of the algorithm all relies on the accuracy of prediction.This paper proposes a reconstruction algorithm based on joint total variation (TV) minimization to improve the quality of reconstructed images.In order to jointly exploit the sparsity of images and their residual,TV norm of a target image block and TV norm of its residual are both calculated in the established reconstruction model.To solve the minimization problem,new variables are introduced,and an iterative algorithm is developed based on the split Bregman method.The experimental results show that when compared with other traditional algorithms,the proposed algorithm is able to provide higher quality of reconstructed images at the same sampling rates.关键词：compressed sensing;total variation;sparsity prior;residual reconstruction2|1789|6更新时间：2025-07-16 - 摘要：Resection is one of important issues in machine vision.Although L2 norm based least square method is reasonably fast,the globally optimal solution cannot be obtained theoretically due to its non-convexity of the objective function.Optimization using the L∞ norm has been becoming an effective way to solve parameter estimation problems in multiview geometry.But the computational cost increases rapidly with the size of measurement data.In the paper,we propose a novel approach under the framework of enhanced continuous taboo search (ECTS) for resection in multiview geometry.ECTS is an optimization method in the domain of artificial intelligence,which has an interesting ability of covering a wide solution space by promoting the search far away from current solution and consecutively decreasing the possibility of trapping in the local minima.We propose the corresponding ways in the key steps of ECTS,diversification and intensification.We also present theoretical proof to guarantee the global convergence of search with probability one.Experimental results validate that the ECTS can obtain the global optimum effectively and efficiently.Potentially,the novel ECTS framework can be employed in many applications of multi-view geometry.关键词：multiview geometry;resection;global optimization;taboo search2|1218|0更新时间：2025-07-16
- 摘要：When the distributions of 2 class samples are different,the classification results will be biased by using least square classifiers,such as proximal support vector machine (PSVM).Inevitably,this decision bias will cause non-minimal classification error rates.In the present paper,based on equivalent generalized eigenvalue decomposition model of PSVM,a novel optimizing samples distribution PSVM model is proposed,which can improve original PSVM decision.The model is constructed as a generalized eigenvalue decomposition model and contains an optimal samples distribution regularization item.It can maximize distances between correctly classified samples and decision boundary and minimize distances between misclassified samples and decision boundary.Experimental results under artificial datasets and 10 data subsets from UCI datasets show that using this novel model can adjust decision effectively and achieve better classification effects.关键词：proximal support vector machine(PSVM);optimizing sample distribution;regularization technique2|1278|2更新时间：2025-07-16
- 摘要：K-means algorithm is the most widely used method due to its easy understanding and fast speed.However,this method has the disadvantage that the clustering results depend on the selection of the initial clustering center and it is easy to fall into local optimal.For this reason,this paper proposed a honey-bee mating optimization clustering algorithm.It generates initial swarm by density and distance,and regards rough set clustering algorithm which has strong local search ability as a code of the works to enhance the local search ability of the algorithm.At last,in order to improve the diversity level of the swarm and the global optimization ability of the algorithm,random swarm population are introduced continuously in the iterative process.Our experiments show that the proposed algorithm not only can effectively suppress premature convergence,but also has strong stability and produces good clustering results.关键词：clustering;honey-bee mating optimization;rough set;K-means2|1740|4更新时间：2025-07-16
- 摘要：The areas at an altitude of 1000m and above account for 65% of the total area of China,therefore,China is a plateau country.For electronic devices such as computers,cooling ability is much affected by attitude,and electric heat dissipation directly affects the service life of components,computing speed,stability,etc.To study the effects of altitude on the cooling of electric devices,the altitude parameters are introduced to modify the Zukauskas mathematical model,Chiltion-Colburn model,and other heat transfer models,according to the fundamental theory of thermodynamics.Electrical heat calculation method for the electronic devices at different altitudes is proposed,and the relationship between the altitude and electrical cooling capability is revealed.The analysis result conforms to the international electro-technical commission standard experiment and is verified by the specialized thermal design software Ansys.Icepak4.5,which provides theoretical basis for the thermal design and the life-span evaluation of the electric devices,such as computers,at different altitudes.关键词：high altitude;air density;heat dissipation;zukauskas mathematical model2|3318|2更新时间：2025-07-16
- 摘要：The paper proposed an adaptive partition method considering environmental structural factors,which is applicable for multilayered complex environment.Simulation scene is automatically extracted to walkable adjacent areas,and a coarse granularity partition based on regions is applied to get shorter execution time.The inter-individual perceptual computing of any two individuals separated by obstacle between two adjacent regions is negligible,so it efficiently reduces the inter-node communication cost and makes the algorithm more suitable for large scale crowd simulation.The results show the proposed algorithm gets lower cost and higher performance.An efficient distributed simulation model is designed for the partition method,and a distributed system based on the model gets higher simulation performance on both inner door and out door scene.The performance of system with the same crowd size linearly increases with the increase of compute nodes,which proves high scalability of the system.关键词：distributed simulation;crowd simulation;task partition;graphic processing unit (GPU)2|1172|0更新时间：2025-07-16
- 摘要：Based on compressed sensing theory,we research a meticulous sparsity adaptive matching pursuit algorithm,and propose a new method for digital image retrieval on this basis.Firstly,the original signal of color and vein are formed from RGB color and gray level co-occurrence matrix by order of column prior.Then,these two signals are measured by the blocked compressive sensing method,and measurement vectors are obtained which representing the color and texture features.Secondly,we reconstruct the image by blocks using the MSAMP(Meticulous Sparsity Adaptive Matching Pursuit) algorithm,and calculate the difference and sparse value between the original blocked signals.Finally,we calculate the overall image similarity,and focus on estimating the sparseness of measurement difference.Because it does no need to recover the original signal precisely,so it can reduce the number of iteration and accelerate the retrieval speed.Simulation results show that the retrieval speed and retrieval precision about this image retrieval algorithm based on compressive sensing signal have higher performance.关键词：compressive sensing;image retrieval;veins feature;color feature;adaptive matching pursuit2|1777|2更新时间：2025-07-16
- 摘要：Software change is a fundamental ingredient of software maintenance.Changes made to software will inevitably cause some unpredicted and undesirable effects to other parts of the software.Software change impact analysis (CIA) is a technique for identifying the potential consequences of a change.It is found that CIA is very helpful in many aspects,including software maintenance,regression testing,etc.This paper attempts to give a survey of CIA techniques in recent years,and aims at providing references for developers to choose suitable CIA techniques.In this paper,we first introduce five classification approaches for CIA techniques.Then,we discuss some future challenges and directions for CIA in its fundamental theories,tools,evaluation,scalability,traceability,etc.关键词：software change;change impact analysis;survey2|1752|1更新时间：2025-07-16
- 摘要：Attack graph analysis is an effective tool for analyzing network vulnerability,representing the process that attackers penetrate networks using the complex interdependence between vulnerabilities and network configurations.In this paper,we prove the equivalence of the optimization security measure problem and the weighted hitting set problem,and present the method which converts the optimization security measure problem to the weighted hitting set problem on the premise of not increasing the problem scale.Theoretical analysis and experiments show that the method based on conversion has better performance than the method based on critical attack sets in converging to the global optimal solution.关键词：attack graph;optimization security measure;conversion;global optimal solution2|1329|3更新时间：2025-07-16
- 摘要：The rational secret sharing is an intersection direction between the traditional secret sharing and game theory.In the rational secret sharing scheme,the selfishness maybe impels rational players to deviate from the protocols so as to influence the fairness of scheme.In the existing threshold rational secret sharing schemes,the fairness of (2,2) rational secret sharing scheme,which is a special case,is hard to be realized,especially implementing on the asynchronous communication channel.To achieve fairness of (2,2) rational secret sharing over the asynchronous communication channel,this paper firstly analyzes rational players' utility by simultaneously discussing their short-term interest and long-term interest.Then through illustrating rational players' available actions and belief systems,and computing their expected utilities with the dynamic games of incomplete information,the perfect Bayesian equilibrium for reconstruction phase of (2,2) rational secret sharing is studied.Furthermore,combining with the VCG(Vickrey-Clarke-Groves)mechanism of design theory,the incentive compatibility mechanism,which is named recording interaction,is designed to restrict the behavior of rational players.Consequently,the fair (2,2) rational secret sharing scheme is presented,which does not need the dealer to keep on-line over the asynchronous communication channel.关键词：rational secret sharing;incomplete information;belief system;perfect Bayesian equilibrium;mechanism design2|1431|4更新时间：2025-07-16
- 摘要：Through the sputtering power analysis of field-emission electrons which hit on the end surface of positive electrode in single discharging pulse,the material wear mechanism of positive electrical discharging machining(short in EDM)process was studied,and theoretical prediction equations of maximum and minimum material wear ratio of electrodes were deduced too.A series of single-hole EDM experiments were designed and the experimental results show that,the mean discharging power produced by the electrode of copper is nearly 75 times higher than that of A3# steel when the other processing parameters are the same,and material wear ratio of the former is almost 10 times than that of the latter;both the machining efficiency and the material wear ratio of electrode increase with the improvement of valid work time and the pulse discharging power,and the increasing degree of machining efficiency is more significant than that of the material wear ratio of tool electrode.关键词：electrical discharge machining;material wear of electrode;work energy;electron sputtering2|1432|0更新时间：2025-07-16
- 摘要：RFID reader system which is based on passive RFID tags typically takes the "zero-IF" receiving solution.This solution will cause carrier leakage between the sender and receiver of RF signal.This carrier leakage will cause two undesirable results:one is that it's easier for the front of receiver to become saturated which will reduce the communication distance of system;the other is that the "DC offset" phenomenon will be caused then the bit error rate of system will be increased.Therefore,two measures are proposed in this paper to solve this problem.Firstly,the carry cancellation technology is be applied in the RFID reader at 2.45GHz band,and the microstrip circuit is used in the design.By simulation and prototyping test,the results of leakage power of improved circulator are given.Secondly,a wideband and high-gain DC amplifier with DC feedback loop is proposed,it is used as the baseband signal amplifier without distortion and it can compensate the DC component brought by the mixer automatically.Thus,it will reduce the bit error rate of RFID readers when the electronic tags are readed.关键词：RFID reader;zero IF;carrier leakage;carrier cancellation technology;DC offset;DC feedback loop2|1903|0更新时间：2025-07-16
- 摘要：A novel generation method of ISAR (Inverse Synthetic Aperture Radar)decoy is presented based on coherent multiplication modulated jamming.By processing the modal image by 2-D FFT(Fast Fourier Transform),jamming signal can be formed offline and then modulated on interceptive radar signal to generate a vivid decoy with arbitrary shape and size.After the theory of coherent multiplication modulated jamming is expounded,a theoretical study is carried out to analyze this generation method.On this basis,more analyses are given the jamming parameters,and the key factor of scale zoom and the reliance on reconnaissance is presented.At last,the simulation demonstrates that the above method is feasible and effective.关键词：coherent multiplication modulated jamming;linear frequency modulated signal;inverse synthetic aperture radar;scale zoom2|1384|5更新时间：2025-07-16
- 摘要：Under the framework of IFS(Intuitionistic Fuzzy Sets),aiming at the situation that targets' attributes are interval value,the weights are totally unknown,and decision-makers have preference information,a threat assessment method with uncertain attribute weight based on intuitionistic fuzzy multi-attribute decision is proposed.Firstly,based on the above-mentioned problem,intuitionistic fuzzy interval judgment matrix is set up,and a standard interval value index processing method is put forward;secondly,by analyzing the target attribute,attribute weight,and decision-makers' authority degree in project,the preference project model in group decision making is finally constructed;thirdly,according to the attribute's variety character in interval value,the definition of intuitionistic fuzzy interval value's similarity and ideal resolve is given,and the optimization attribute weight restriction model is built up;lastly,some typical threat assessment examples are cited to verify that the method can reflect the influence of both subjective and objective information,which can avoid the deviation caused by sensor invalidation,outside environment's effect,or decision-makers' subjective experience.Finally,the superiority of the method is proved by the threat assessment of some typical targets.关键词：intuitionistic fuzzy sets;interval judgment matrix;multiple-attribute decision;threat assessment2|1643|31更新时间：2025-07-16
- 摘要：An anti-collision scheme for the radio-frequency identification system is used to guarantee that all the tags in the reader field are identified.This paper develops an efficient anti-collision algorithm based on the tree search algorithms to improve the performance of the RFID system.The improvement is achieved by means of the manner of the requests' building and the mapping of collision bits.Taking into account the average request cycle and the length of transmitted data,this scheme has been designed to complete identifying all tags.The simulation results demonstrate the effectiveness of the proposed scheme in terms of time complexity,communication overhead and energy efficiency.关键词：radio frequency identification(RFID);anti-collision;mapped data;energy efficiency2|1673|4更新时间：2025-07-16
- 摘要：The electromagnetic performance of active phased array antenna (APAA) is obviously degraded because of plane distortion errors which include random errors generated in antenna plane assembling and structural distortion resulting from vibration,thermal power consumption,etc.It has become one of the difficulties to develop high-performance active phased array antennas.By introducing the plane distortion errors into the antenna pattern function as an additional phase factor,the coupled structural-electromagnetic model between the plane distortion errors and the performance of the planar rectangular APAA is established.The influence of the electromagnetic performances of antenna with the plane distortion errors is analyzed with the valueful results.关键词：active phased array antenna;distortion error;electromagnetic performance;coupled analysis2|1595|4更新时间：2025-07-16
- 摘要：A major component of flow cytometry data analysis involves gating,which is the process of identifying homogeneous groups of cells.As manual gating is error-prone,non-reproducible,nonstandardized,and time-consuming,we propose a flexible statistical model-based clustering approach to identifying cell populations in flow cytometry data based on skew t-mixture models.This approach,which employs a finite mixture model with the density function of skew t-distribution,estimates parameters via an expectation maximization algorithm.Data analysis from two different experiments prove that the model-based clustering methods give better results in terms of robustness against outliers than non model-based clustering methods.Compared to the Gaussian mixture models,skew normal mixture models and t-mixture models,the skew t-mixture models have more flexibility in clustering symmetric data and leads to lower misclassification rates when handling highly asymmetric data.关键词：mixture models;skew t-distribution;flow cytometry;EM algorithm2|1645|3更新时间：2025-07-16
- 摘要：We first propose the hierarchical fault diagnosis algorithm-HFD algorithm for data center network.According to the structural characteristics of data center network,the algorithm divides the network system into two logical layers.On the first layer,we perform multiple simplest tests on the "basic unit groups",which will be divided into "relative fault unit groups" and "relative fault-free unit groups".On the second layer,combining the "positive-negative correlation" idea firstly proposed in this paper and the "absolute fault base" idea previously proposed by the authors,we design the AD-FAFD algorithm for mutual test and diagnosis among units.The simulation result shows that HFD algorithm reduces the time complexity effectively while keeping good diagnosis accuracy.关键词：system-level fault diagnosis;data center network;HFD algorithm;positive-negative correlation;FAFD algorithm2|1473|2更新时间：2025-07-16
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