基于D-S理论的网格信任模型

信任机制已经被广泛地应用于网格计算。基于网格节点对于资源提供的反馈评价,提出了一种基于Dempster-Shafer证据理论的网格信任模型。该模型给出信任函数、似然函数、信任损失的表示方法,并在此基础上建立了对于资源提供者的信任监测机制及防止资源使用者共同串谋与诋毁的方法。

基于视觉的自主车道路检测技术研究

针对结构化道路检测中基于单一特征的检测易受影响,非结构化道路检测算法对多种类型的非标准道路缺乏适应性的问题,分别提出了一种基于D-S证据理论的多视觉特征融合的车道线检测方法和一种基于增量模糊支持向量机(IFSVM)的非结构化道路在线学习检测方法;选取梯度幅度等检测算子分别设计基本概率分配函数,根据建立的分段线性道路模型进行求解,FSVM分类器通过从前先的检测结果中学习,在耗费少量计算时间与内存空间的情况下,不断再训练以增强分类器的性能;实验结果表明,该算法比单纯利用图像的边缘或颜色等特征进行道路检测具有更高的可靠性,对复杂环境下的道路检测具有较强的鲁棒性和较强的抗干扰能力。

INTELLIGENT FUSION FOR AEROENGINE WEAR FAULT DIAGNOSIS

Four common oil analysis techniques, including the ferrography analysis （FA）, the spectrometric oil analysis （SOA）, the particle count analysis （PCA）, and the oil quality testing （OQT）, are used to implement the military aeroengine wear fault diagnosis during the test drive process. To improve the precision and the reliability of the diagnosis, the aeroengine wear fault fusion diagnosis method based on the neural networks （NN） and the Dempster-Shafter （D-S） evidence theory is proposed. Firstly, according to the standard value of the wear limit, original data are pre-processed into Boolean values. Secondly, sub-NNs are established to perform the single diagnosis, and their training samples are dependent on experiences from experts. After each sub-NN is trained, diagnosis results are obtained. Thirdly, the diagnosis results of each sub-NN are considered as the basic probability allocation value to faults. The improved D-S evidence theory is applied to the fusion diagnosis, and the final fusion results are obtained. Finally, the method is verified by a diagnosis example.

Structural damage detection method based on information fusion technique

Multi-source information fusion （MSIF） is imported into structural damage diagnosis methods to improve the validity of damage detection. After the introduction of the basic theory, the function model, classifications and mathematical methods of MSIF, a structural damage detection method based on MSIF is presented, which is to fuse two or more damage character vectors from different structural damage diagnosis methods on the character-level. In an experiment of concrete plates, modal information is measured and analyzed. The structural damage detection method based on MSIF is taken to localize cracks of concrete plates and it is proved to be effective. Results of damage detection by the method based on MSIF are compared with those from the modal strain energy method and the flexibility method. Damage, which can hardly be detected by using the single damage identification method, can be diagnosed by the damage detection method based on the character-level MSIF technique. Meanwhile multi-location damage can be identified by the method based on MSIF. This method is sensitive to structural damage and different mathematical methods for MSIF have different preconditions and applicabilities for diversified structures. How to choose mathematical methods for MSIF should be discussed in detail in health monitoring systems of actual structures.

Application of data fusion method to fault diagnosis of nuclear power plant

The work condition of nuclear power plant (NPP) is very bad, which makes ithas faults easily. In order to diagnose (he faults real time, the fusion diagnosis system is built.The data fusion fault diagnosis system adopts data fusion method and divides the fault diagnosisinto three levels, which are data fusion level, feature level and decision level. The feature leveluses three parallel neural networks whose structures are the same. The purpose of using neuralnetworks is mainly to get basic probability assignment ( BPA) of D-S evidence theory, and the neuralnetworks in feature level are used for local diagnosis. D-S evidence theory is adopted to integratethe local diagnosis results in decision level. The reactor coolant system is the study object andwe choose 2# steam generator U-tubes break of the reactor coolant system as a diagnostic example.The experiments prove that the fusion diagnosis system can satisfy the fault diagnosis requirementof complicated system, and verify that the fusion fault diagnosis system can realize the faultdiagnosis of NPP on line timely.

EARLY WARNING MODEL OF NETWORK INTRUSION BASED ON D-S EVIDENCE THEORY

Application of data fusion technique in intrusion detection is the trend of next- generation Intrusion Detection System (IDS). In network security, adopting security early warn- ing technique is feasible to effectively defend against attacks and attackers. To do this, correlative information provided by IDS must be gathered and the current intrusion characteristics and sit- uation must be analyzed and estimated. This paper applies D-S evidence theory to distributed intrusion detection system for fusing information from detection centers, making clear intrusion situation, and improving the early warning capability and detection efficiency of the IDS accord- ingly.

Fault diagnosis method of hydraulic system based on fusion of neural network and D-S evidence theory

According to fault type diversity and fault information uncertainty problem of the hydraulic driven rocket launcher servo system（HDRLSS） , the fault diagnosis method based on the evidence theory and neural network ensemble is proposed. In order to overcome the shortcomings of the single neural network, two improved neural network models are set up at the com-mon nodes to simplify the network structure. The initial fault diagnosis is based on the iron spectrum data and the pressure, flow and temperature（PFT） characteristic parameters as the input vectors of the two improved neural network models, and the diagnosis result is taken as the basic probability distribution of the evidence theory. Then the objectivity of assignment is real-ized. The initial diagnosis results of two improved neural networks are fused by D-S evidence theory. The experimental results show that this method can avoid the misdiagnosis of neural network recognition and improve the accuracy of the fault diagnosis of HDRLSS.

Full Diversity Reception Based on Dempster-Shafer Theory for Network Coding with Multiple-Antennas Relay

In this paper,a two-way relay system which achieves bi-directional communication via a multiple-antenna relay in two time slots is studied.In the multiple access(MA) phase,the novel receive schemes based on Dempster-Shafer(D-S) evidence theory are proposed at the relay node.Instead of traditional linear detection,the first proposed MIMO-DS NC scheme adopts D-S evidence theory to detect the signals of each source node before mapping them into network-coded signal.Moreover,different from traditional physical-layer network coding(PNC) based on virtual MIMO model,the further proposed MIMO-DS PNC comes from the vector space perspective and combines PNC mapping with D-S theory to obtain network-coded signal without estimating each source node signal.D-S theory can appropriately characterize uncertainty and make full use of multiple evidence source information by Dempster's combination rule to obtain reliable decisions.In the broadcast(BC) phase,the space-time coding(STC) and antenna selection(AS) schemes are adopted to achieve transmit diversity.Simulation results reveal that the STC and AS schemes both achieve full transmit diversity in the BC phase and the proposed MIMO-DS NC/PNC schemes obtain better end-to-end BER performance and throughputs compared with traditional schemes with a little complexity increasing and no matter which scheme is adopted in the BC phase,MIMO-DS PNC always achieves full end-to-end diversity gain as MIMO-ML NC but with a lower complexity and its throughput approaches the throughput of MIMO-ML NC in high SNR regime.

D-S Evidence Theory Based Trust Ant Colony Routing in WSN

This paper proposes a trust ant colony routing algorithm by introducing a node trust evaluation model based on the D-S evidence theory into the ant colony routing protocol to improve the security of wireless sensor networks. To reduce the influence of conflict evidences caused by malicious nods, the consistent intensity is introduced to preprocess conflict evidences before using the D-S combination rule to improve the reliability of the D-S based trust evaluation. The nodes with high trust values will be selected as the routing nodes to insure the routing security, and the trust values are used as heuristic functions of the ant colony routing algorithm. The simulation tests are conducted by using the network simulator NS2 to observe the outcomes of performance metrics of packets loss rate and average end-to-end delay etc. to indirectly evaluate the security issue under the attack of inside malicious nodes. The simulation results show that the proposed trust routing algorithm can efficiently resist malicious attacks in terms of keeping performances of the average end-to-end delay, the throughtput and the routing packet overhead under attacking from malicious nodes.

A Kind of Information Processing Method in Linguistic-Value Appraisement of Enterprise Human Resource

Linguistic-value appraisement extensively exists in artificial intelligence and social system. In the appraisement of enterprise human resource, there is a great amount of linguistic-value information. In order to improve the reasonability of the result of appraisement of enterprise human resource, we need to study the methods for processing the linguistic-value information. In this paper, a 2-stages method is proposed for processing the linguistic-value appraisement of enterprise human resource. At the first stage, we choose the experts familiar with the related field according to the appraisement goal and problem. At the second stage, we combine the appraisement results by D-S evidence theory or LOWA operator according to the nature of linguistic variable.