Ke Hongfa

Grey Distance Information Approach for Parameter Estimation of Small Samples

Parameter estimation of small samples is a valuable research problem in various test domains. Because of the complexity in determining the probability distribution, it is difficult to use a traditional probability theory to process the samples and assess the degree of uncertainty. Based on the grey relational theory and the norm theory, the grey distance information approach for small-sample processing is proposed. The correlative problems, including the definitions and the characteristics of the grey distance information quantity and the average grey distance information quantity, the point estimation and the confidence interval estimation algorithm, and the acceptance and rejection criteria of the samples, are also proposed. In addition, the information whitening ratio is introduced to select the weight algorithm and to compare the different sample sets. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective.

Data processing of small samples based on grey distance information approach

Abstract Data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is dificult and complex to determine the probability distribution of small samples, it is dificult to use the traditional probability theory to process the samples and assess the degree of uncertainty. Using the grey relational theory and the norm theory, the grey distance information approach, which is based on the grey distance information quantity of a sample and the average grey distance information quantity of the samples, is proposed in this article. The deffnitions of the grey distance information quantity of a sample and the average grey distance information quantity of the samples, with their characteristics and algorithms, are introduced. The correlative problems, including the algorithm of estimated value, the standard deviation, and the acceptance and rejection criteria of the samples and estimated results, are also proposed. Moreover, the information whitening ratio is introduced to select the weight algorithm and to compare the difierent samples. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective.

A novel situation analysis method of electronic countermeasure based on unascertained rational number

Quantitative situation analysis and assessment of electronic countermeasure is one of the most important goals of researches on mission programming of electronic countermeasure equipment. But most references focused on total assessment of countermeasure situation, instead of specific analysis. A novel situation analysis method of electronic countermeasure that is based on unascertained rational number was proposed in the paper. The description model of situation data and the specific analysis model were introduced, which was presented by the simulation of the situation analysis of electronic jamming scene. The results show that the proposed method is rational and valid. It can analyze both countermeasure situation of electronic equipment concretely and quantitatively.

CBR-based grey relational identification method for technical risks in equipment tests

Considering that poor/limited data about technical risks is obtained in equipment tests, its not a good idea to use existing methods to identify and deal with new risks. In this paper, a four-step method which combining case based reasoning and grey relational analysis is proposed. By utilizing prior information, a case library, in which every case is described in details representing for certain kind of technical risk, is built. With a new kind of risk symptom rising, the previous library is retrieved to find the case with largest conditional degree, and then a recommendation solution for the new risk symptom is given according to the solution which is taken to solve the risk with largest conditional degree mentioned above. The knowledge comes into being in the process of dealing with the new risk symptom, is combined into a new case, by creating or modifying the existing case. At last, the new case is stored in the case library. A practical example is provided. The results show that the CBR-based grey relational technical risk identification method is sensible and feasible.

Study on Big Data Development of Test and Evaluation of Weapon and Equipment

The big data development problem of test and evaluation of weapon and equipment is studied. Firstly, the concept of big data and research status in the military domain are summarized. And the concept of big data of test and evaluation of weapon and equipment is given. Secondly, the development demands and status of big data of test and evaluation of weapon and equipment are analyzed. Then, the development contents of big data of test and evaluation of weapon and equipment, such as data collection, big data calculation, data mining, and et al, are introduced. Finally, the key development problems of big data of test and evaluation of weapon and equipment, such as theory system, technique system, operation system, and et al, are proposed emphasisly.

Grey Relational Evaluation of Electronic Equipment Effectiveness Based on Ideal Reference Sequence

Evaluating the combat effectiveness of electronic equipment is an important research task. Due to the incomplete information, the data which is used for effectiveness evaluation is regarded as the uncertain grey number according to the grey system theory. Based on the positive and negative ideal sequence, a grey relational analysis model for the combat effectiveness evaluation of electronic equipment is introduced. And the relevant grey relational analysis algorithm is established also. The effectiveness value is acquired through an optimal function which maximizes the combat effectiveness of the equipment. Then the evaluation distinguishing coefficient is defined to compare the effectiveness evaluation model and algorithm. The simulation example shows the rationality and feasibility of the proposed method. This method can accurately rank the combat effectiveness of electronic equipment so that the best equipment can be chosen