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An integral equation for the second moment function of a geometric process and its numerical solution
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In this article, an integral equation satisfied by the second moment function M2(t) of a geometric process is obtained. The numerical method based on the trapezoidal integration rule proposed by Tang and Lam for the geometric function M(t) is adapted to solve this integral equation. To illustrate the numerical method, the first interarrival time is assumed to be one of four common lifetime distributions, namely, exponential, gamma, Weibull, and lognormal. In addition to this method, a power series expansion is derived using the integral equation for the second moment function M2(t), when the first interarrival time has an exponential distribution. 相似文献
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某新型飞机武器控制系统故障诊断过程复杂,故障征兆和故障原因之间存在着许多不确定因素,精确定位故障存在许多困难.针对这种情况,提出了基于模糊神经网络,研究了模糊神经网络技术在武器控制系统故障诊断领域的应用,并根据系统本身的特点,提出了诊断和算法模型.在此基础上,研制出武器控制系统检查仪,对该方法作了验证.结果表明:该方法是可行和有效的. 相似文献
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《防务技术》2020,16(1):208-216
As the generalization of intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS), the q-rung orthopair fuzzy set (q-ROFS) has emerged as a more meaningful and effective tool to solve multiple attribute group decision making (MAGDM) problems in management and scientific domains. The MABAC (multi-attributive border approximation area comparison) model, which handles the complex and uncertain decision making issues by computing the distance between each alternative and the bored approximation area (BAA), has been investigated by an increasing number of researchers more recent years. In our article, consider the conventional MABAC model and some fundamental theories of q-rung orthopair fuzzy set (q-ROFS), we shall introduce the q-rung orthopair fuzzy MABAC model to solve MADM problems. at first, we briefly review some basic theories related to q-ROFS and conventional MABAC model. Furthermore, the q-rung orthopair fuzzy MABAC model is built and the decision making steps are described. In the end, An actual MADM application has been given to testify this new model and some comparisons between this novel MABAC model and two q-ROFNs aggregation operators are provided to further demonstrate the merits of the q-rung orthopair fuzzy MABAC model. 相似文献
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