A class of Bayes-optimal two-stage screens

Items are characterized by a set of attributes (T) and a collection of covariates (X) associated with those attributes. We wish to screen for acceptable items (T ∈ C_T), but T is expensive to measure. We envisage a two-stage screen in which observation of X_ is used as a filter at the first stage to sentence most items. The second stage involves the observation of T for those items for which the first stage is indecisive. We adopt a Bayes decision-theoretic approach to the development of optimal two-stage screens within a general framework for costs and stochastic structure. We also consider the important question of how much screens need to be modified in the light of resource limitations that bound the proportion of items that can be passed to the second stage. © 1996 John Wiley & Sons, Inc.     

多重结构神经网络在平台罗经故障诊断中的应用

提出了基于层次分类诊断模型的多重结构神经网络 (MNN)在平台罗经故障诊断中的应用方法 ,并对其温控子系统的人工神经网络 (ANN)进行了Matlab实现     

Probabilistic partial set covering problems

In this article, we consider a situation in which a group of facilities need to be constructed in order to serve a given set of customers. However, the facilities cannot guarantee an absolute coverage to any of the customers. Hence, we formulate this problem as one of maximizing the total service reliability of the system subject to a budgetary constraint. For this problem, we develop and test suitable branch-and-bound algorithms and study the effect of problem parameters on solution difficulty. Some generalizations of this problem are also mentioned as possible extensions.     

Linear search with bounded resources

A point is placed at random on the real line according to some known distribution F, and a search is made for this point, beginning at some starting points s on the line, and moving along the line according to some function x(t). The objective of this article is to maximize the probability of finding the point while traveling at most d units. Characterizations of simple optimal searches are found for arbitrary distributions, for continuous distributions with continuous density everywhere (e.g., normal, Cauchy, triangular), and for continuous distributions with density which is continuous on its support (e.g., exponential, uniform). These optimal searches are also shown to be optimal for maximization of the expected number of points found if the points are placed on the line independently from a known distribution F.     

Economic design of sampling plans with multi-decision alternatives

For situations where there are several markets with different profit-cost structures, economic attributes sampling plans are developed for determining the market to ship the lot to. Two sampling plans are considered; the fixed-size sampling plan with several levels of acceptance numbers, and the inverse sampling plan with several levels of sample sizes. Linear profit models are constructed which involve four profit/cost components; profit from a conforming item, inspection cost, replacement cost, and cost from an accepted nonconforming item. For fixed-size and inverse sampling plans, methods of finding optimal sampling plans are presented and examples with beta-binomial prior distributions are given.     

A periodic maintenance model with used equipment and random minimal repair

The maintenance strategy considered in this article is in the class of block replacement policies. The working unit is replaced by new ones at instants T,2T,3T,… independently of the age and state of the unit. If a failure occurs between these instants, the random repair cost is evaluated. If it is smaller than a predetermined control limit then a minimal repair is carried out. Otherwise the unit is replaced by a used unit. The performance of this maintenance strategy is evaluated in terms of average total cost per time unit over an infinite time span. The mathematical model is defined and several analytical results are obtained. A computer program has been written, which solves the mathematical problem, and some examples are given for the cases where the underlying life distribution is gamma, Weibull or truncated normal.     

Optimal layered search

This article investigates the problem of planning an optimal layered search for a stationary target. A search is layered if it assigns each point in the search space an integer number of glimpses or looks. General necessary and sufficient conditions and an existence theorem are obtained. The special case in which the initial target distribution is bivariate normal is considered in detail.     

A model for critical crack size estimation in fatigue failure of gun barrels

With repeated firing, fatigue cracks are produced in a gun barrel, and the barrel is no longer useful when a crack reaches a critical size. The initial crack size and the critical crack size, as well as the number of firings producing the critical crack size, may be considered as random variables. Assuming a proportional damage model for crack growth, a method for estimating the critical crack size distribution is presented. From these results, an estimate of the barrel life, or the residual barrel life once a crack of a given size is measured, can be obtained.