舰船装备保障性工程研究

介绍舰船装备保障性工程的定义和内涵，分析舰船装备全寿期各阶段保障性工程的任务和工作内容，提出实施保障性工程的6个步骤及开展舰船装备保障性工程的措施和建议。     

基于能力的装备保障性能研究

从装备各自的设计特性角度出发而形成的武器装备发展思路,未能考虑能力需求,也未从能力的角度来评价研制的最终成果,造成装备部署后,形成的作战能力和保障能力滞缓。提出了保障能力的定义和内涵,并研究提出以能力需求为出发点,以"联合作战方案—使命任务—保障能力—保障性能—关键技术突破—能力设计实现—能力评价—能力发挥和保持"为主线,用形成的能力来评价研制成果的保障能力形成过程,同时提出了保证装备尽快形成保障能力的对策与措施。     

Research on Equipment Support Activity Process Simulation Based on Monte Carlo Method

The influencing factors of the equipment support activity process have the characteristics of nonlinearity, high dimension, many constraints, random uncertainty and fuzzy uncertainty. Monte Carlo method can solve the above problems commendably. This paper analyzes the main equipment support activity process and establishes the sampling plan and simulation model of the medium maintenance process based on Monte Carlo method, and the simulation result verifies a fact that the medium maintenance time can be effectively reduced when parallel operation on some procedures is used. It has a practical value and can give good advice to achieve the capability of equipment supportability.     

舰船装备保障性系统工程的新观点

从用户角度出发,运用系统工程的理论、技术和方法,重新认识舰船保障性并提出一些新的观点。通过研究得出结论,为了达到用户的保障性目标和要求,使设计的舰船装备是可保障的,必须在舰船的全寿期中全面实施保障性系统工程。     

读“总体者，集大成也”一文引起的思考

读"总体者,集大成也"一文后针对"总体"的理解和定义,以及关于"能力"的界定和如何实现"能力集成"等方面进行了研究和探讨.     

舰船保障性工程概述

通过保障性与保障性工程的介绍 ,阐述了舰船保障性工程的定义和内涵 ,提出实施保障性工程的 6个步骤 ,并分析舰船寿命期各阶段保障性的任务和工作内容 ,提出开展舰船保障性工程的建议。     

Hybrid Reliability Parameter Selection Method Based on Text Mining,Frequent Pattern Growth Algorithm and Fuzzy Bayesian Network

Reliability parameter selection is very important in the period of equipment project design and demonstration. In this paper, the problem in selecting the reliability parameters and their number is proposed. In order to solve this problem, the thought of text mining is used to extract the feature and curtail feature sets from text data firstly, and frequent pattern tree (FPT) of the text data is constructed to reason frequent item-set between the key factors by frequent patter growth (FPG) algorithm. Then on the basis of fuzzy Bayesian network (FBN) and sample distribution, this paper fuzzifies the key attributes, which forms associated relationship in frequent item-sets and their main parameters, eliminates the subjective influence factors and obtains condition mutual information and maximum weight directed tree among all the attribute variables. Furthermore, the hybrid model is established by reason fuzzy prior probability and contingent probability and concluding parameter learning method. Finally, the example indicates the model is believable and effective.