Reduction rules-based search algorithm for opportunistic replacement strategy of multiple life-limited parts

The opportunistic replacement of multiple Life-Limited Parts （LLPs） is a problem widely existing in industry. The replacement strategy of LLPs has a great impact on the total maintenance cost to a lot of equipment. This article focuses on finding a quick and effective algorithm for this problem. To improve the algorithm efficiency, six reduction rules are suggested from the perspectives of solution feasibility, determination of the replacement of LLPs, determination of the maintenance occasion and solution optimality. Based on these six reduction rules, a search algorithm is proposed. This search algorithm can identify one or several optimal solutions. A numerical experiment shows that these six reduction rules are effective, and the time consumed by the algorithm is less than 38 s if the total life of equipment is shorter than 55000 and the number of LLPs is less than 11. A specific case shows that the algorithm can obtain optimal solutions which are much better than the result of the traditional method in 10 s, and it can provide support for determining tobe-replaced LLPs when determining the maintenance workscope of an aircraft engine. Therefore, the algorithm is applicable to engineering applications concerning opportunistic replacement of multiple LLPs in aircraft engines.

Rough Set Based K-Exception Approach to Approximate Rule Reduction

There are rules refering to infrequent instances after the procession of attribute reductionand value reduction with traditional methods.A rough set RS based k-exception approach (RSKEA) torule reduction is presented.Its main idea lies in a two-phase RS based rule reduction.An ordinarydecision table is attained through general method of RS knowledge reduction in the first phase.Then a k-exception candidate set is nominated according to the decision table.RS rule reduction is employed forthe reformed source data set,which remove all the instances included in the k-exception set.We apply theapproach to the automobile database.Results show that it can reduce the number and complexity of ruleswith adjustable conflict rate,which contributes to approximate rule reduction.

Applying Petri-Net-Based Reduction Approach for Verifying the Correctness of Workflow Models

The correctness of workflow models is one of the major challenges in context of workflow analysis. The aim of this paper is to provide an improved Petri net-based reduction approach for verifying the correctness of workflow models. To the end, how to represent well-behaved building blocks and control structures of business processes by Petri nets is given at first, and then how to build well-structured process nets is presented. According to the structural characteristics of well-structured process nets, a set of legacy reduction rules are improved and extended, and then a complete Petri-net-based verification approach is proposed. The sound ness and the complexity with polynomial time for the improved re duction method are also proven.

Reduction techniques of workflow verification and its implementation

Many workflow management systems have emerged in recent years, but few of them provide any form of support for verification. This frequently results in runtime errors that need to be corrected at prohibitive costs. In Ref.[1], a few reduction rules of verifying workflow graph are given. After analyzing the reduction rules, the overlapped reduction rule is found to be inaccurate. In this paper, the improved reduction rules are presented and the matrix-based implementing algorithm is given, so that the scope of the verification of workflow is expanded and the efficiency of the algorithm is enhanced. The method is simple and natural, and its implementation is easy too.

A New Safety Assessment Method Based on Belief Rule Base With Attribute Reliability

Safety assessment is one of important aspects in health management.In safety assessment for practical systems,three problems exist:lack of observation information,high system complexity and environment interference.Belief rule base with attribute reliability(BRB-r)is an expert system that provides a useful way for dealing with these three problems.In BRB-r,once the input information is unreliable,the reliability of belief rule is influenced,which further influences the accuracy of its output belief degree.On the other hand,when many system characteristics exist,the belief rule combination will explode in BRB-r,and the BRB-r based safety assessment model becomes too complicated to be applied.Thus,in this paper,to balance the complexity and accuracy of the safety assessment model,a new safety assessment model based on BRB-r with considering belief rule reliability is developed for the first time.In the developed model,a new calculation method of the belief rule reliability is proposed with considering both attribute reliability and global ignorance.Moreover,to reduce the influence of uncertainty of expert knowledge,an optimization model for the developed safety assessment model is constructed.A case study of safety assessment of liquefied natural gas(LNG)storage tank is conducted to illustrate the effectiveness of the new developed model.

Optimization of fault management system in power plants based on DD-RCM and TPN

A method of optimizing the fault management system in power plants based on DD-RCM （resultchain based modeling for digital developing） and TPN （temporal Petri net） is proposed. First, the model of the fault management system was set using DD-RCM. Then, it was transformed to the temporal Petri net model by corresponding rules. Secondly, relationships among all the activities, such as choice, conflict, synchronization and concurrency, were confirmed according to the Petri net model and described employing the reengineering algorithm of incidence matrix. Thirdly, the Petri net model was reduced by combining reduction rules and conflict, synchronization relationships to optimize the fault management system in power plants. Finally, the functionality of the reduced net was proved by the temporal logic of the temporal Petri net.

Evaluation Model for Scientific Quality Based on Rough Sets and Its Empirical Study

By analyzing the questionnaires recollected from 74 different government departments in Chengdu, China, an evaluation model for scientific quality of civil servants was developed with the rough set theory. In the empirical study, a series of important rules were given to help to check and forecast the degree of the scientific quality of civil servants by using the reduction algorithm, and the total accuracy of prediction was 93.2%.

Reduction Method for Reachability Analysis of Petri Nets

Reachability analysis is an important approach for acquiring Petri net (PN) properties. The reachability tree and the solution of the state equation are two commonly used methods for reachability analysis, but they can result in state explosion and spurious solutions in some cases. As a significant complementary method, the PN reduction technique simplifies the reachability analysis by reducing the net size while preserving the reachability. This paper introduces several useful reduction rules and defines a reduction process for the analysis of reachability which is easy to understand and implement. Some examples are given to explain the method to solve the reachability problem. The analysis shows that the proposed reduction method preserves the visualization feature of PN and can be easily used.

Efficient multi-event monitoring using built-in search engines

Users of the internet often wish to follow certain news events, and the interests of these users often overlap. General search engines （GSEs） cannot be used to achieve this task due to incomplete coverage and lack of freshness. Instead, a broker is used to regularly query the built-in search engines （BSEs） of news and social media sites. Each user defines an event profile consisting of a set of query rules called event rules （ERs）. To ensure that queries match the semantics of BSEs, ERs are transformed into a disjunctive normal form, and separated into conjunctive clauses （atomic event rules, AERs）. It is slow to process all AERs on BSEs, and can violate query submission rate limits. Accordingly, the set of AERs is reduced to eliminate AERs that are duplicates, or logically contained by other AERs. Five types of event are selected for experimental comparison and analysis, including natural disasters, accident disasters, public health events, social security events, and negative events of public servants. Using 12 BSEs, 85 ERs for five types of events are defined by five users. Experimental comparison is conducted on three aspects： event rule reduction ratio, number of collected events, and that of related events. Experimental results in this paper show that event rule reduction effectively enhances the efficiency of crawling.