ER rule classifier with an optimization operator recommendation

It is difficult for many classic classification methods to consider expert experience and classify small-sample datasets well. The evidential reasoning rule (ER rule) classifier can solve these problems. The ER rule has strong processing and comprehensive analysis abilities for diversified mixed information and can solve problems with expert experience effectively. Moreover, the initial parameters of the classifier constructed based on the ER rule can be set according to empirical knowledge instead of being trained by a large number of samples, which can help the classifier classify small-sample datasets well. However, the initial parameters of the ER rule classifier need to be optimized, and choosing the best optimization algorithm is still a challenge. Considering these problems, the ER rule classifier with an optimization operator recommendation is proposed in this paper. First, the initial ER rule classifier is constructed based on training samples and expert experience. Second, the adjustable parameters are optimized, in which the optimization operator recommendation strategy is applied to select the best algorithm by partial samples, and then experiments with full samples are carried out. Finally, a case study on a turbofan engine degradation simulation dataset is carried out, and the results indicate that the ER rule classifier has a higher classification accuracy than other classic classifiers, which demonstrates the capability and effectiveness of the proposed ER rule classifier with an optimization operator recommendation.

A NNIA Scheme for Timetabling Problems

This paper presents a memetic multiobjective optimization algorithm based on NNIA for examination timetabling problems. In this paper, the examination timetabling problem is considered as a two-objective optimization problem while it is modeled as a single-objective optimization problem generally. Within the NNIA framework, the special crossover operator is utilized to search in the solution space; two local search techniques are employed to optimize these two objectives and a diversity-keeping strategy which consists of an elitism group operator and an extension optimization operator to ensure a sufficient number of solutions in the pareto front. The proposed algorithm was tested on the most widely used uncapacitated Carter benchmarks. Experimental results prove that the proposed algorithm is a competitive algorithm.

Integrated Process and Control System Model for Product Quality Control - Application to a Polypropylene Plant

In the near future of chemical industry, communication between design, manufacturing, marketing and management should be centered on modeling and simulation, which could integrate the whole product and process development chains, process units and subdivisions of the company. Solutions to this topic often set aside one or more components from product, process and control models, hence, as a novel know-how, an information system methodology was developed. Its structure integrates models of these components with a process data warehouse where integration includes information, location, application and time integrity. It supports complex engineering tasks related to analysis of system performance, process optimization, operator training systems (OTS), decision support systems (DSS), reverse engineering or software sensors (soft-sensors). The case study in this article presents the application of the proposed methodology for product quality soft-sensor application by on-line melt index prediction of an operating polymerization technology.

Frontiers in Engineering Optimization

The successful application of a mathematical programming algorithm to a complex engineering problem requires a careful interfacing of needs and requirements between the optimization operator and the engineering system. This paper outlines some areas where interface requirements have not been successfully resolved. In order to bridge the frontier between theory and practice, issues are identified which require resolution by both algorithm developers and system engineers.