A Novel Association Rule Decision Algorithm Based on Ant Colony Optimization Algorithm for Ball Mill Pulverizing System

Zhu, Wenzhi; Wang, Jingcheng; Cao, Hui

doi:10.1109/csse.2008.1171

Cited by 4 publications

(6 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Various approaches for self optimizing control have been tried for the milling system [96][97][98][99][100][101][102][103]. The aim of the operators is to run the plant at the optimal operational point, but due to transients and other variations in the system, real optimum is often different from the assumed one.…”

Section: Comparison Of Various Control Approachesmentioning

confidence: 99%

“…The application of self optimizing control for the mill can be found in [96][97][98][99][100][101][102][103]. The techniques developed in [96][97][98][99][100] computed suitable set points for the coal level/load, pressure difference, and the outlet temperature loops, depending on the current operating condition, and employed fuzzy control for regulating the hot air damper, recycle air damper, and the coal feed to the mill system.…”

Section: Self Optimizing Control For Mills and Optimization Studiesmentioning

confidence: 99%

“…The techniques developed in [96][97][98][99][100] computed suitable set points for the coal level/load, pressure difference, and the outlet temperature loops, depending on the current operating condition, and employed fuzzy control for regulating the hot air damper, recycle air damper, and the coal feed to the mill system. The set points are determined by solving the optimization problem, which is either maximizing the quantity of the coal in the mill or maximizing the coal feed rate, while meeting the constraints.…”

Section: Self Optimizing Control For Mills and Optimization Studiesmentioning

confidence: 99%

See 2 more Smart Citations

Review of control and fault diagnosis methods applied to coal mills

Agrawal

Panigrahi

Subbarao

2015

Journal of Process Control

View full text Add to dashboard Cite

Section: Comparison Of Various Control Approachesmentioning

confidence: 99%

Section: Self Optimizing Control For Mills and Optimization Studiesmentioning

confidence: 99%

Section: Self Optimizing Control For Mills and Optimization Studiesmentioning

confidence: 99%

See 1 more Smart Citation

Review of control and fault diagnosis methods applied to coal mills

Agrawal

Panigrahi

Subbarao

2015

Journal of Process Control

View full text Add to dashboard Cite

“…There is another use of ACO by Zhu, Wang, Cao, and Zhang (). In this paper, they proposed a new AR decision algorithm based on ACO for a Ball Mill Pulverizing system.…”

Section: Arm Algorithmsmentioning

confidence: 99%

“…Zhu et al () applied ACO to propose a new AR decision algorithm for a Ball Mill Pulverizing system which determines a set of variables that control the system. The authors believe that the AR decision problem is a combinational problem that it is hard to be solved and ACO is a good approach to solve very hard combinatorial optimization (Zhu et al, ). Their simulation results illustrate that applying this heuristic approach can result in finding the best ARs.…”

Section: Applications Of Heuristic Algorithmsmentioning

confidence: 99%

A survey on association rules mining using heuristics

Ghafari

Tjortjis

2019

WIREs Data Min & Knowl

View full text Add to dashboard Cite

Association rule mining (ARM) is a commonly encountred data mining method. There are many approaches to mining frequent rules and patterns from a database and one among them is heuristics. Many heuristic approaches have been proposed but, to the best of our knowledge, there is no comprehensive literature review on such approaches, yet with only a limited attempt. This gap needs to be filled. This paper reviews heuristic approaches to ARM and points out their most significant strengths and weaknesses. We propose eight performance metrics, such as execution time, memory consumption, completeness, and interestingness, we compare approaches against these performance metrics and discuss our findings. For instance, comparison results indicate that SRmining, PMES, Ant‐ARM, and MDS‐H are the fastest heuristic ARM algorithms. HSBO‐TS is the most complete one, while SRmining and ACS require only one database scan. In addition, we propose a parameter, named GT‐Rank for ranking heuristic ARM approaches, and based on that, ARMGA, ASC, and Kua emerge as the best approaches. We also consider ARM algorithms and their characteristics as transactions and items in a transactional database, respectively, and generate association rules that indicate research trends in this area. This article is categorized under: Algorithmic Development > Association Rules Technologies > Association Rules Fundamental Concepts of Data and Knowledge > Motivation and Emergence of Data Mining

show abstract