Fuzzy similarity-based rough set method for case-based reasoning and its application in tool selection

Jiang, Yajun; Chen, Jun; Ruan, Xiaogang

doi:10.1016/j.ijmachtools.2005.05.003

Cited by 44 publications

(19 citation statements)

References 15 publications

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“…By reduct calculation and knowledge extraction, rough sets data analysis approaches can establish the mapping relationship between equivalent classes of input space and decision classes in information system, then based on it, the decision model of classification problem can be built from original data. Recently rough sets has been extensively applied in data mining [2,3], knowledge discovery [4,5], uncertain reasoning [6,7], granular computing [8,9], and so on.…”

Section: Introductionmentioning

confidence: 99%

Rough Neural Network Based on Bottom-Up Fuzzy Rough Data Analysis

Zhang

Wang

2009

Neural Process Lett

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Based on bottom-up fuzzy rough data analysis, a new rough neural network decision-making model is proposed. Through supervised Gaustafason-Kessel (G-K) clustering algorithm, proper fuzzy clusters are found to partition the input data space. At the same time cluster number is searched by monotone increasing process. If the cluster number matches with that exactly exist in data sets then excellent fuzzy rough data modeling (FRDM) model can be built. And by integrating it with neural network technique, corresponding rough neural network is constructed. Our method overcomes the defects of conventional top-down based rough logic neural network (RLNN) method, and it also achieves adaptive learning ability and comprehensive soft decision-making ability compared with FRDM model. The experiment results indicate that our method has stronger generalization ability and more compact network structure than conventional RLNN.

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Section: Introductionmentioning

confidence: 99%

Rough Neural Network Based on Bottom-Up Fuzzy Rough Data Analysis

Zhang

Wang

2009

Neural Process Lett

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“…Jiang et al used fuzzy similarity-based rough set to retrieval tool information for kinds of features, such as pocket, slot, hole, etc. [1]. You et al represented FFS as a flat-blend graph to retrieve process planning and die design for manufacturing automotive panels [4].…”

Section: Case-based Reasoningmentioning

confidence: 99%

“…Many case-based reasoning (CBR) systems were proposed to solve engineering problems in mould industry relying on experience [1,4,8,13], but case-based tool reuse for sculptured cavity machining has not been studied. This work tries to bridge the gap between new solution and reuse of previous successful cases.…”

mentioning

confidence: 99%

A geometry search approach in case-based tool reuse for mould manufacturing

Zhou

Liu

et al. 2015

Int J Adv Manuf Technol

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Similar freeform surfaces are widely adopted in product family or different generations. Manufacturing of these surfaces with efficiency is essential to competitiveness of the company. Conventionally, milling tools were chosen mainly by experience; therefore, reuse of existing experience is essential to advanced manufacturing. This paper proposed a novel geometry search approach to recommend tool selection for review and reuse based on previous cases. First, a hierarchical representation is extracted from freeform meshes. Then, qualitative and quantitative properties were defined to support matching and comparison in the level of detail. Geometry search algorithm is then adapted with boundary condition to find best sequence of tools, where existing cases were stored in layered slices along with their tool information, and new case of cavity is explored in a sequence to progressively find the best match of each layer. Finally, retrieved tools were adapted to review and assist for process planners. A prototype system and a case study are provided to demonstrate the proposed method.

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“…Li et al (2006) presented a novel rough set-based case-based reasoner for application of text categorization. Jiang et al (2006) presented a novel methodology for utilizing a fuzzy similarity-based Rough Set algorithm in feature weighting and reduction for CBR systems in tool selection for die and mold NC machining. Liu and Yu (2009) applied rough set to remove out the non-correlated parameters for simplifying case library of CBR and searching the most similar cases implemented by the rough set rules.…”

Section: Introductionmentioning

confidence: 99%

A combined data mining approach using rough set theory and case-based reasoning in medical datasets

Rezvan¹,

Hamadani²,

Saffari³

et al. 2014

10.5267/j.dsl

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Case-based reasoning (CBR) is the process of solving new cases by retrieving the most relevant ones from an existing knowledge-base. Since, irrelevant or redundant features not only remarkably increase memory requirements but also the time complexity of the case retrieval, reducing the number of dimensions is an issue worth considering. This paper uses rough set theory (RST) in order to reduce the number of dimensions in a CBR classifier with the aim of increasing accuracy and efficiency. CBR exploits a distance based co-occurrence of categorical data to measure similarity of cases. This distance is based on the proportional distribution of different categorical values of features. The weight used for a feature is the average of cooccurrence values of the features. The combination of RST and CBR has been applied to real categorical datasets of Wisconsin Breast Cancer, Lymphography, and Primary cancer. The 5-fold cross validation method is used to evaluate the performance of the proposed approach. The results show that this combined approach lowers computational costs and improves performance metrics including accuracy and interpretability compared to other approaches developed in the literature.

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Fuzzy similarity-based rough set method for case-based reasoning and its application in tool selection

Cited by 44 publications

References 15 publications

Rough Neural Network Based on Bottom-Up Fuzzy Rough Data Analysis

Rough Neural Network Based on Bottom-Up Fuzzy Rough Data Analysis

A geometry search approach in case-based tool reuse for mould manufacturing

A combined data mining approach using rough set theory and case-based reasoning in medical datasets

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