A Processing Route Decision Method for Ring-Frame Parts Based on Improved Bayesian Rough Set

An information system as a database that represents relationships between objects and attributes is an important mathematical model in the field of artificial intelligence. Hybrid data means boolean, categorical, real-valued, set-valued data and missing data in this paper. A hybrid information system is an information system where its attribute is hybrid data. This paper proposes a three-way decision method based on hybrid data. First, the distance between two objects based on the conditional attribute set in a given hybrid information system is developed and Gaussian kernel based on this distance is acquired. Then, the fuzzy Tcos-equivalence relation, induced by this information system, is obtained by using Gaussian kernel. Next, the decision-theoretic rough set model in this hybrid information system is presented. Moreover, a three-way decision method is given by means of this decision-theoretic rough set model and inclusion degree between two fuzzy sets. Finally, an example is employed to illustrate the feasibility of the proposed method, which may provide an effective method for hybrid data analysis in real applications.

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Three-way decisions with decision-theoretic rough sets based on covering-based q-rung orthopair fuzzy rough set model

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-202291 ◽

2021 ◽

pp. 1-21

Author(s):

Fang Liu ◽

Yi Liu ◽

Saleem Abdullah

Keyword(s):

Rough Set ◽

Loss Function ◽

Rough Sets ◽

Fuzzy Numbers ◽

Fuzzy Rough Set ◽

Decision Method ◽

Fuzzy Environment ◽

Multi Attribute Decision Making ◽

The Stability ◽

Function Matrix

Based on decision theory rough sets (DTRSs), three-way decisions (TWDs) provide a risk decision method for solving multi-attribute decision making (MADM) problems. The loss function matrix of DTRS is the basis of this method. In order to better solve the uncertainty and ambiguity of the decision problem, we introduce the q-rung orthopair fuzzy numbers (q-ROFNs) into the loss function. Firstly, we introduce concepts of q-rung orthopair fuzzy β-covering (q-ROF β-covering) and q-rung orthopair fuzzy β-neighborhood (q-ROF β-neighborhood). We combine covering-based q-rung orthopair fuzzy rough set (Cq-ROFRS) with the loss function matrix of DTRS in the q-rung orthopair fuzzy environment. Secondly, we propose a new model of q-ROF β-covering DTRSs (q-ROFCDTRSs) and elaborate its relevant properties. Then, by using membership and non-membership degrees of q-ROFNs, five methods for solving expected losses based on q-ROFNs are given and corresponding TWDs are also derived. On this basis, we present an algorithm based on q-ROFCDTRSs for MADM. Then, the feasibility of these five methods in solving the MADM problems is verified by an example. Finally, the sensitivity of each parameter and the stability and effectiveness of these five methods are compared and analyzed.

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Dynamic Online learning Algorithm For Three-way decision

MATEC Web of Conferences ◽

10.1051/matecconf/201823203024 ◽

2018 ◽

Vol 232 ◽

pp. 03024

Author(s):

Gaojie Cheng ◽

Jianmo Liu ◽

Jianfeng Xu ◽

Xiqiu Wang

Keyword(s):

Online Learning ◽

Rough Set ◽

Learning Algorithm ◽

Learning Models ◽

Stream Computing ◽

Data Set ◽

Time Efficiency ◽

Decision Method ◽

Computing Process ◽

Online Learning Algorithm

Three-way decision is an important theory for solving uncertain problems. Online computing is a new dynamic Stream computing form. How to execute three-way decision quickly in online computing is a challenging topic. In this paper, Online computing process is divided into incremental computing portion and decreasing computing portion. And a three-way decision dynamic incremental and decreasing learning algorithm for online computing is proposed. Firstly, the dynamic incremental and decreasing learning models is studied for stream computing based on probabilistic rough set . Then, the logical reasoning for three-way decision regions changing are discussed based on the dynamic incremental and decreasing learning models. And a novel dynamic online learning algorithm for three-way decision online computing is proposed based on the above theory. Finally, the experiment by UCI data set show that the proposed algorithms are superior than classical static three-way decision method in time efficiency.

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Three-Way Decisions Making Using Covering Based Fractional Orthotriple Fuzzy Rough Set Model

Mathematics ◽

10.3390/math8071121 ◽

2020 ◽

Vol 8 (7) ◽

pp. 1121 ◽

Cited By ~ 3

Author(s):

Shougi S. Abosuliman ◽

Saleem Abdullah ◽

Muhammad Qiyas

Keyword(s):

Decision Making ◽

Rough Set ◽

Rough Sets ◽

Fuzzy Numbers ◽

Loss Functions ◽

Multi Criteria Decision Making ◽

Expected Loss ◽

Fuzzy Rough Set ◽

Decision Method ◽

Proposed Model

On the basis of decision-theoretical rough sets (DTRSs), the three-way decisions give new model of decision approach for deal with the problem of decision. This proposed model of decision method is based on the loss function of DTRSs. First, the concept of fractional orthotriple fuzzy β -covering (FOF β -covering) and fractional orthotriple fuzzy β -neighborhood (FOF β -neighborhood) was introduced. We combined loss feature of DTRSs with covering-based fractional orthotriple fuzzy rough sets (CFOFSs) under the fractional orthotriple fuzzy condition. Secondly, we proposed a new FOF-covering decision-theoretical rough sets model (FOFCDTRSs) and developed related properties. Then, based on the grade of positive, neutral and negative membership of fractional orthotriple fuzzy numbers (FOFNs), five methods are established for addressing the expected loss expressed in the form of FOFNs and the corresponding three-way decisions are also derived. Based on this, we presented a FOFCDTRS-based algorithm for multi-criteria decision making (MCDM). Then, an example verifies the feasibility of the five methods for solving the MCDM problem. Finally, by comparing the results of the decisions of five methods with different loss functions.

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The crystallization of thin-film ceramics

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100122095 ◽

1992 ◽

Vol 50 (1) ◽

pp. 338-339

Author(s):

J.M. Schwartz ◽

L.F. Francis ◽

L.D. Schmidt ◽

P.S. Schabes-Retchkiman

Keyword(s):

Thin Films ◽

Grain Size ◽

Sol Gel ◽

Processing Route ◽

Small Areas ◽

Ceramic Thin Films ◽

Complex Shapes ◽

Sol Gel Process ◽

Ceramic Precursors ◽

Crystalline Ceramic

Ceramic thin films and coatings are of interest for electrical, optical, magnetic and thermal barrier applications. Critical for improved properties in thin films is the development of specific microstructures during processing. To this end, the sol-gel method is advantageous as a versatile processing route. The sol-gel process involves depositing a solution containing metalorganic or colloidal ceramic precursors onto a substrate and heating the deposited layer to form a crystalline or non-crystalline ceramic coating. This route has several advantages, including the ability to create tailored microstructures and properties, to coat large or small areas, simple or complex shapes, and to more easily prepare multicomponent ceramics. Sol-gel derived coatings are amorphous in the as-deposited state and develop their crystalline structure and microstructure during heat-treatment. We are particularly interested in studying the amorphous to crystalline transformation, because many key features of the microstructure such as grain size and grain size distribution may be linked to this transformation.

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Comparing fast inductive tempering and conventional tempering: Effects on microstructure and mechanical properties

Metallurgical Research & Technology ◽

10.1051/metal/2018015 ◽

2018 ◽

Vol 115 (4) ◽

pp. 407 ◽

Cited By ~ 4

Author(s):

Annika Eggbauer Vieweg ◽

Gerald Ressel ◽

Peter Raninger ◽

Petri Prevedel ◽

Stefan Marsoner ◽

...

Keyword(s):

Mechanical Properties ◽

Impact Energy ◽

Charpy Impact ◽

Heat Treating ◽

Processing Route ◽

High Heating Rate ◽

Heating Rates ◽

High Heating ◽

Tempering Treatment ◽

Carbide Distribution

Induction heating processes are of rising interest within the heat treating industry. Using inductive tempering, a lot of production time can be saved compared to a conventional tempering treatment. However, it is not completely understood how fast inductive processes influence the quenched and tempered microstructure and the corresponding mechanical properties. The aim of this work is to highlight differences between inductive and conventional tempering processes and to suggest a possible processing route which results in optimized microstructures, as well as desirable mechanical properties. Therefore, the present work evaluates the influencing factors of high heating rates to tempering temperatures on the microstructure as well as hardness and Charpy impact energy. To this end, after quenching a 50CrMo4 steel three different induction tempering processes are carried out and the resulting properties are subsequently compared to a conventional tempering process. The results indicate that notch impact energy raises with increasing heating rates to tempering when realizing the same hardness of the samples. The positive effect of high heating rate on toughness is traced back to smaller carbide sizes, as well as smaller carbide spacing and more uniform carbide distribution over the sample.

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