ABSTRACT Multi-attribute decision-making is usually concerned with weighting alternatives, thereb... more ABSTRACT Multi-attribute decision-making is usually concerned with weighting alternatives, thereby requiring weight information for decision attributes from a decision maker. However, the assignment of an attribute’s weight is sometimes difficult, and may vary from one decision maker to another. Additionally, imprecision and vagueness may affect each judgment in the decision-making process. That is, in a real application, various statistical data may be imprecise or linguistically as well as numerically vague. Given this coexistence of random and fuzzy information, the data cannot be adequately treated by simply using the formalism of random variables. To address this problem, fuzzy random variables are introduced as an integral component of regression models. Thus, in this paper, we proposed a fuzzy random multi-attribute evaluation model with confidence intervals using expectations and variances of fuzzy random variables. The proposed model is applied to oil palm fruit grading, as the quality inspection process for fruits requires a method to ensure product quality. We include simulation results and highlight the advantage of the proposed method in handling the existence of fuzzy random information.
Flavor is an essential quality characteristics of soymilk, which contains volatile compounds deri... more Flavor is an essential quality characteristics of soymilk, which contains volatile compounds derived from fatty acids via enzymatic and thermal reactions. In this study, 67 kinds of soybean cultivars were selected, and correlation analysis was conducted between physicochemical indexes of these soybean cultivars and flavor characteristic indexes of soymilk. With clustering analysis, all the soybean cultivars could be classified into three classes, and according to the results of principal component analysis for each class of soymilk flavor characteristics, the soymilk of second class had relatively heavier beany and non-beany flavor, and the third class had weaker flavor. For soybean cultivars of which the soymilk characteristics were unknown, two discriminant functions could be used to predict flavor characteristics if the physicochemical indexes were known. Therefore, screening of soybean cultivars suitable for soymilk processing can be targeted for the flavor favored by consumers and an evaluation method established.
In real-world regression problems, various statistical data may be linguistically imprecise or va... more In real-world regression problems, various statistical data may be linguistically imprecise or vague. Because of such co-existence of random and fuzzy information, we can not characterize the data only by random variables. Therefore, one can consider the use of fuzzy random variables as an integral component of regression problems. The objective of this paper is to build a regression model
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
Abstract The objective of this paper is to study facility location problems under a hybrid uncert... more Abstract The objective of this paper is to study facility location problems under a hybrid uncertain environment involving randomness and fuzziness. A two-stage fuzzy random facility location model with recourse is developed in which the demands and the costs are assumed to be fuzzy random variables. As in general the fuzzy random parameters in the model can be regarded as continuous fuzzy random variables with infinite realizations, the computation of the recourse requires solving infinite second-stage programming problems ...
The concept of prosthesis-guided implantation has been widely accepted for intraoral implant plac... more The concept of prosthesis-guided implantation has been widely accepted for intraoral implant placement, although clinicians do not fully appreciate its use for facial defect restoration. In this clinical report, multiple digital technologies were used to restore a facial defect with prosthesis-guided implantation. A simulation surgery was performed to remove the residual auricular tissue and to ensure the correct position of the mirrored contralateral ear model. The combined application of computed tomography and 3-dimensional photography preserved the position of the mirrored model and facilitated the definitive implant-retained auricular prosthesis.
In the context of robust optimization with information granules for distributional parameters, th... more In the context of robust optimization with information granules for distributional parameters, this paper investigates a two-stage waste-to-energy feedstock flow planning problem with uncertain capacity expansion costs. The objective is to minimize the worst-case overall loss in a mean-risk criterion where the risk is measured by a conditional value-at-risk operator. As a salient feature, an integrated uncertainty is considered which consists of not only the uncertainty in distribution shapes of the uncertain variables, but also the manifold uncertainties of the mean parameters. To tackle the robust optimization under such integrated uncertainty, we first discuss a distributional robust two-stage feedstock flow planning model with precise mean parameters that handles the uncertainty in distribution shape, and the model can be equivalently transformed into a linear program (LP). Furthermore, the precise-mean-based robust model is extended into the case of multifaceted uncertainty for...
ABSTRACT In this paper, a Value-at-Risk (VaR) based fuzzy random facility location model (VaR-FRF... more ABSTRACT In this paper, a Value-at-Risk (VaR) based fuzzy random facility location model (VaR-FRFLM) is built in which both the costs and demands are assumed to be fuzzy random variables, and the capacity of each facility is unfixed but a decision variable. A hybrid approach based on modified particle swarm optimization (MPSO) is proposed to solve the VaR-FRFLM. In this hybrid mechanism, an approximation algorithm is utilized to compute the fuzzy random VaR, a continuous Nbest-Gbest-based PSO and a genotype-phenotype-based binary PSO vehicles are designed to deal with the continuous capacity decisions and the binary location decisions, respectively, and two mutation operators are incorporated into the PSO to further enlarge the search space. A numerical experiment illustrates the application of the proposed hybrid MPSO algorithm and lays out its robustness to the parameter settings when dealing with the VaR-FRFLM.
Yi chuan = Hereditas / Zhongguo yi chuan xue hui bian ji, 2014
The genes of sulfur-containing amino acid synthetases in soybean are essential for the synthesis ... more The genes of sulfur-containing amino acid synthetases in soybean are essential for the synthesis of sulfur-containing amino acids. Gene mining of these enzymes is the basis for the molecular assistant breeding of high sulfur-containing amino acids in soybean. In this study, using software BioMercator2.1, 113 genes of sulfur-containing amino acid enzymes and 33 QTLs controlling the sulfur-containing amino acids content were mapped onto Consensus Map 4.0, which was integrated by genetic and physical maps of soybean. Sixteen candidate genes associated to the synthesis of sulfur-containing amino acids were screened based on the synteny between gene loci and QTLs, and the effect values of QTLs. Through a bioinformatic analysis of the copy number, SNP information, and expression profile of candidate genes, 12 related enzyme genes were identified and mapped on 8 linkage groups, such as D1a, M, A2, K, and G. The genes corresponding to QTL regions can explain 6%?38.5% genetic variation of su...
The expectation function of fuzzy variable is an important and widely used criterion in fuzzy opt... more The expectation function of fuzzy variable is an important and widely used criterion in fuzzy optimization, and sound properties on the expectation function may help in model analysis and solution algorithm design for the fuzzy optimization problems. The present paper deals with some analytical properties of credibilistic expectation functions of fuzzy variables that lie in three aspects. First, some continuity theorems on the continuity and semicontinuity conditions are proved for the expectation functions. Second, a differentiation formula of the expectation function is derived which tells that, under certain conditions, the derivative of the fuzzy expectation function with respect to the parameter equals the expectation of the derivative of the fuzzy function with respect to the parameter. Finally, a law of large numbers for fuzzy variable sequences is obtained leveraging on the Chebyshev Inequality of fuzzy variables. Some examples are provided to verify the results obtained.
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
Abstract In this paper, using value-at-risk, a new fuzzy portfolio selection model named VaR-FPSM... more Abstract In this paper, using value-at-risk, a new fuzzy portfolio selection model named VaR-FPSM is proposed. The value-at-risk is the measure of risk, which describes the greatest loss of an investment with some confidence level. When security returns are same kind of ...
Due to subjective judgement, imprecise human knowledge and perception in capturing statistical da... more Due to subjective judgement, imprecise human knowledge and perception in capturing statistical data, the real data of lifetimes in many systems are both random and fuzzy in nature. Based on the fuzzy random variables that are used to characterize the lifetimes, this paper studies the redundancy allocation problems to a fuzzy random parallel-series system. Two fuzzy random redundancy allocation models
ABSTRACT In this chapter, we revisit the facility location problem. Applying the two-stage fuzzy ... more ABSTRACT In this chapter, we revisit the facility location problem. Applying the two-stage fuzzy stochastic programming with VaR (FSP-VaR) discussed in Chap. 6 to the context of facility location selection with variable capacity, we present another two-stage facility location model in the fuzzy random environment which owns a quite different structure from the location model of Chap. 5.
ABSTRACT Multi-attribute decision-making is usually concerned with weighting alternatives, thereb... more ABSTRACT Multi-attribute decision-making is usually concerned with weighting alternatives, thereby requiring weight information for decision attributes from a decision maker. However, the assignment of an attribute’s weight is sometimes difficult, and may vary from one decision maker to another. Additionally, imprecision and vagueness may affect each judgment in the decision-making process. That is, in a real application, various statistical data may be imprecise or linguistically as well as numerically vague. Given this coexistence of random and fuzzy information, the data cannot be adequately treated by simply using the formalism of random variables. To address this problem, fuzzy random variables are introduced as an integral component of regression models. Thus, in this paper, we proposed a fuzzy random multi-attribute evaluation model with confidence intervals using expectations and variances of fuzzy random variables. The proposed model is applied to oil palm fruit grading, as the quality inspection process for fruits requires a method to ensure product quality. We include simulation results and highlight the advantage of the proposed method in handling the existence of fuzzy random information.
Flavor is an essential quality characteristics of soymilk, which contains volatile compounds deri... more Flavor is an essential quality characteristics of soymilk, which contains volatile compounds derived from fatty acids via enzymatic and thermal reactions. In this study, 67 kinds of soybean cultivars were selected, and correlation analysis was conducted between physicochemical indexes of these soybean cultivars and flavor characteristic indexes of soymilk. With clustering analysis, all the soybean cultivars could be classified into three classes, and according to the results of principal component analysis for each class of soymilk flavor characteristics, the soymilk of second class had relatively heavier beany and non-beany flavor, and the third class had weaker flavor. For soybean cultivars of which the soymilk characteristics were unknown, two discriminant functions could be used to predict flavor characteristics if the physicochemical indexes were known. Therefore, screening of soybean cultivars suitable for soymilk processing can be targeted for the flavor favored by consumers and an evaluation method established.
In real-world regression problems, various statistical data may be linguistically imprecise or va... more In real-world regression problems, various statistical data may be linguistically imprecise or vague. Because of such co-existence of random and fuzzy information, we can not characterize the data only by random variables. Therefore, one can consider the use of fuzzy random variables as an integral component of regression problems. The objective of this paper is to build a regression model
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
Abstract The objective of this paper is to study facility location problems under a hybrid uncert... more Abstract The objective of this paper is to study facility location problems under a hybrid uncertain environment involving randomness and fuzziness. A two-stage fuzzy random facility location model with recourse is developed in which the demands and the costs are assumed to be fuzzy random variables. As in general the fuzzy random parameters in the model can be regarded as continuous fuzzy random variables with infinite realizations, the computation of the recourse requires solving infinite second-stage programming problems ...
The concept of prosthesis-guided implantation has been widely accepted for intraoral implant plac... more The concept of prosthesis-guided implantation has been widely accepted for intraoral implant placement, although clinicians do not fully appreciate its use for facial defect restoration. In this clinical report, multiple digital technologies were used to restore a facial defect with prosthesis-guided implantation. A simulation surgery was performed to remove the residual auricular tissue and to ensure the correct position of the mirrored contralateral ear model. The combined application of computed tomography and 3-dimensional photography preserved the position of the mirrored model and facilitated the definitive implant-retained auricular prosthesis.
In the context of robust optimization with information granules for distributional parameters, th... more In the context of robust optimization with information granules for distributional parameters, this paper investigates a two-stage waste-to-energy feedstock flow planning problem with uncertain capacity expansion costs. The objective is to minimize the worst-case overall loss in a mean-risk criterion where the risk is measured by a conditional value-at-risk operator. As a salient feature, an integrated uncertainty is considered which consists of not only the uncertainty in distribution shapes of the uncertain variables, but also the manifold uncertainties of the mean parameters. To tackle the robust optimization under such integrated uncertainty, we first discuss a distributional robust two-stage feedstock flow planning model with precise mean parameters that handles the uncertainty in distribution shape, and the model can be equivalently transformed into a linear program (LP). Furthermore, the precise-mean-based robust model is extended into the case of multifaceted uncertainty for...
ABSTRACT In this paper, a Value-at-Risk (VaR) based fuzzy random facility location model (VaR-FRF... more ABSTRACT In this paper, a Value-at-Risk (VaR) based fuzzy random facility location model (VaR-FRFLM) is built in which both the costs and demands are assumed to be fuzzy random variables, and the capacity of each facility is unfixed but a decision variable. A hybrid approach based on modified particle swarm optimization (MPSO) is proposed to solve the VaR-FRFLM. In this hybrid mechanism, an approximation algorithm is utilized to compute the fuzzy random VaR, a continuous Nbest-Gbest-based PSO and a genotype-phenotype-based binary PSO vehicles are designed to deal with the continuous capacity decisions and the binary location decisions, respectively, and two mutation operators are incorporated into the PSO to further enlarge the search space. A numerical experiment illustrates the application of the proposed hybrid MPSO algorithm and lays out its robustness to the parameter settings when dealing with the VaR-FRFLM.
Yi chuan = Hereditas / Zhongguo yi chuan xue hui bian ji, 2014
The genes of sulfur-containing amino acid synthetases in soybean are essential for the synthesis ... more The genes of sulfur-containing amino acid synthetases in soybean are essential for the synthesis of sulfur-containing amino acids. Gene mining of these enzymes is the basis for the molecular assistant breeding of high sulfur-containing amino acids in soybean. In this study, using software BioMercator2.1, 113 genes of sulfur-containing amino acid enzymes and 33 QTLs controlling the sulfur-containing amino acids content were mapped onto Consensus Map 4.0, which was integrated by genetic and physical maps of soybean. Sixteen candidate genes associated to the synthesis of sulfur-containing amino acids were screened based on the synteny between gene loci and QTLs, and the effect values of QTLs. Through a bioinformatic analysis of the copy number, SNP information, and expression profile of candidate genes, 12 related enzyme genes were identified and mapped on 8 linkage groups, such as D1a, M, A2, K, and G. The genes corresponding to QTL regions can explain 6%?38.5% genetic variation of su...
The expectation function of fuzzy variable is an important and widely used criterion in fuzzy opt... more The expectation function of fuzzy variable is an important and widely used criterion in fuzzy optimization, and sound properties on the expectation function may help in model analysis and solution algorithm design for the fuzzy optimization problems. The present paper deals with some analytical properties of credibilistic expectation functions of fuzzy variables that lie in three aspects. First, some continuity theorems on the continuity and semicontinuity conditions are proved for the expectation functions. Second, a differentiation formula of the expectation function is derived which tells that, under certain conditions, the derivative of the fuzzy expectation function with respect to the parameter equals the expectation of the derivative of the fuzzy function with respect to the parameter. Finally, a law of large numbers for fuzzy variable sequences is obtained leveraging on the Chebyshev Inequality of fuzzy variables. Some examples are provided to verify the results obtained.
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
Abstract In this paper, using value-at-risk, a new fuzzy portfolio selection model named VaR-FPSM... more Abstract In this paper, using value-at-risk, a new fuzzy portfolio selection model named VaR-FPSM is proposed. The value-at-risk is the measure of risk, which describes the greatest loss of an investment with some confidence level. When security returns are same kind of ...
Due to subjective judgement, imprecise human knowledge and perception in capturing statistical da... more Due to subjective judgement, imprecise human knowledge and perception in capturing statistical data, the real data of lifetimes in many systems are both random and fuzzy in nature. Based on the fuzzy random variables that are used to characterize the lifetimes, this paper studies the redundancy allocation problems to a fuzzy random parallel-series system. Two fuzzy random redundancy allocation models
ABSTRACT In this chapter, we revisit the facility location problem. Applying the two-stage fuzzy ... more ABSTRACT In this chapter, we revisit the facility location problem. Applying the two-stage fuzzy stochastic programming with VaR (FSP-VaR) discussed in Chap. 6 to the context of facility location selection with variable capacity, we present another two-stage facility location model in the fuzzy random environment which owns a quite different structure from the location model of Chap. 5.
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Papers by Shuming Wang