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Articles 1 - 7 of 7
Full-Text Articles in Engineering
Data‐Enabled Cognitive Modeling: Validating Student Engineers’ Fuzzy Design‐Based Decision‐Making In A Virtual Design Problem, Golnaz Arastoopour Irgens, Naomi C. Chesler, Jeffrey Linderoth, David Williamson Shaffer
Data‐Enabled Cognitive Modeling: Validating Student Engineers’ Fuzzy Design‐Based Decision‐Making In A Virtual Design Problem, Golnaz Arastoopour Irgens, Naomi C. Chesler, Jeffrey Linderoth, David Williamson Shaffer
Golnaz Arastoopour Irgens
The ability of future engineering professionals to solve complex real‐world problems depends on their design education and training. Because engineers engage with open‐ended problems in which there are unknown parameters and multiple competing objectives, they engage in fuzzy decision‐making, a method of making decisions that takes into account inherent imprecisions and uncertainties in the real world. In the design‐based decision‐making field, few studies have applied fuzzy decision‐making models to actual decision‐making process data. Thus, in this study, we use datasets on student decision‐making processes to validate approximate fuzzy models of student decision‐making, which we call data‐enabled cognitive modeling. The results …
Data‐Enabled Cognitive Modeling: Validating Student Engineers’ Fuzzy Design‐Based Decision‐Making In A Virtual Design Problem, Golnaz Arastoopour Irgens, Naomi C. Chesler, Jeffrey Linderoth, David Williamson Shaffer
Data‐Enabled Cognitive Modeling: Validating Student Engineers’ Fuzzy Design‐Based Decision‐Making In A Virtual Design Problem, Golnaz Arastoopour Irgens, Naomi C. Chesler, Jeffrey Linderoth, David Williamson Shaffer
Publications
The ability of future engineering professionals to solve complex real‐world problems depends on their design education and training. Because engineers engage with open‐ended problems in which there are unknown parameters and multiple competing objectives, they engage in fuzzy decision‐making, a method of making decisions that takes into account inherent imprecisions and uncertainties in the real world. In the design‐based decision‐making field, few studies have applied fuzzy decision‐making models to actual decision‐making process data. Thus, in this study, we use datasets on student decision‐making processes to validate approximate fuzzy models of student decision‐making, which we call data‐enabled cognitive modeling. The results …
Fuzzy Differential Evolution Algorithm, Dejan Vucetic
Fuzzy Differential Evolution Algorithm, Dejan Vucetic
Electronic Thesis and Dissertation Repository
The Differential Evolution (DE) algorithm is a powerful search technique for solving global optimization problems over continuous space. The search initialization for this algorithm does not adequately capture vague preliminary knowledge from the problem domain. This thesis proposes a novel Fuzzy Differential Evolution (FDE) algorithm, as an alternative approach, where the vague information of the search space can be represented and used to deliver a more efficient search. The proposed FDE algorithm utilizes fuzzy set theory concepts to modify the traditional DE algorithm search initialization and mutation components. FDE, alongside other key DE features, is implemented in a convenient decision …
Multi-Criteria Analysis Of Potential Recovery Facilities In A Reverse Supply Chain, Surendra M. Gupta, Satish Nukala
Multi-Criteria Analysis Of Potential Recovery Facilities In A Reverse Supply Chain, Surendra M. Gupta, Satish Nukala
Surendra M. Gupta
Analytic Hierarchy Process (AHP) has been employed by researchers for solving multi-criteria analysis problems. However, AHP is often criticized for its unbalanced scale of judgments and failure to precisely handle the inherent uncertainty and vagueness in carrying out the pair-wise comparisons. With an objective to address these drawbacks, in this paper, we employ a fuzzy approach in selecting potential recovery facilities in the strategic planning of a reverse supply chain network that addresses the decision maker's level of confidence in the fuzzy assessments and his/her attitude towards risk. A numerical example is considered to illustrate the methodology.
Towards A More Adequate Defuzzification Of Interval-Valued Fuzzy Sets, Vladik Kreinovich, Van Nam Huynh, Yoshiteru Nakamori
Towards A More Adequate Defuzzification Of Interval-Valued Fuzzy Sets, Vladik Kreinovich, Van Nam Huynh, Yoshiteru Nakamori
Departmental Technical Reports (CS)
It is known that interval-valued fuzzy sets [m(x)] provide a more adequate description of expert uncertainty than the more traditional "type-1" (number-valued) fuzzy techniques. Specifically, an interval-valued fuzzy set can be viewed as a class of possible fuzzy sets m(x) from [m(x)]. In this case, as a result of defuzzification, it is natural to return the range [u] of all possible values u(m) that can be obtained by defuzzifying membership functions m(x) from this class. In practice, it is reasonable to restrict ourselves only to fuzzy numbers m(x), i.e., to "unimodal" fuzzy sets. Under this restriction, in general, we get …
Towards A More Adequate Use Of Interval-Valued Fuzzy Techniques In Intelligent Control: A Fuzzy Analogue Of Unimodality, Van Nam Huynh, Vladik Kreinovich
Towards A More Adequate Use Of Interval-Valued Fuzzy Techniques In Intelligent Control: A Fuzzy Analogue Of Unimodality, Van Nam Huynh, Vladik Kreinovich
Departmental Technical Reports (CS)
It is known that interval-valued fuzzy sets provide a more adequate description of expert uncertainty than the more traditional "type-1" (number-valued) fuzzy techniques. In the current approaches for using interval-valued fuzzy techniques, it is usually assumed that all fuzzy sets m(x) from the interval [l(x),u(x)] are possible. In this paper, we show that it is reasonable to restrict ourselves only to fuzzy numbers m(x), i.e., "unimodal" fuzzy sets. We also describe feasible algorithms for implementing thus modified intelligent control.
Why Intervals? Why Fuzzy Numbers? Towards A New Justification, Vladik Kreinovich
Why Intervals? Why Fuzzy Numbers? Towards A New Justification, Vladik Kreinovich
Departmental Technical Reports (CS)
The purpose of this paper is to present a new characterization of the set of all intervals (and of the corresponding set of fuzzy numbers). This characterization is based on several natural properties useful in mathematical modeling; the main of these properties is the necessity to be able to combine (fuse) several pieces of knowledge.