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Author (up) Allende, H.; Bravo, D.; Canessa, E.
Title Robust design in multivariate systems using genetic algorithms Type
Year 2010 Publication Quality & Quantity Abbreviated Journal Qual. Quant.
Volume 44 Issue 2 Pages 315-332
Keywords Robust design; Taguchi methods; Genetic algorithms; Desirability functions
Abstract This paper presents a methodology based oil genetic algorithms, which finds feasible and reasonably adequate Solutions to problems of robust design in multivariate systems. We use a genetic algorithm to determine the appropriate control factor levels for simultaneously optimizing all of the responses of the system, considering the noise factors which affect it. The algorithm is guided by a desirability function which works with only one fitness function although the system May have many responses. We validated the methodology using data obtained from a real system and also from a process simulator, considering univariate and multivariate systems. In all cases, the methodology delivered feasible solutions, which accomplished the goals of robust design: obtain responses very close to the target values of each of them, and with minimum variability. Regarding the adjustment of the mean of each response to the target value, the algorithm performed very well. However, only in some of the multivariate cases, the algorithm was able to significantly reduce the variability of the responses.
Address [Allende, Hector; Bravo, Daniela; Canessa, Enrique] Univ Adolfo Ibanez, Fac Ciencia & Tecnol, Balmaceda 1620, Vina Del Mar, Chile, Email: hallende@uai.cl
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0033-5177 ISBN Medium
Area Expedition Conference
Notes WOS:000275327300008 Approved
Call Number UAI @ eduardo.moreno @ Serial 82
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Author (up) Canessa, E.; Chaigneau, S.
Title The dynamics of social agreement according to Conceptual Agreement Theory Type
Year 2014 Publication Quality & Quantity Abbreviated Journal Qual. Quant.
Volume 48 Issue 6 Pages 3289-3309
Keywords Conceptual Agreement Theory; Agent-based modeling; Conceptual diversity; Dynamics of conceptual development
Abstract Many social phenomena can be viewed as processes in which individuals in social groups develop agreement (e.g., public opinion, the spreading of rumor, the formation of social and linguistic conventions). Conceptual Agreement Theory (CAT) models social agreement as a simplified communicational event in which an Observer and Actor exchange ideas about a concept , and where uses that information to infer whether 's conceptual state is the same as its own (i.e., to infer agreement). Agreement may be true (when infers that is thinking and this is in fact the case, event ) or illusory (when infers that is thinking and this is not the case, event ). In CAT, concepts that afford or become more salient in the minds of members of social groups. Results from an agent-based model (ABM) and probabilistic model that implement CAT show that, as our conceptual analyses suggested would be the case, the simulated social system selects concepts according to their usefulness to agents in promoting agreement among them (Experiment 1). Furthermore, the ABM exhibits more complex dynamics where similar minded agents cluster and are able to retain useful concepts even when a different group of agents discards them (Experiment 2). We discuss the relevance of CAT and the current findings for analyzing different social communication events, and suggest ways in which CAT could be put to empirical test.
Address [Canessa, Enrique] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Vina Del Mar, Chile, Email: ecanessa@uai.cl;
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0033-5177 ISBN Medium
Area Expedition Conference
Notes WOS:000343294900024 Approved
Call Number UAI @ eduardo.moreno @ Serial 418
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Author (up) Canessa, E.; Droop, C.; Allende, H.
Title An improved genetic algorithm for robust design in multivariate systems Type
Year 2012 Publication Quality & Quantity Abbreviated Journal Qual. Quant.
Volume 46 Issue 2 Pages 665-678
Keywords Robust design; Taguchi methods; Genetic algorithms; Desirability functions; Research article
Abstract In a previous article, we presented a genetic algorithm (GA), which finds solutions to problems of robust design in multivariate systems. Based on that GA, we developed a new GA that uses a new desirability function, based on the aggregation of the observed variance of the responses and the squared deviation between the mean of each response and its corresponding target value. Additionally, we also changed the crossover operator from a one-point to a uniform one. We used three different case studies to evaluate the performance of the new GA and also to compare it with the original one. The first case study involved using data from a univariate real system, and the other two employed data obtained from multivariate process simulators. In each of the case studies, the new GA delivered good solutions, which simultaneously adjusted the mean of each response to its corresponding target value. This performance was similar to the one of the original GA. Regarding variability reduction, the new GA worked much better than the original one. In all the case studies, the new GA delivered solutions that simultaneously decreased the standard deviation of each response to almost the minimum possible value. Thus, we conclude that the new GA performs better than the original one, especially regarding variance reduction, which was the main problem exhibited by the original GA.
Address [Canessa, Enrique; Droop, Christian; Allende, Hector] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Balmaceda 1620, Vina Del Mar, Chile, Email: ecanessa@uai.cl
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0033-5177 ISBN Medium
Area Expedition Conference
Notes WOS:000299134200017 Approved
Call Number UAI @ eduardo.moreno @ Serial 191
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Author (up) Canessa, E.C.; Chaigneau, S.E.
Title When are concepts comparable across minds? Type
Year 2016 Publication Quality & Quantity Abbreviated Journal Qual. Quant.
Volume 50 Issue 3 Pages 1367-1384
Keywords Conceptual Agreement Theory; Conceptual variability; Shared meaning; Agreement
Abstract In communication, people cannot resort to direct reference (e.g., pointing) when using diffuse concepts like democracy. Given that concepts reside in individuals' minds, how can people share those concepts? We argue that concepts are comparable across a social group if they afford agreement for those who use it; and that agreement occurs whenever individuals receive evidence that others conceptualize a given situation similarly to them. Based on Conceptual Agreement Theory, we show how to compute an agreement probability based on the sets of properties belonging to concepts. If that probability is sufficiently high, this shows that concepts afford an adequate level of agreement, and one may say that concepts are comparable across individuals' minds. In contrast to other approaches, our method considers that inter-individual variability in naturally occurring conceptual content exists and is a fact that must be taken into account, whereas other theories treat variability as error that should be cancelled out. Given that conceptual variability will exist, our approach may establish whether concepts are comparable across individuals' minds more soundly than previous methods.
Address [Canessa, Enrique Carlos] Univ Adolfo Ibanez, Fac Ingn & Ciencias, Av P Hurtado 750, Vina Del Mar, Chile, Email: ecanessa@uai.cl;
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0033-5177 ISBN Medium
Area Expedition Conference
Notes WOS:000374458900025 Approved
Call Number UAI @ eduardo.moreno @ Serial 614
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