Uncertainty Modeling and Analysis in Engineering and the Sciences

Ayyub, Bilal M.; Klir, George J.

doi:10.1201/9781420011456

Cited by 277 publications

(214 citation statements)

References 193 publications

Supporting

Mentioning

209

Contrasting

Unclassified

Order By: Relevance

“…Dois especialistas possuem experiência animal e dois em produção de frangos de corte, sendo que todos possuem mais de 10 anos de atuação nas respectivas áreas, caracterizando domínio sobre o tema. Tal experiência é desejada por um especialista (Ayyub & Klir, 2006), tendo em vista sua influência direta na confiabilidade e na qualidade dos resultados.…”

Section: Figura 2 -Curvas De Pertinência Para As Variáveis De Saídaunclassified

Índice Fuzzy Para O Conforto Térmico De Suínos Na Fase De Crescimento E Terminação Com Base Na Temperatura Superficial E Frequencia Respiratória

et al. 2016

View full text Add to dashboard Cite

RESUMO:O objetivo do trabalho foi desenvolver e testar um modelo matemático computacional, com base na teoria dos conjuntos fuzzy, para predizer a temperatura superficial e frequência respiratória de suínos em função da idade dos animais e o índice de temperatura e umidade (ITU). Foram observados suínos na fase de crescimento e terminação. Os dados do ambiente térmico (ITU) e respostas fisiológicas (Temperatura Superficial (TS) e Frequência Respiratória (FR)) foram usados no desenvolvimento de um modelo fuzzy, sendo definidas, como variáveis de entrada a idade dos animais (dias) e o índice de temperatura e umidade (ITU), por se tratarem de variáveis que influenciam diretamente nas respostas fisiológicas dos animais. O desvio padrão médio do modelo fuzzy em relação aos valores observados experimentalmente foi de 0,61% e 1,38%, para TS e FR, respectivamente, sendo o desvio padrão maior encontrado de 1,30% e 4,16% (para TS e FR, respectivamente) e o desvio padrão menor de 0,01% e 0,14% (para TS e FR respectivamente). Os coeficientes de determinação (R 2 , %) obtidos mostraram que 58,72% e 83,55% (para TS e FR respectivamente) da variação podem ser explicadas pelo modelo. Portanto, o modelo fuzzy desenvolvido em função da idade dos suínos e do ITU mostrou-se mais adequado para a predição da resposta frequência respiratória do que para a predição da temperatura superficial de suínos na fase de crescimento. Apresenta baixo desvio padrão e correlação considerável para essa variável com os dados medidos durante a condução do experimento de campo, podendo ser utilizado como ferramenta de controle do ambiente térmico em instalações comerciais de produção. PALAVRA-CHAVE: ambiência térmica, instalações para suínos, modelagem fuzzy THERMAL COMFORT FUZZY INDEX OF PIGS IN GROWING AND FINISHING BASED ON SURFACE TEMPERATURE AND RESPIRATORY RATEABSTRACT: The objective of this study was to develop and test a computational mathematical model, based on the fuzzy theory to predict the surface temperature and respiratory rate of pigs in function of their age and the temperature and humidity index (THI). Pigs were observed in the growth-finishing phase. The data of the thermal environment (THI) and physiological responses (surface temperature (ST) and respiratory rate (RR)) were used in developing the fuzzy model. The age of the animals (days) and the temperature and humidity index (THI), were defined as input variables because they are variables that directly influence the physiological responses of the animals. The average standard deviation of the fuzzy model observed values was 0.61% and 1.38% for TS and FR, respectively. The highest standard deviation was 1.30% and 4.16% (for TS and RR, respectively), and the lowest standard deviation was of 0.01% and 0.14% (for TS and FR respectively). The coefficients of determination (R 2 %) showed that 58.72% and 83.55% (for TS and FR respectively) of the variation can be explained by the model. Therefore, the fuzzy model was more suitable for respiratory response prediction than for predictin...

show abstract

Section: Figura 2 -Curvas De Pertinência Para As Variáveis De Saídaunclassified

Índice Fuzzy Para O Conforto Térmico De Suínos Na Fase De Crescimento E Terminação Com Base Na Temperatura Superficial E Frequencia Respiratória

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Uncertainty is a common problem in the physical and chemical sciences and engineering [39]. Several methods and approaches exist within these fields that allow uncertainty modeling and quantification.…”

Section: Uncertainty In Biological Systemsmentioning

confidence: 99%

Production of biofuels and biochemicals: in need of an ORACLE

Mišković

Hatzimanikatis

2010

Trends in Biotechnology

103

110

View full text Add to dashboard Cite

The engineering of cells for the production of fuels and chemicals involves simultaneous optimization of multiple objectives, such as specific productivity, extended substrate range and improved tolerance -all under a great degree of uncertainty. The achievement of these objectives under physiological and process constraints will be impossible without the use of mathematical modeling. However, the limited information and the uncertainty in the available information require new methods for modeling and simulation that will characterize the uncertainty and will quantify, in a statistical sense, the expectations of success of alternative metabolic engineering strategies. We discuss these considerations toward developing a framework for the Optimization and Risk Analysis of Complex Living Entities (ORACLE) -a computational method that integrates available information into a mathematical structure to calculate control coefficients. Biofuels and biochemicals: a multi-objective optimization problem Nearly 20 years ago, Tong and Cameron classified the applications of metabolic engineering into five main areas: (i) improved production and utilization of chemicals already produced/used by the host; (ii) extended substrate range for growth and production; (iii) addition of new catabolic activities for the degradation of toxic chemicals; (iv) production of chemicals new to the host; and (v) modification of the cell [1]. In the development of microorganisms for fuels and chemicals, one must consider and optimize almost all of these objectives simultaneously. For example, the economics of the fuels and commodity chemicals will require a host that is able to overproduce a fuel or chemical (native or new to the organism) from a broad range of carbon substrates, some of them not used previously by this organism, with high specific rates and with near-theoretical yields [2]. All of these issues become more challenging when we consider the use of new hosts for engineering [3,4], where there is not enough genomic information, the genetic tools for metabolic engineering are limited, and extensive knowledge about their physiology is lacking.The development of microorganisms for fuels and chemicals will also require the fine-tuning of carbon flows and redox balance. All of the biofuels currently considered require delicate manipulation of the carbon flows in the central metabolism, and any intervention in these pathways can have significant implications for the cellular physiology. Redox balance, energy charge and cofactor levels are also important because they are involved in many of the pathways for the production of biofuels and acids. For example, these pathways involve reactions that produce and consume redox potential, and their directionality is determined by the NAD + /NADH ratio. Metabolic engineering of these pathways could alter the balance of redox and coenzyme cofactors, thereby reducing the productivity and the yield, leading to the production of byproducts that could increase the cost of downstream processing [2,[5][6][...

show abstract

“…Sii et al (2001), Koch et al (1999), Allen et al (2006), and uncertainty, e.g. Suh (1990), Du and Chen (2000), Ayyub and Klir (2006), are becoming the standard concepts in many recent design references, see e.g. ISSC (2012).…”

Section: Selection Space L/set L (See Regions a And D In The Top Row Ofmentioning

confidence: 99%

“…Among the latter, the techniques of scoring (max utility), compromising (closest to ideal) and concordance models (based on evaluation of preference rankings) are used. Finally, the techniques of uncertainty analysis can also be used in the subjective decision-making models, Ayyub and Klir (2006). Figure 2) Selection space is combining the start (design requirements/aspirations) and end (set of preferred designs of design space transformations): Composite value function…”

Section: Value Functions V(−) Seementioning

confidence: 99%

Methods and concepts for the multi-criteria synthesis of ship structures

Žanić

2013

Ships and Offshore Structures

View full text Add to dashboard Cite

EDITORIAL Methods and concepts for the multi-criteria synthesis of ship structuresThe basic concepts and methods for multi-criteria synthesis of complex thin-walled ship structures in concept and preliminary design are presented. The principal steps in the definition of the design model, the selected general requirements on the design procedure and balanced and applicable combinations of design models are elaborated. The paper also provides an introduction to the basic theory, mappings, non-dominance concepts (Pareto frontier), spaces and sets used for the mathematical definition of design problems (DPs) together with the unified taxonomy applicable in the handling of complex DPs. System identification from the multi-stakeholder perspectives of owner and society and the formulations and solutions of structural DP are discussed.Keywords: design support system (DeSS); Pareto-supported decision making (PSD); thin-walled ship structures; structural design procedure; structural optimisation; Pareto optimality; design synthesis This introductory paper is devoted to my colleague and friend Professor Owen F. Hughes with whom I have had the privilege of sharing the burden and enjoyment of generating methods for the design of efficient and safe ship structures. ForewordIt has been claimed that this century in engineering will be the century of synthesis, after the twentieth century generated fast and reliable analysis methods capable of dealing with complex structural problems. Synthesis introduces the additional level of complexity, encapsulating the analysis models (AMs). For the synthesis problems, there is no universal technique (like finite element method (FEM) in structural analysis) to solve the non-linear, fuzzy, multi-criteria DP of high dimensionality leading to the multiplicity of different solutions/methods.Most of the papers in this SAOS Special Issue come from the structural analysis area. It is an objective of this introductory paper to systematise some of the basic concepts and methods of synthesis, applicable to the realistic ship structural DPs.Available design methods and optimisation techniques also confirm that analysis methods, as presented in this issue, as well as many methods from other authors can be included into the modern design environments and prove that the 'added level of complexity' is within our reach. For these reasons, this editorial is also an attempt to introduce a novel design-oriented point of view to the interested reader, because we all have as an ultimate objective of our respective work a contribution to the design of efficient and safe structures. This special issue is concluded by the autobiographical essay written by Professor Owen Hughes showing the evolution of concepts and methods from his lifetime experience, supported and augmented by recollections from some of his colleagues and friends. In the field of Naval Architecture, it was Owen Hughes who recognised that the utmost simplicity of methods and clarity of ideas are needed in order to apply the 'first principles anal...

show abstract

Uncertainty Modeling and Analysis in Engineering and the Sciences

Cited by 277 publications

References 193 publications

Índice Fuzzy Para O Conforto Térmico De Suínos Na Fase De Crescimento E Terminação Com Base Na Temperatura Superficial E Frequencia Respiratória

Índice Fuzzy Para O Conforto Térmico De Suínos Na Fase De Crescimento E Terminação Com Base Na Temperatura Superficial E Frequencia Respiratória

Production of biofuels and biochemicals: in need of an ORACLE

Methods and concepts for the multi-criteria synthesis of ship structures

Contact Info

Product

Resources

About