scholarly journals One Step at a Time: The Origins of Sequential Simulation and Beyond

Author(s):  
J. Jaime Gómez-Hernández ◽  
R. Mohan Srivastava

AbstractIn the mid-1980s, still in his young 40s, André Journel was already recognized as one of the giants of geostatistics. Many of the contributions from his new research program at Stanford University had centered around the indicator methods that he developed: indicator kriging and multiple indicator kriging. But when his second crop of graduate students arrived at Stanford, indicator methods still lacked an approach to conditional simulation that was not tainted by what André called the ‘Gaussian disease’; early indicator simulations went through the tortuous path of converting all indicators to Gaussian variables, running a turning bands simulation, and truncating the resulting multi-Gaussian realizations. When he conceived of sequential indicator simulation (SIS), even André likely did not recognize the generality of an approach to simulation that tackled the simulation task one step at a time. The early enthusiasm for SIS was its ability, in its multiple-indicator form, to cure the Gaussian disease and to build realizations in which spatial continuity did not deteriorate in the extreme values. Much of Stanford’s work in the 1980s focused on petroleum geostatistics, where extreme values (the high-permeability fracture zones and the low-permeability shale barriers) have much stronger anisotropy, and much longer ranges of correlation in the maximum continuity direction, than mid-range values. With multi-Gaussian simulations necessarily imparting weaker continuity to the extremes, SIS was an important breakthrough. The generality of the sequential approach was soon recognized, first through its analogy with multi-variate unconditional simulation achieved using the lower triangular matrix of an LU decomposition of the covariance matrix as the multiplier of random normal deviates. Modifying LU simulation so that it became conditional gave rise to sequential Gaussian simulation (SGS), an algorithm that shared much in common with SIS. With nagging implementation details like the sequential path and the search neighborhood being common to both methods, improvements in either SIS or SGS often became improvements to the other. Almost half of the contributors to this Special Issue became students of André in the classes of 1984–1988, and several are the pioneers of SIS and SGS. Others who studied later with André explored and developed the first multipoint statistics simulation procedures, which are based on the same concept that underlies sequential simulation. Among his many significant intellectual accomplishments, one of the cornerstones of André Journel’s legacy was sequential simulation, built one step at a time.

2011 ◽  
Vol 62 (2) ◽  
pp. 99-103
Author(s):  
Vojtech Veselý

Stable Model Predictive Control Design: Sequential Approach The paper addresses the problem of output feedback stable model predictive control design with guaranteed cost. The proposed design method pursues the idea of sequential design for N prediction horizon using one-step ahead model predictive control design approach. Numerical examples are given to illustrate the effectiveness of the proposed method.


2019 ◽  
Vol 200 ◽  
pp. 13-26 ◽  
Author(s):  
Mahyadin Mohammadpour ◽  
Abbas Bahroudi ◽  
Maysam Abedi ◽  
Gholamreza Rahimipour ◽  
Golnaz Jozanikohan ◽  
...  

2004 ◽  
Vol 113 (4) ◽  
pp. 249-259 ◽  
Author(s):  
Xavier Emery ◽  
Julián M. Ortiz

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1160
Author(s):  
Yiming Xi ◽  
Xinquan Liu ◽  
Denis Constales ◽  
Gregory S. Yablonsky

The “conservatively perturbed equilibrium” (CPE) technique for a complex chemical system is computationally analyzed in a batch reactor considering different linear mechanisms with three and four species. Contrary to traditional chemical relaxation procedures, in CPE experiments only some initial concentrations are modified; other conditions, including the total amount of chemical elements and temperature are kept unchanged. Generally, for “unperturbed” species with initial concentrations equal to their corresponding equilibrium concentrations, unavoidable extreme values are observed during relaxation to the equilibrium. If the unperturbed species is involved in one step only, this extremum is a momentary equilibrium of the step; if the unperturbed species is involved in more reactions, the extremum is not a momentary equilibrium. The acyclic mechanism with four species may exhibit two extrema and an inflection point, which corresponds to an extremum of the rate of the species change. These facts provide essential information about the detailed mechanism of the complex reaction.


Irriga ◽  
2006 ◽  
Vol 11 (2) ◽  
pp. 178-187
Author(s):  
Francisco Edinaldo Pinto Mousinho ◽  
Aderson Soares de Andrade Júnior ◽  
Antônio Carlos Andrade Gonçalves ◽  
José Antonio Frizzone

VARIABILIDADE ESPACIAL DOS PERCENTIS 75 DA PRECIPITAÇÃO PLUVIAL ANUAL  PARA O ESTADO DO  PIAUÍ  Francisco Edinaldo Pinto Mousinho1; Aderson Soares de Andrade Júnior2; Antônio Carlos Andrade Gonçalves3; José Antonio Frizzone41Universidade Federal do Piauí, Campus Amílcar Ferreira Sobral,  Florian, -PI, [email protected] Meio-Norte, Teresina, -PI3Universidade Estadual de Maringá, Departamento de Agronomia, Maringá, PR4Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo, Piracicaba, SP  1 RESUMO No presente trabalho foi avaliada a variabilidade espacial dos percentis 75 da precipitação pluvial anual para o Estado do Piauí, empregando-se técnicas estatísticas descritivas e geoestatísticas. A estatística descritiva descartou a presença de valores extremos e confirmou o ajuste dos dados à distribuição normal, sendo realizada então a análise geoestatística. O semivariograma experimental foi melhor ajustado ao modelo  Gaussiano, mostrando nítida continuidade espacial do atributo estudado. Utilizando-se a krigagem ordinária, os valores dos percentis 75 foram estimados para locais não amostrados e a seguir gerado o mapa temático para o Estado do Piauí. Os percentis 75 apresentaram uma grande variabilidade espacial sendo os maiores valores observados no noroeste do Estado e os menores no sudeste, região semi-árida. A variância dos dados se aproximou do patamar do modelo de semivariograma, o que contribui para se pressupor a condição de estacionaridade do processo. O efeito pepita de 9200mm2 revelou  a variabilidade não explicada ou a possibilidade de existir dependência espacial em uma escala menor que a amostrada. Os percentis 75 da precipitação anual  apresentaram um alcance da dependência espacial da ordem de240 km, com forte continuidade espacial,  e a sua espacialização para o Estado do Piauí permitiu a visualização da sua distribuição. UNITERMOS: Precipitação pluviométrica, espacialização, geoestatística  MOUSINHO, F. E. P., ANDRADE JÚNIOR, A. S. , GONÇALVES, A. C. A., FRIZZONE, J. A. SPATIAL VARIABILITY OF ANNUAL 75 PERCENTIL PRECIPITATION  FOR PIAUI STATE  2 ABSTRACT In the present work the spatial variability of annual 75-percentile precipitation for Piauí  State, using descriptive statistical and geostatistics techniques, was evaluated. Descriptive statistics discarded the presence of extreme values and confirmed the data adjustment to normal distribution, and then geostatistical analysis was carried out. The experimental semivariogram was better adjusted to the Gaussian model, showing the spatial continuity of the studied matter. Using ordinary kriging, the 75 percentile values were estimated for non-sampled points and then a map was generated for PiauíState. 75 percentile values presented a great spatial variability with maximum values in the northwestern region and minimum values in the southeastern one, i.e., the semi-arid region.  Data semi variance was close to the semivariogram model sill and that contributes to presuppose the stationary process condition. The nugget effect value of 9200mm2 revealed the non-explained variability or the possibility of spatial dependence existence in a smaller scale than the sampled one. The annual 75-percentile precipitation presented a spatial dependence range of240 km, with strong spatial continuity, and its spatialization forPiauíState can be used for agricultural zoning state programs. KEYWORDS:  pluviometric precipitation, spatialization, geostatistics  3 INTRODUÇÃO A distribuição espacial da precipitação pluvial em uma determinada região é um dos fatores que refletem diretamente os diferentes níveis de desenvolvimento regional, principalmente o agrícola, pois dentre todas as atividades produtivas a agricultura é a que apresenta maior  dependência da ocorrência das chuvas, sendo esta a principal  responsável pela alternância das produções agrícolas anuais (Morais et al., 2001).No Estado do Piauí, onde predomina a agricultura de “sequeiro",  é de capital importância a realização de estudos sobre a distribuição espacial destas no seu território, tornando possível um planejamento regional criterioso quanto às culturas a serem exploradas e locais e épocas de cultivo, de modo a se obter, com um dado nível de probabilidade, um determinado nível de rendimento.       De acordo com Gomes & Cruz (2002), vários trabalhos têm sido feitos visando caracterizar a distribuição das precipitações pluviais, utilizando-se para tal as médias, sazonais ou anuais. Todavia, estas informações não são suficientemente confiáveis para fins de planejamento agrícola, constituindo um risco para o produtor, já a probabilidade de ocorrência das médias é de apenas 50%, justificando o uso de probabilidades não inferiores a 75% com vistas a minimizar estes  riscos (Gondim & Fernández Medina, 1980).A análise estatística clássica considera que os valores medidos de uma determinada variável são independentes, variando aleatoriamente no espaço, o que nem sempre é verdade. Contrariamente, a geoestatística considera a continuidade espacial da variável, tendo, assim, um amplo campo de utilização pois muitas variáveis têm nítida continuidade espacial e devem ser analisadas segundo a teoria das variáveis regionalizadas (Hamlett et al, 1986).De acordo com Gonçalves et al. (2001), a hipótese do ajuste dos valores de determinado atributo à distribuição normal geralmente não é testada, embora a realização de qualquer estudo estatístico ou geoestatístico assuma a condição de normalidade dos dados. Segundo Hamlett et al. (1986), a análise exploratória dos valores de uma determinada variável distribuída no espaço, é um procedimento indispensável em estudos geoestatísticos, pois, por meio deste se verifica o ajuste dos mesmos à distribuição normal. Gonçalves et al. (2001), também, ressaltaram a importância de uma cuidadosa análise de variáveis espacialmente distribuídas como etapa prévia de uma análise geoestatística.Com o conhecimento do padrão de variabilidade espacial de um atributo pode-se estimar valores  em locais não amostrados, sendo a krigagem o interpolador utilizado nos estudos geoestatísticos por ser não tendencioso e de variância mínima, assegurando a melhor estimativa. Utilizando-se uma grade regular de valores estimados através da krigagem pode-se elaborar mapas que representem a distribuição da variável em uma determinada região, os quais constituem uma das maneiras mais ilustrativas para  representar a espacialização de uma variável em uma determinada área.Face ao exposto, este trabalho teve por objetivo avaliar a variabilidade espacial dos percentis 75 da precipitação pluviométrica anual e realizar a sua espacialização para o Estado do Piauí, empregando-se técnicas estatísticas descritivas e geoestatísticas. 


Heritage ◽  
2019 ◽  
Vol 2 (2) ◽  
pp. 1045-1059
Author(s):  
Vera Mariz ◽  
Rosário Salema de Carvalho ◽  
Fernando Cabral ◽  
Maria Neto ◽  
Clara Moura Soares ◽  
...  

ORION is a digital art history research-oriented project focused on the study of art collections and collectors in Portugal, supported on a relational database management system. Besides the obvious advantage of organizing and systematizing an enormous amount of information, promoting its analysis, this database was specifically designed to highlight the relationships between data. Its relational capacity is not only one of the most relevant features of ORION, but a differentiating quality, one step forward in comparison to other international databases and studies that use digital methodologies. This article discusses the methods and the advantages of using ORION in research related to the history of collecting, art markets and provenance of art objects in Portugal, where it is the very first time that an approach such as this is intended, looking for a systematization of data that paves the way to the emergence of new research questions. Furthermore, and because ORION aims to share the data and knowledge with other projects, institutions and researchers, the database uses different international standards, such as data structure (CIDOC-OIC and Getty-CDWA), controlled vocabulary (Iconclass, Art and Architecture Thesaurus (AAT), Thesaurus of Geographic Names (TGN), and Union List of Artist Names (ULAN)) and communication and exchange of information (CIDOC-CRM).


Author(s):  
Tom Elfring ◽  
Kim Klyver ◽  
Elco van Burg

This book presents entrepreneurship as networking as a perspective. Persistent problems around the dominant “individual-opportunity” approach in the entrepreneurship field motivated the authors to focus on the social-interactive aspects and action orientation of entrepreneurship. The work promises to address the challenge of providing a more integrated account in which the entrepreneur’s agency is combined with a greater emphasis on the social environment. The importance of social relations and the associated interactions between entrepreneurs and their environment give insight into key entrepreneurial processes. The authors address the guiding questions of what a viable network is for (nascent) entrepreneurs and how networking activities affect their entrepreneurial endeavors. Therefore, they first create a synthesis of key network mechanisms and networking dynamics. This allows them (a) to shed new light on the origins of opportunities and improve understanding of how entrepreneurs access resources and subsequently mobilize and deploy them, and (b) to explain how entrepreneurs build legitimacy, facilitating them to act on perceived new combinations and thereby exploit their potential. Thus, this book highlights how networking is a central constitutive force in entrepreneurship. Previous work showed how networks can or will lead to entrepreneurial action as a facilitator. Going one step further, the authors posit that networking is entrepreneurial action, and entrepreneurial action is networking, thereby opening an entirely new research agenda.


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