Creative Design and the Generative Evolutionary Paradigm

Frazer, John

doi:10.1016/b978-155860673-9/50047-1

Cited by 53 publications

(33 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Such a complete and mature system is typi ed by my 'Evolutionary Digital Design Method' and described in An Evolutionary Architecture (1995). 19 But we have much further to go yet. Architecture does not address trivial problems, so a computer program of suf cient complexity to play an active role in building design needs to learn skills far beyond the knowledge and experience of the programmer.…”

Section: Adding Power To Parametricsmentioning

confidence: 97%

Parametric Computation: History and Future

Frazer¹

2016

Architectural Design

Self Cite

View full text Add to dashboard Cite

John Frazer is a pioneer and leader in the field of generative design and evolutionary computation. In the 1970s he developed the world's first microcomputer‐based design systems and invented tangible interfaces. Professor at the European Graduate School, he is the author of the seminal book An Evolutionary Architecture (1995). Here he traces the history of parametric architecture and discusses how, in its second state, redefined as Parametricism 2.0, Parametricism opens up the possibilities to become more than a matter of generational technique, scripting variational geometry, and a means to addressing wider social and environmental purpose.

show abstract

Section: Adding Power To Parametricsmentioning

confidence: 97%

Parametric Computation: History and Future

Frazer¹

2016

Architectural Design

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is advocated that this approach could enhance the system's capabilities by allowing the generation of complex forms with various details and layouts that would not be possible without using such a system. Several researchers have highlighted the benefits of using evolutionary design (Frazer, 2002;von Buelow, 2007;Janssen, 2006;Narahara et al, 2006). In addition, architectural design has benefited from the application of generative algorithm by adopting five different techniques: genetic algorithm, cellular automata, L-systems, swarm intelligence and shape grammars (Janssen, 2006).…”

Section: Generative Evolutionary Designmentioning

confidence: 99%

Virtual generative BIM workspace for maximising AEC conceptual design innovation

Abrishami

Goulding

Rahimian

et al. 2015

Construction Innovation

View full text Add to dashboard Cite

Access to this document was granted through an Emerald subscription provided by 549148 [] For AuthorsIf you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.The Architecture, Engineering, and Construction (AEC) sector is one of the largest industrial employers, representing 9.8% of a countries' Gross Domestic Product, and employing over 7.1% of the workforce (Business Watch, 2005). However, the fragmentation of the AEC industry is well recognised -the consequences of which have led to well-documented problems relating ostensibly to failures in communication and information processing (Egan, 1998;Latham, 1994). These failures have contributed to the proliferation of adversarial nature of the different parties involved in a project (Forcade et al., 2007), which has also affected the veracity of design information (Cera et al., 2002;Fruchter, 1998) within the project lifecycle. In essence, the nature and complexity of communication within AEC projects has changed significantly over the last ten years, especially with advances in technology, and the increased prevalence, of web-based project collaboration technologies and project extranets. Within the AEC sector, Information and Communication Technology has revolutionised production and design (Cera et al., 2002), which has led to dramatic changes in terms of labour and skills (Fruchter, 1998). However, it is also important to acknowledge that the capabilities of such applications (and implementation thereof) in predicting the cost and performance of optimal design proposals (Petric et al., 2002) should enable design engineers to compare the quality of any one tentative solution against the quality of previous solutions. This was reinforced by Goulding and Rahimian (2012), regarding the ability to experiment and experience decisions in a 'cyber-safe' environment, in order to mitigate or reduce risks prior to construction. Consequently, the success of AEC projects is highly dependent upon the 'type', 'level' and 'quality' of the innovative communication exchange of various disciplines involved in the design and implementation phases.One of the key debates with respect to advanced technology adoption to the AEC industry is the level of automation throughout the project lifecycle (Frohm et al., 200...

show abstract

“…Original designs usually require much research work, knowledge and skill, and creativity [Pahl et al, 2007]. The second case where a product is designed by modification of an existing one is known as evolutionary design [Frazer et al, 2002; Kicinger et al, 2005]. This design type is initiated and driven by ECs.…”

Section: Background Of the Proposed Literature Categorization Frammentioning

confidence: 99%

Analysis of tumor markers in cytological fluid obtained from computed tomography–guided needle aspiration biopsies for the diagnosis of ground‐glass opacity pulmonary lesions

Kim

Hur

Lee

et al. 2012

Cancer Cytopathology

View full text Add to dashboard Cite

BACKGROUND:The purpose of this study was to assess whether analyses of tumor markers in cytological fluid can improve the performance of computed tomography (CT)‐guided needle aspiration biopsy (NAB) for the diagnosis of ground‐glass opacity (GGO) pulmonary lesions.METHODS:Forty‐two patients were prospectively enrolled for CT‐guided NAB. Levels of cytokeratin 19 fragments (CYFRA 21‐1) and carcinoembryonic antigen (CEA) from serum and cytological fluid were measured. The cutoff values of 3.3 ng/mL for CYFRA 21‐1 and 5.0 ng/mL for CEA (threshold A) or thresholds by adding 2 standard deviations to the mean levels of markers found in patients without malignancy (threshold B) were used to identify malignancy. The sensitivity and area under the curve (AUC) of NAB alone were compared with those of NAB combined with serum or cytological tumor markers.RESULTS:Among the 42 patients, 30 (71.4%) had malignant and 12 (28.6%) had benign lesions. For NAB alone, the sensitivity, specificity, and AUC for diagnosing GGO were 70.0%, 100%, and 0.850, respectively. The sensitivity and AUC increased significantly for NAB with cytological CYFRA 21‐1 compared with NAB alone, using both thresholds (threshold A: 86.7%, P = .026 and .933, P = .016; threshold B: 93.3%, P = .008 and .925, P = .046).CONCLUSIONS:Cytological fluid measurements of CYFRA 21‐1 can improve the diagnostic performance of CT‐guided NAB for GGO pulmonary lesions. Cancer (Cancer Cytopathol) 2013;121:214–222. © 2012 American Cancer Society.

show abstract

Creative Design and the Generative Evolutionary Paradigm

Cited by 53 publications

References 1 publication

Parametric Computation: History and Future

Parametric Computation: History and Future

Virtual generative BIM workspace for maximising AEC conceptual design innovation

Analysis of tumor markers in cytological fluid obtained from computed tomography–guided needle aspiration biopsies for the diagnosis of ground‐glass opacity pulmonary lesions

Contact Info

Product

Resources

About