The management of intelligence-assisted finite element analysis technology

Sharif, Amir M.

doi:10.1109/picmet.1997.653671

Cited by 3 publications

(3 citation statements)

References 73 publications

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“…Intelligent systems can provide many interesting means of problemsolving, decision support and process simulation, as can be seen from a review of the literature 27) . It has also become increasingly apparent that the greatest advantages in applying artificial intelligence, comes from taking advantage of the best aspects of each type of technology.…”

Section: Developing Agile Intelligent Systemsmentioning

confidence: 99%

“…For example, on-going research into the generation of finite element (FE) meshes, a genetic algorithm approach has been used to optimise interconnecting polygonals which may be used for numerical analysis schemes 26,27,28) (such as finite element analysis, FEA). This evolutionary AI method treated the meshing problem in terms of a solution to a multiobjective function relative to mesh distribution density, polygonal geometry and localised error estimates.…”

Section: )mentioning

confidence: 99%

“…These were as a means of helping users carry out mundane, data and evaluation-intensive processes, often with multiple and varying constraints 11) . The transfer of knowledge from humanexpert to computer-expert, has in essence become a de facto approach to the design of many intelligent systems in business and engineering 5,22,27) .…”

Section: Introductionmentioning

confidence: 99%

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Harnessing agile concepts for the development of Intelligent Systems

Sharif¹

1999

NGCO

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Traditional and current approaches to intelligent systems design, have led to the creation of sophisticated and computationally-intensive packages and environments, for a wide range of applications. This paper proposes methods with which to extend the functionality of such systems, borrowing knowledge management concepts from the field of Agile Manufacturing. As such, this paper proposes that the future of intelligent systems design should be based not only upon the continuing development of artificial intelligence techniques, but also effective methods for harnessing human skills and core competencies to achieve these aims.

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Section: Developing Agile Intelligent Systemsmentioning

confidence: 99%

Section: )mentioning

confidence: 99%

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Harnessing agile concepts for the development of Intelligent Systems

Sharif¹

1999

NGCO

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Feature-based fuzzy control adaptive finite-element mesh generation for electromagnetic fields

et al. 2005

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The application of artificial intelligence and machine learning in the design process for electromagnetic devices

Lowther

2023

JAE

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Designing an electromagnetic device, as with many other devices, is an inverse problem. The issue is that the performance and some constraints on the inputs are provided but the solution to the design problem is non-unique. Additionally, conventionally, at the start of the design process, the information on potential solutions needs to be generated quickly so that a designer can make effective decisions before moving on to detailed performance analysis, but the amount of information that can be obtained from simple analysis tools is limited. Machine learning may be able to assist by increasing the amount of information available at the early stages of the design process. This is not a new concept, in fact it has been considered for several decades but has always been limited by the computational power available. Recent advances in machine learning might allow for the creation of a more effective “sizing” stage of the design process, thus reducing the cost of generating a final design. The goal of this paper is to review some of the work in applying artificial intelligence to the design and analysis of electromagnetic devices and to discuss what might be possible by considering some examples of the use of machine learning in several tools used in conventional design, which have been considered over the past three decades.

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The management of intelligence-assisted finite element analysis technology

Cited by 3 publications

References 73 publications

Harnessing agile concepts for the development of Intelligent Systems

Harnessing agile concepts for the development of Intelligent Systems

Feature-based fuzzy control adaptive finite-element mesh generation for electromagnetic fields

The application of artificial intelligence and machine learning in the design process for electromagnetic devices

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