BDES: A bridge design expert system

New functions and requirements of high performance building (HPB) being added and several regulations and certification conditions being reinforced steadily make it harder for designers to decide HPB designs alone. Although many designers wish to rely on HPB consultants for advice, not all projects can afford consultants. We expect that, in the near future, computer aids such as design expert systems can help designers by providing the role of HPB consultants. The effectiveness and success or failure of the solution offered by the expert system must be affected by the quality, systemic structure, resilience, and applicability of expert knowledge. This study aims to set the problem definition and category required for existing HPB designs, and to find the knowledge acquisition and representation methods that are the most suitable to the design expert system based on the literature review. The HPB design literature from the past 10 years revealed that the greatest features of knowledge acquisition and representation are the increasing proportion of computer-based data analytics using machine learning algorithms, whereas rules, frames, and cognitive maps that are derived from heuristics are conventional representation formalisms of traditional expert systems. Moreover, data analytics are applied to not only literally raw data from observations and measurement, but also discrete processed data as the results of simulations or composite rules in order to derive latent rule, hidden pattern, and trends. Furthermore, there is a clear trend that designers prefer the method that decision support tools propose a solution directly as optimizer does. This is due to the lack of resources and time for designers to execute performance evaluation and analysis of alternatives by themselves, even if they have sufficient experience on the HPB. However, because the risk and responsibility for the final design should be taken by designers solely, they are afraid of convenient black box decision making provided by machines. If the process of using the primary knowledge in which frame to reach the solution and how the solution is derived are transparently open to the designers, the solution made by the design expert system will be able to obtain more trust from designers. This transparent decision support process would comply with the requirement specified in a recent design study that designers prefer flexible design environments that give more creative control and freedom over design options, when compared to an automated optimization approach.

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An Intelligent User Friendly Interface for a Database Design Expert System

Systems Prospects ◽

10.1007/978-1-4613-0845-4_16 ◽

1989 ◽

pp. 93-96

Author(s):

J. Moses

Keyword(s):

Expert System ◽

Database Design ◽

Design Expert ◽

User Friendly

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Gaudii: An Automated Graphic Design Expert System

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v24i2.18811 ◽

2021 ◽

Vol 24 (2) ◽

pp. 1775-1780

Author(s):

Carlos Glez-Morcillo ◽

Victor Martin ◽

David Vallejo Fernandez ◽

Jose Castro-Schez ◽

Javier Albusac

Keyword(s):

Fuzzy Logic ◽

Expert System ◽

Evolutionary Computation ◽

Graphic Design ◽

Expert Knowledge ◽

Trial And Error ◽

Design Elements ◽

Design Expert ◽

Novel Approach ◽

Design Activities

Graphic design is the process of creating graphics to meet specific commercial needs based on knowledge of layout principles and esthetic concepts. This is usually an iterative trial and error process which requires a lot of time even for expert designers. This expert knowledge can be modelled, represented and used by a computer to perform design activities. This paper describes a novel approach named Gaudii (standing for "Intelligent Automated Graphic Design Generator") which utilizes principles and techniques known from the fields of Evolutionary Computation and Fuzzy Logic to automatically obtain design elements. Experimental results that demonstrate the potential of the proposed approach are presented in the area of poster design.

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Constraint Absorption and Relaxation Using a Design History

2nd International Conference on Design Theory and Methodology ◽

10.1115/detc1990-0126 ◽

1990 ◽

Author(s):

Edmund J. Meehan ◽

David C. Brown

Keyword(s):

Expert System ◽

Design History ◽

Design Constraints ◽

Limited Ability ◽

Design Expert ◽

Redundant Constraints ◽

Simple Mechanism ◽

Routine Design

Abstract A simple mechanism has been implemented and demonstrated within a routine design expert system. It has a limited ability to adjust design constraints based on experience within the domain. The mechanism is activated in response to noticing an extended run of either constraint failures or constraint successes. It reasons about the validity of either relaxing or absorbing a constraint. This process is referred to as Constraint Absorption. We hope to improve the performance of the expert system by reducing the incidence of repeated constraint failure, and by eliminating redundant constraints.

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An expert system for pneumatic design

Artificial intelligence for engineering design analysis and manufacturing ◽

10.1017/s0890060498121121 ◽

1998 ◽

Vol 12 (1) ◽

pp. 3-11 ◽

Cited By ~ 1

Author(s):

HEUNG-YEOUL SHIN ◽

JAE-WON LEE

Keyword(s):

Expert System ◽

Image Data ◽

Work Load ◽

Pneumatic System ◽

Design System ◽

Design Expert ◽

Reasoning Strategy ◽

Design Requirements ◽

System Prototype ◽

Configuration Information

One of the biggest problems in pneumatic system design is over design. Thus, the results are excessive in costs of the initial investment and it requires too much energy. This article describes the development of expert system based pneumatic design system, PNEUDES (PNEUmatic Design Expert System), prototype that enables the user the optimal design of pneumatic system. Once the design requirements such as cylinder type and work load, etc. are input to the system, optimal cylinder specifications with standardized order-based size, valves types, and necessary accessories are all determined. Also the configuration information such as the connectivity among components and cylinder image data are supplied to the user. It can also help the novice of pneumatic design. The rule-based reasoning approach is used as a reasoning strategy with Intelligent Rule Element shell.

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