scholarly journals Artificial Intelligence in Civil Engineering

2012 ◽  
Vol 2012 ◽  
pp. 1-22 ◽  
Author(s):  
Pengzhen Lu ◽  
Shengyong Chen ◽  
Yujun Zheng
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Systems ◽  
Firefly Algorithm ◽  
Civil Engineering ◽  
Complex Structure ◽  
Cuckoo Search ◽  
Research Trends ◽  
Main Research ◽  
Knowledge Based ◽  
Intelligent Computer

Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

CONTRIBUTION OF AI TO THE CONSTRUCTION WORLD

2021 ◽  
Vol 12 (1) ◽  
pp. 58-70
Author(s):  
Kanhaiya Kumar ◽  
◽  
Muskan Kumari
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Simulated Annealing ◽  
Chaos Theory ◽  
Fuzzy Systems ◽  
Firefly Algorithm ◽  
Civil Engineering ◽  
Complicated Structure ◽  
Know How ◽  
Intelligent Computer

Artificial intelligence is a department of computer science and information technological know-how, involved in the research, layout, and application of intelligent computer. Conventional techniques for modeling and optimizing complicated structure systems require big amounts of computing assets, and artificial-intelligence-primarily based solutions can frequently provide treasured alternatives for successfully solving problems inside the civil engineering. This paper summarizes currently evolved methods and theories within the growing path for programs of synthetic intelligence in civil engineering, such as evolutionary computation, neural networks, fuzzy systems, professional machine, reasoning, type, and learning, in addition to others like chaos theory, cuckoo seek, firefly algorithm, know-how-based engineering, and simulated annealing. The primary studies tendencies are also talked about in the end. The paper presents an overview of the advances of synthetic intelligence carried out in civil engineering.

An Intelligent Computer-Assisted Instruction System Designed for Rural Health Workers in Developing Countries

1992 ◽  
Vol 31 (03) ◽  
pp. 193-203 ◽  
Author(s):  
B. Auvert ◽  
V. Gilbos ◽  
F. Andrianiriana ◽  
W. E. Bertrand ◽  
X. Emmanuelli ◽  
...  
Keyword(s):  
Developing Countries ◽  
Decision Support ◽  
Rural Health ◽  
Health Workers ◽  
Computer Assisted Instruction ◽  
Computer Assisted ◽  
Instruction System ◽  
Knowledge Based ◽  
Assisted Instruction ◽  
Intelligent Computer

Abstract:This paper describes an intelligent computer-assisted instruction system that was designed for rural health workers in developing countries. This system, called Consult-EAO, includes an expert module and a coaching module. The expert module, which is derived from the knowledge-based decision support system Tropicaid, covers most of medical practice in developing countries. It allows for the creation of outpatient simulations without the help of a teacher. The student may practice his knowledge by solving problems with these simulations. The system gives some initial facts and controls the simulation during the session by guiding the student toward the most efficient decisions. All student answers are analyzed and, if necessary, criticized. The messages are adapted to the situation due to the pedagogical rules of the coaching module. This system runs on PC-compatible computer.

Survey of the State-of-the-Art Expert/Knowledge Based Systems in Civil Engineering.

1986 ◽  
Author(s):  
Simon S. Kim ◽  
Mary Lou Maher ◽  
Raymond E. Levitt ◽  
Martin F. Rooney ◽  
Thomas J. Siller
Keyword(s):  
Civil Engineering ◽  
Expert Knowledge ◽  
State Of The Art ◽  
The State ◽  
Knowledge Based Systems ◽  
Knowledge Based

Capturing and Using Designer Intent in a Design-With-Features System

1991 ◽  
Author(s):  
Eric H. Nielsen ◽  
John R. Dixon ◽  
George E. Zinsmeister
Keyword(s):  
Computer Aided Design ◽  
Simultaneous Equation ◽  
The Core ◽  
Knowledge Based ◽  
Evaluation Procedures ◽  
Equation Solving ◽  
Feature Based ◽  
Design Systems ◽  
Aided Design ◽  
Intelligent Computer

Abstract The goal of “intelligent” computer-aided-design (CAD) systems is to provide greater support for the process of design, as distinguished from drafting and analysis. More supportive design systems should provide a quick and simple means of creating and modifying design configurations, automating evaluation procedures (e.g., for manufacturing), and automating interfaces to analysis procedures. In this paper we are concerned with the issues of representing in-progress designs so that such goals can be met. A feature-based representation is proposed in which features are defined as possessing not only form but also certain designer intentions regarding geometric relationships. A working experimental version of a design-with-features system using this representation for thin-walled components illustrates its use in composing a design as a configuration of feature-forms, in modifying the design geometry through automatic, intelligent incorporation and propagation of designer-initiated geometry changes, and in providing for the generation of user-defined features. In contrast to constraint-driven simultaneous equation solving methods, this system uses an intent-driven knowledge-based method to propagate and incorporate geometry modifications not only in fully-constrained designs, but also in over- and under-constrained designs. Issues of manageability, extensibility, and computationally efficiency were considered in the development of the core services of the system.

Knowledge-Based Instructional Gaming: GEO

1989 ◽  
Vol 17 (3) ◽  
pp. 189-203 ◽  
Author(s):  
Philip Duchastel
Keyword(s):  
Artificial Intelligence ◽  
Types Of Knowledge ◽  
Knowledge Based ◽  
Instructional Gaming

Games have a fascination for people which make them ideal vehicles for instruction of an informal nature. Described here is an instructional game (GEO) in which the user learns elements of Canadian geography as she chases a spy around the country. The game utilizes artificial intelligence approaches to represent and put to use various types of knowledge (knowledge of geography, of tutoring, and of the student). Our experience in designing and refining the game is discussed, as well as prospects for extending this approach to other learning situations.

Design of Mine Ventilation Systems Based on Artificial Intelligence

2014 ◽  
Vol 614 ◽  
pp. 107-112
Author(s):  
Xiao Yu Yin ◽  
Xian Ping Xie ◽  
Zhen Li ◽  
Jian Gong Li ◽  
Ting Jun Wang ◽  
...  
Keyword(s):  
Expert System ◽  
Computer Aided Design ◽  
Design Method ◽  
Mine Ventilation ◽  
Design System ◽  
Knowledge Based ◽  
Aided Design ◽  
And Control ◽  
Intelligent Computer ◽  
Ventilation Systems

Expert systems, or knowledge based systems, are programs in which the answer to a user-posed question is reached by logical or plausible inference rather than strictly by calculation, although calculation routines can form a major part of an expert system. Based on the integration of expert system technology and optimization technology, an intelligent computer aided design method for mine ventilation systems is proposed in this paper. Firstly, the structure and control algorithm of the intelligent design system are explored. Secondly, the knowledge types required for the mine ventilation expert system and the acquiring method of knowledge are discussed. Finally, the inference method of this expert system is put forward.

scholarly journals Learning Social Media Content Optimization: How Can SMEs Draw the Users' Attention on Official WeChat Accounts?

2022 ◽  
Vol 12 ◽  
Author(s):  
Xueyun Zeng ◽  
Xuening Xu ◽  
Yenchun Jim Wu
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Psychological Needs ◽  
Media Content ◽  
Media Usage ◽  
Knowledge Based ◽  
Related Information ◽  
Artificial Intelligence Technology ◽  
Positive Effect ◽  
Content Optimization

Application of artificial intelligence is accelerating the digital transformation of enterprises, and digital content optimization is crucial to take the users' attention in social media usage. The purpose of this work is to demonstrate how social media content reaches and impresses more users. Using a sample of 345 articles released by Chinese small and medium-sized enterprises (SMEs) on their official WeChat accounts, we employ the self-determination theory to analyze the effects of content optimization strategies on social media visibility. It is found that articles with enterprise-related information optimized for content related to users' psychological needs (heart-based content optimization, mind-based content optimization, and knowledge-based content optimization) achieved higher visibility than that of sheer enterprise-related information, whereas the enterprise-related information embedded with material incentive (benefits-based content optimization) brings lower visibility. The results confirm the positive effect of psychological needs on the diffusion of enterprise-related information, and provide guidance for SMEs to apply artificial intelligence technology to social media practice.

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