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Pollution Prevention: Principles and Applications
Published in Jiaping Paul Chen, Decontamination of Heavy Metals, 2012
A knowledge-based system, sometimes called an expert system, is a system of rules based on an area of proven expert knowledge. It also can be used for hierarchical design and review procedures. Computer programs based on this system can simulate human thought processes and can therefore be used to design a cleaner manufacturing facility to produce less polluted (or greener) products. This system is essentially dependent on a long-term accumulation of expert knowledge. It can be used for a new plant design as well as a retrofit of an old plant. More recently, Halim and Srinivasan developed an intelligent system for qualitative waste minimization analysis.18 A knowledge-based expert system called ENVOP Expert was used to identify practical and cost-effective P2 programs. A case study of the hydrodealkylation process was tested with satisfactory results.
Technology of Intelligent Systems
Published in James A. Momoh, Mohamed E. El-Hawary, Electric Systems, Dynamics, and Stability with Artificial Intelligence Applications, 2018
James A. Momoh, Mohamed E. El-Hawary
There is a lot of confusion about terminology in the artificial intelligence literature because there are few standardization efforts. So in the following paragraph we present the definitions used in this chapter. A knowledge-based system is “a program in which the domain knowledge is explicit and separate from the program’s other knowledge.” It consists of the following five components: the knowledge base, the knowledge acquisition module, the inference engine, the explanation module, and the user interface (Fig. 7.3).
Expert COSYSMO Systems Engineering Cost Model and Risk Advisor
Published in Natalie M. Scala, James P. Howard, Handbook of Military and Defense Operations Research, 2020
Raymond Madachy, Ricardo Valerdi
A knowledge-based approach solves complex problems within a specific substantive domain, which this method applies to systems engineering risk. Knowledge-based systems solve problems that can’t be solved by individuals without domain specific knowledge. Expert systems and decision support systems are common types of knowledge-based systems. An expert system that is rule-based operates on a collection of rules that a human expert would follow in dealing with a problem.
Stream Reasoning to Improve Decision-Making in Cognitive Systems
Published in Cybernetics and Systems, 2020
Caterine Silva de Oliveira, Franco Giustozzi, Cecilia Zanni-Merk, Cesar Sanin, Edward Szczerbicki
In this context, methods incorporating prior knowledge and context information have gained interest. The understanding about scene composition in an image (which set of objects are present) can improve recognition performance about the scene where they are inserted (Zambrano et al. 2015). For instance, the presence of multiple cutlery items in an image can aid the recognition of a kitchen image. This relationship is held both ways, as contextual knowledge can also offer insights about the function of an object in a scene, reducing the impacts of sensor noise or occlusions (Aditya et al. 2017). These technologies are known as knowledge-based systems. For instance, an automatic semantic and flexible annotation service able to work in a variety of video analysis with little modification to the code using Set of Experience Knowledge Structure (SOEKS) was proposed in work by Zambrano et al. (2015). This system is a pathway toward cognitive vision and it is composed, basically, by the combinations of detection algorithms and an experience based approximation.
Multi-objective optimisation of a container ship lashing bridge using knowledge-based engineering
Published in Ships and Offshore Structures, 2019
KBE is an artificial intelligence technology that reuses previously designed experience, domain knowledge and professional knowledge to develop new designs. Through the knowledge of judgments and logical reasoning, the intelligent design of new products can be achieved (McMahon et al. 2004). A concise definition of KBE was given by Kim et al. (2012) that KBE originates from CAD and knowledge-based systems, and covers the full range of activities related to product lifecycle management and multi-disciplinary design optimisation. The development process of knowledge-based system follows the sequence of knowledge acquisition, knowledge representation and knowledge reasoning. It’s emphasised to reuse domain knowledge, expert experience and other kinds of knowledge in developing new designs, new and optimal products with the fastest speed (Zhou et al. 2007). Figure 1 shows the general process of knowledge acquisition and reproduction. The design process of new product by KBE is illustrated in Figure 2.
Cognitive evaluation for conceptual design: cognitive role of a 3D sculpture tool in the design thinking process
Published in Digital Creativity, 2018
Jeehyun Lee, Jiwon Ahn, Jieun Kim, Jeong Min Kho, Hyo Yon Paik
Design activity is composed of various activity modes, which can be sorted into design arguments and design moves (Goldschmidt 1991). The behavioural aspects of human activity, such as sketching, writing, working with computers, and many other types of activity, can be used to find satisfactory solutions to poorly defined design problems. In the human problem-solving process, design activity continues until the designer has achieved a satisfactory outcome. Because of the potential complexity of design problems and the environment, researchers can have reflective conversations about situations by going back and forth within a prior act (Oxman 2001). The cognitive model of design constitutes a conventional approach to modelling cognitive processes in design as a process of thinking and reasoning. Moreover, a cognitive model in design can be symbolically formulated in knowledge-based systems (Coyne et al. 1990), rule-based systems, and case-based systems (Oxman 1996).