A multiple-domain knowledge based system: Coordination and integration of agronomic and economic knowledge bases with databases and bio-economic models

1995 ◽  
Vol 48 (2) ◽  
pp. 141-161 ◽  
Author(s):  
Z. Hochman ◽  
P.T. Mears ◽  
R.J. Farquharson ◽  
J.H. Hindmarsh ◽  
C.J. Pearson
1995 ◽  
Vol 48 (3) ◽  
pp. 243-270 ◽  
Author(s):  
Z. Hochman ◽  
H. Hearnshaw ◽  
R. Barlow ◽  
J.F. Ayres ◽  
C.J. Pearson

Author(s):  
Shun-Chieh Lin ◽  
◽  
Chia-Wen Teng ◽  
Shian-Shyong Tseng ◽  

Knowledge acquisition is a critical bottleneck in building a knowledge-based system. Much research and many tools have been developed to acquire domain knowledge with embedded rules that may be ignored in constructing the initial prototype. Due to different backgrounds and dynamic knowledge changing over time, domain knowledge constructed at one time may be degraded at any time thereafter. Here, we propose knowledge acquisition, called enhanced embedded meaning capturing under uncertainty deciding (enhanced EMCUD), which constructs a domain ontology and traces information over time to efficiently update time-related domain knowledge based on the current environment. We enrich the knowledge base and ease the construction of domain knowledge that changes with times and the environment.


Author(s):  
V.C. MOULIANITIS ◽  
A.J. DENTSORAS ◽  
N.A. ASPRAGATHOS

The paper presents a knowledge-based system (KBS) for the conceptual design of grippers for handling fabrics. Its main purpose is the integration of the domain knowledge in a single system for the systematic design of this type of grippers. The knowledge presented, in terms of gripper, material and handling process, are classified. The reasoning strategy is based upon a combination of a depth-first search method and a heuristic method. The heuristic search method finds a final solution from a given set of feasible solutions and can synthesize new solutions to accomplish the required specifications. Details of the main features of the system are given, including its ability to take critical design decisions according to four criteria, weighted by the designer. The knowledge-based system was implemented in the Kappa P. C. 2.3.2 environment. Two examples are given to illustrate some critical aspects concerning the KBS development, to explain the operation of the proposed searching heuristic method, and to show its effectiveness in producing design concepts for grippers.


Author(s):  
P Olley ◽  
A K Kochhar

This paper addresses the issues of using a learning mechanism for closed-loop updating of the repair knowledge base of a working knowledge-based system (KBS). Issues addressed are stability under noisy data and errors arising from learning from cases in which several repairs are attempted. Simulated data are used to investigate the effects of the latter feature. It is shown that the learning method can cause a significant systematic error in learnt knowledge. A knowledge-based method, which aims to intelligently compensate for the systematic error using diagnostic domain knowledge, is investigated. It is shown that the method greatly reduces the systematic error in learnt repair knowledge.


1994 ◽  
Vol 33 (05) ◽  
pp. 454-463 ◽  
Author(s):  
A. M. van Ginneken ◽  
J. van der Lei ◽  
J. H. van Bemmel ◽  
P. W. Moorman

Abstract:Clinical narratives in patient records are usually recorded in free text, limiting the use of this information for research, quality assessment, and decision support. This study focuses on the capture of clinical narratives in a structured format by supporting physicians with structured data entry (SDE). We analyzed and made explicit which requirements SDE should meet to be acceptable for the physician on the one hand, and generate unambiguous patient data on the other. Starting from these requirements, we found that in order to support SDE, the knowledge on which it is based needs to be made explicit: we refer to this knowledge as descriptional knowledge. We articulate the nature of this knowledge, and propose a model in which it can be formally represented. The model allows the construction of specific knowledge bases, each representing the knowledge needed to support SDE within a circumscribed domain. Data entry is made possible through a general entry program, of which the behavior is determined by a combination of user input and the content of the applicable domain knowledge base. We clarify how descriptional knowledge is represented, modeled, and used for data entry to achieve SDE, which meets the proposed requirements.


2013 ◽  
Vol 1 (1) ◽  
pp. 158-178
Author(s):  
Urcun John Tanik

Cyberphysical system design automation utilizing knowledge based engineering techniques with globally networked knowledge bases can tremendously improve the design process for emerging systems. Our goal is to develop a comprehensive architectural framework to improve the design process for cyberphysical systems (CPS) and implement a case study with Axiomatic Design Solutions Inc. to develop next generation toolsets utilizing knowledge-based engineering (KBE) systems adapted to multiple domains in the field of CPS design automation. The Cyberphysical System Design Automation Framework (CPSDAF) will be based on advances in CPS design theory based on current research and knowledge collected from global sources automatically via Semantic Web Services. A case study utilizing STEM students is discussed.


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