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We present a novel framework for the optimization and synthesis of complex reactor networks based on systems knowledge in an effort to overcome convergence and computational speed limitations associated with current reactor network synthesis technologies.
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Most early formulations are at least partly based on System 1 knowledge and have a tendency to bias unless one takes time for reflection through the influence of System 2. Robust data for predictive values may not exist or not be powerful enough to lead to safe closure.
In the MPC approach, control actions to a certain system are computed online based on existing system knowledge and future predictions rather than using off-line static results [13].
Burke [16] proposed the restraint-based recommendation system based on recommendation knowledge base while in [17] Burke proposed the case-based recommendation approach.
The system is based on the knowledge-based system approach, and is able to make recommendations of system feasibility, cell formation techniques and cell types.
Biometrics authentication and identification systems offer several advantages over systems based on knowledge or possession such as unsupervised (legacy) password/PIN-based systems and supervised (legacy) passport-based systems.
Towards this goal, we have developed a novel framework, called Discovery Informatics, that is based on knowledge-based systems, statistical machine learning, neural networks and genetic algorithms, for the rapid discovery and design of new materials such as fuel additives, rubber compounds, polymers, catalysts, and nanomaterials.
In contrast to insights into the significance of various single proteins based on model systems, the knowledge about the processes at the actual site of wound healing is still limited.
It rightly points out that one should be careful in changing classification systems based on limited knowledge and that perhaps discarding the term atypical ductal hyperplasia at the present time may be premature.
Based on a knowledge representation system working in the background this system can guide the user in entering all the necessary information while constantly checking the consistency of the resulting information.
This paper addresses an Arabic financial ontology and presents a methodology for creating ontologies based on declarative knowledge representation systems.
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