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Besides conventional methods, intelligent system designs are seem to be more useful to improve efficiency of renewable energy systems.
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However, plant metabolic engineering currently proceeds more by trial and error than by intelligent system design.
A satisfaction-based approximation space for patterns extracted from intelligent system design models is introduced.
Though system performance is optimized by many different techniques, however, intelligent system design is an useful technique to optimize the efficiency of such systems.
This article introduces an approximation space for graded acceptance of proposed models for intelligent system design relative to design patterns that conform to a design standard.
It is not generally known how to measure the extent that a particular intelligent system design conforms to a standard design pattern.
The intelligent system designed basically consists of these parts: States Encoding, Console Automaton, Vehicle Automaton, Communication System and Security of Communications.
Association rule mining is one of the most important techniques for intelligent system design and has been widely applied in a large number of real applications.
A low-cost intelligent system designed in a single chip with the task to carry out the complete functionality for the greenhouse climate control was developed.
The rough set approach introduced by Zdzisław Pawlak provides a ground for concluding to what degree a particular model for an intelligent system design is a part of a set of a set of models representing a standard.
Looking at existing literature in tourism, this paper discusses critical gaps in the knowledge of the field to be filled so that intelligent system design can be informed and impacts understood.
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