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The present work is based on the assumption that the common classification-based approaches to time series interpretation suffer from a set of inherent weaknesses, whose ultimate cause lies in the monotonic nature of the deductive reasoning paradigm.
The main result of this study covers a variety of four reasoning methodologies, which reveals that case based reasoning paradigm is the best reasoning technique methodology regarding to the issues of maintenance,powerful and knowledge representations.
Complex AI systems tend to comprise a suite of modules, each of which is capable of solving a different aspect of the overall problem, and each of which may incorporate a different reasoning paradigm.
The approach is based on the quantified fuzzy temporal rules (QFTRs) knowledge representation and reasoning paradigm, that is able to analyze the spatio-temporal patterns that are associated to people.
The paper considers application of the case-based reasoning paradigm for solving of the problem related to computer-aided identification of technical states for mechanical systems employed in petrochemistry.
This study presents a classification tool called MicroCBR that uses the case-based reasoning paradigm and incorporates a novel filtering technique based on statistical methods, a new clustering technique that uses ESOINN (Enhanced Self-Organizing Incremental Neuronal Network), and a knowledge extraction technique based on the J48 algorithm.
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This system is based on an integration of different reasoning paradigms: rule-based reasoning, case-based reasoning, and model-based reasoning.
Our approach to designing an integrated knowledge-based system that provides advice concerning such ecosystems is to incorporate various reasoning paradigms.
Such methodology exploits the integration of case based reasoning (CBR) and rule based reasoning (RBR), with the aim of helping physicians during therapy planning, by overcoming the intrinsic limitations shown by the independent application of the two reasoning paradigms.
For instance, in the most commonly used reasoning paradigms, subjects are confronted with a choice between two bowls, one of which is baited.
The case-based reasoning (CBR) paradigm developed in the context of artificial intelligence intends to simulate this type of problem-solving behaviour [ 10].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com