Abstract
On purpose of improving the research in interactive intelligent analysis system (IIAS) when the knowledge in hand is not sufficient, an intuition inversion learning model (IILM) based on experience and knowledge is presented. The paper introduces intuitionistic fuzzy mapping inversion (IFMI) method to the criminal investigation, and poses a skeleton of intuitionistic fuzzy reasoning. Through the relationship construction of practical crime model and on-the-spot model, it sets up a couple of mapping models intuitionistic fuzzy information acquisition. The study shows that the premise of automatic reasoning is to set up patterns of intuitionistic fuzzy relationship. The paper views that the reliability of the automatic reasoning depends on the man-computer interaction results. Simultaneously, choosing the case-cracking clue should be determined by comprehensive evaluations, and self-learning of intuition or fuzzy logical judgments are essentially needed. A simple example on how to create and apply the model is give. The presented model can be applied conveniently by selecting suitable IIAS in accordance with the give intuitive judge and computing the best decision from the rules in those IIAS.
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References
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He, P. (2010). An Interactive Intelligent Analysis System in Criminal Investigation. In: Luo, Q. (eds) Advancing Computing, Communication, Control and Management. Lecture Notes in Electrical Engineering, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05173-9_33
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DOI: https://doi.org/10.1007/978-3-642-05173-9_33
Publisher Name: Springer, Berlin, Heidelberg
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