Data classification system and method based on quantum fuzzy information

A technology of data classification and fuzzy information, applied in the field of data classification system based on quantum fuzzy information, to achieve the effect of fast processing

Pending Publication Date: 2021-04-20
CHENGDU UNIV OF INFORMATION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the problems existing in the prior art, the present invention provides a cross fusion of intuitionistic fuzzy set theory and quantum computing based on quantum fuzzy information, uses intuitionistic fuzzy set theory to describe uncertain problems, fuzzifies uncertain problems, and combines quantum computing in processing High efficiency on complexity and uncertainty issues, quantize fuzzy information; use quantum states as information processing units, improve traditional support vector machines into quantized fuzzy support vector machines, and classify hyperplane quadratic programming problems Transforming it into a linear equation problem that can be handled by a quantum computer provides an objective, efficient and accurate method for classifying uncertainty problems, laying a theoretical foundation for the study of quantum fuzzy machine learning algorithms

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  • Data classification system and method based on quantum fuzzy information
  • Data classification system and method based on quantum fuzzy information
  • Data classification system and method based on quantum fuzzy information

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Embodiment 1

[0051] Such as figure 1 As shown, the present embodiment provides a data classification system based on quantum fuzzy information, including: a quantum fuzzy input module, an improved fuzzy support vector machine classification module and an output module;

[0052] The quantum fuzzy input module is set to quantize the fuzzy elements in the problem domain and pass them to the improved fuzzy support vector machine classification module.

[0053] It should be understood that when dealing with the uncertainty of each element in the problem domain, the existing technologies can be divided into three categories: probability-based reasoning theory; credibility-based evidence theory; possibility-based theory. Possibility theory based on degree of membership; and fuzzy set theory based on degree of membership. The present invention uses fuzzy set theory to deal with uncertain elements in the problem domain.

[0054] Those skilled in the art can know that the key to fuzzifying uncerta...

Embodiment 2

[0061] Such as figure 2 As shown, this embodiment is developed on the basis of the above-mentioned embodiment 1, and in this embodiment, a specific method for data classification by the above-mentioned system is given.

[0062] Step S1. Fuzzify the elements in the problem domain, quantize the fuzzy information, and obtain the intuitionistic fuzzy set A={i ,μA(x i ), υ A (x i )>|x i ∈X}, where μ A (x i ) for x i The degree of membership to the intuitionistic fuzzy set A, v A (x i ) for x i The degree of non-membership to the intuitionistic fuzzy set A;

[0063] It should be understood that since this application chooses the fuzzy set theory based on the degree of membership, the method of fuzzifying the problem domain elements is to construct the intuitionistic fuzzy set of the problem domain elements.

[0064] Step S2. Coding the intuitionistic fuzzy set A into a quantum fuzzy training set, wherein the quantized fuzzy element x i for π A (x i )=1-μ A (x i )-v...

Embodiment 3

[0070] This embodiment is developed on the basis of the above-mentioned embodiment 1. In this embodiment, the specific components and principles of the quantum fuzzy input module are given.

[0071] The quantum fuzzy input module includes a fuzzy unit and a quantization unit;

[0072] The fuzzing unit is set to input the fuzzy element x i Transformed into an intuitionistic fuzzy set A, where A={i ,μ A (x i ), υ A (x i )>|x i ∈X}, μ A (x i ) for x i The degree of membership to the intuitionistic fuzzy set A, v A (x i ) for x i The degree of non-membership to the intuitionistic fuzzy set A;

[0073] The quantization unit is set to load all elements in the intuitionistic fuzzy set A to the quantum state under the condition of satisfying the normalization of the quantum state to obtain the quantum intuitionistic fuzzy set; wherein, the quantized fuzzy element x i for Among them, π A (x i )=1-μ A (x i )-v A (x i ), for x i The degree of hesitation on the intuitio...

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Abstract

The invention provides a data classification system and method based on quantum fuzzy information. The system comprises: a quantum fuzzy input module, wherein the quantum fuzzy input module is set to quantize fuzzy elements in a problem domain and then transmit the quantized fuzzy elements to the improved fuzzy support vector machine classification module; the improved fuzzy support vector machine classification module which is set to classify the quantized fuzzy elements by utilizing an improved quantized fuzzy support vector machine and transmit a classification result to the output module; the output module which decodes the quantized classification result and converts the quantized classification result into identifiable content for display; an improved quantization fuzzy support vector machine which is a fuzzy support vector machine which converts a quadratic programming problem into a linear equation set solving problem and carries out quantization processing. According to the system and method, the uncertainty problem is described by using the intuitionistic fuzzy set, information contained in each object in the uncertainty problem is objectively, accurately and comprehensively reflected, and the related problems are accurately and quickly processed by using the high-efficiency advantage of quantum computation in processing the complexity and uncertainty problems.

Description

technical field [0001] The invention belongs to the technical field of big data processing, and in particular relates to a data classification system and method based on quantum fuzzy information. Background technique [0002] With the explosive growth of data in various fields, classical information processing technology and quantum information processing technology have been greatly developed and widely used. By discovering and utilizing the valuable data and information hidden in big data, people have greatly facilitated life, work, study and scientific research, but at the same time it has caused many problems. On the one hand, due to the characteristics of complex structure, large scale, variety, and fast flow, big data poses many challenges to traditional computing theories and technologies. , the existing computational model theory is not competent; on the other hand, for the mining and analysis of big data, traditional computers can no longer meet the needs of task ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
Inventor 张仕斌黄曦李同侯敏昌燕闫丽丽
Owner CHENGDU UNIV OF INFORMATION TECH
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