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Quantum neural network-based comprehensive evaluation method for multi-factor system

A quantum neural, comprehensive evaluation technology, applied in the field of comprehensive evaluation of multi-factor systems, can solve problems such as cumbersome calculation, low accuracy rate, and long training time.

Inactive Publication Date: 2011-04-27
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0006] In order to overcome the shortcomings of the existing multi-factor system evaluation method, such as cumbersome calculation, low correct rate, and long training time, the present invention provides a quantum neural network-based multi-factor system that simplifies calculation, improves correct rate, and shortens training time comprehensive evaluation method

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  • Quantum neural network-based comprehensive evaluation method for multi-factor system
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  • Quantum neural network-based comprehensive evaluation method for multi-factor system

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Embodiment Construction

[0037] The present invention will be further described below in conjunction with the accompanying drawings.

[0038] refer to Figure 1 ~ Figure 3 , a multi-factor system comprehensive evaluation method based on quantum neural network, the method is realized in classical computer simulation, a feed-forward quantum neuron is designed and a multi-factor receiver receiving signal is represented by a quantum register, and on this basis the design Multifactor detector based on quantum neural network.

[0039] The specific steps of the implementation method of quantum neural network for multi-factor system comprehensive evaluation are as follows: figure 1 As shown, the specific process is as follows:

[0040] 1): Design multiple feedforward quantum neuron models

[0041] The single feed-forward quantum neuron model designed by the present invention is as figure 2 As shown, the output of QNN in the figure is 1 qubit.

[0042] w 1 ,w 2 ,...,w n : The probability of the activati...

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Abstract

The invention discloses a quantum neural network-based comprehensive evaluation method for a multi-factor system. The method comprises the following steps of: 1) setting a plurality of feed-forward quantum nerve cells of the multi-factor system; 2) preparing a quantum register of n quantum bits; 3) taking l 0) or l 1) of the quantum register as the input of factor number of a user receiver, and taking l phi> as the output of the factor number, wherein l phi> is equal to the sum of costheta l 0) and sintheta l 1) ; 4) setting a parallel computing operator O which is used for the output quantum state of the comprehensive evaluation method for the multi-factor system and is updated and evolved; and 5) till the updated output quantum state and the change before update are in a permitted error range, namely the network state is stable, determining that a sending information sequence corresponding to the output quantum state is the detection result of the multi-factor system.

Description

technical field [0001] The invention relates to the field of comprehensive evaluation of complex systems, in particular to a comprehensive evaluation method for multi-factor systems. Background technique [0002] The comprehensive evaluation methods commonly used in domestic and foreign transportation system evaluation can be generally divided into: expert evaluation method, economic analysis method, operations research method and other mathematical methods. Due to its characteristics of large-scale parallel processing, fault tolerance, self-organization and self-adaptive ability and associative function, neural network has become a powerful tool for solving problems. It has played a significant role and is widely used in many scientific fields. According to its characteristics, researchers also discussed the application of neural network model in comprehensive evaluation. [0003] As an important part of artificial intelligence, the neural network method can avoid the sub...

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Application Information

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IPC IPC(8): G06N3/02
Inventor 董红召金凌黄智陈宁郭明飞郭海锋
Owner ZHEJIANG UNIV OF TECH
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