Hybrid Computing Neural Network and its Application Based on Reverse Cloud Transformation
XU Shaohua
CHEN Yan
XU Chen
ZHANG Yaguang
Abstract：Aiming at the reasoning problems that the Mutual integration of the numerical information and qualitative do‐main knowledge ,this paper proposes a hybrid computing neural network (HCNN) based on cloud transformation was pro‐posed .Using the reverse normal cloud generator can achieve the conversion of the uncertain relationship between the quanti‐tative values and qualitative concept description ,and build the mixed information reasoning logic and HNN model based on cloud transformation . Then transforming the numerical information into qualitative concept in the sense of probability through the cloud transform ,and expressing the inference rules as neurons ,and using the learning nature of the neural net‐works to achieve adaptive processing of mixed quantitative and qualitative information .In algorithm design ,integrating net‐work properties parameters for a particle ,the hybrid particle swarm optimization (pso) algorithm for computing the neural network to the overall optimal solution .In the automatic identification of sedimentary microfacies in the study of petroleum geology ,the results verify the validity of the model and algorithm .
Keywords：process neural networkmembership cloudprocess reasoningtraining algorithmparticle swarm optimi-zation
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 2284-2288 )