A dynamic parallel forecasting model is proposed, which is based on the problem of current forecasting models and their combined model. According to the process of the model, the fuzzy C-means clustering algorithm is ...A dynamic parallel forecasting model is proposed, which is based on the problem of current forecasting models and their combined model. According to the process of the model, the fuzzy C-means clustering algorithm is improved in outliers operation and distance in the clusters and among the clusters. Firstly, the input data sets are optimized and their coherence is ensured, the region scale algorithm is modified and non-isometric multi scale region fuzzy time series model is built. At the same time, the particle swarm optimization algorithm about the particle speed, location and inertia weight value is improved, this method is used to optimize the parameters of support vector machine, construct the combined forecast model, build the dynamic parallel forecast model, and calculate the dynamic weight values and regard the product of the weight value and forecast value to be the final forecast values. At last, the example shows the improved forecast model is effective and accurate.展开更多
The efficiency of reconciliation in the continuous key distribution is the main factor which limits the ratio of secret key distribution. However, the efficiency depends on the computational complexity of the algorith...The efficiency of reconciliation in the continuous key distribution is the main factor which limits the ratio of secret key distribution. However, the efficiency depends on the computational complexity of the algorithm. This paper optimizes the two main aspects of the reconciliation process of the continuous key distribution： the partition of interval and the estimation of bit. We use Gaussian approximation to effectively speed up the convergence of algorithm. We design the estimation function as the estimator of the SEC （sliced error correction） algorithm. Therefore, we lower the computational complexity and simplify the core problem of the reconciliation algorithm. Thus we increase the efficiency of the reconciliation process in the continuous key distribution and then the ratio of the secret key distribution is also increased.展开更多
基金supported by the National Defense Preliminary Research Program of China(A157167)the National Defense Fundamental of China(9140A19030314JB35275)
文摘A dynamic parallel forecasting model is proposed, which is based on the problem of current forecasting models and their combined model. According to the process of the model, the fuzzy C-means clustering algorithm is improved in outliers operation and distance in the clusters and among the clusters. Firstly, the input data sets are optimized and their coherence is ensured, the region scale algorithm is modified and non-isometric multi scale region fuzzy time series model is built. At the same time, the particle swarm optimization algorithm about the particle speed, location and inertia weight value is improved, this method is used to optimize the parameters of support vector machine, construct the combined forecast model, build the dynamic parallel forecast model, and calculate the dynamic weight values and regard the product of the weight value and forecast value to be the final forecast values. At last, the example shows the improved forecast model is effective and accurate.
基金the National Natural Science Foundation of China (Grant No. 60773085)
文摘The efficiency of reconciliation in the continuous key distribution is the main factor which limits the ratio of secret key distribution. However, the efficiency depends on the computational complexity of the algorithm. This paper optimizes the two main aspects of the reconciliation process of the continuous key distribution： the partition of interval and the estimation of bit. We use Gaussian approximation to effectively speed up the convergence of algorithm. We design the estimation function as the estimator of the SEC （sliced error correction） algorithm. Therefore, we lower the computational complexity and simplify the core problem of the reconciliation algorithm. Thus we increase the efficiency of the reconciliation process in the continuous key distribution and then the ratio of the secret key distribution is also increased.
