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The objective of this research is to improve the performance of marine electric power load forecasting based on PSO-Elman neural network. Considering the stochastic characteristics of marine power load variation, using the arbitrary approximation ability of Elman neural network, transform the prediction problem into a function fitting problem to establish a marine electric load forecasting model, and the Elman neural network learning method is optimized by particle swarm algorithm to avoid falling into local optimum. Simulation results obtained have shown that through the learning of a ship’s electrical load data, the load forecasting model based on PSO-Elman neural network can describe the changes in marine electrical load and improve the prediction accuracy and stability.

This paper analyzes the current mainstream open-source Open Stack cloud platform resource scheduling mechanism, and proposes an extensible resource optimization scheduling framework based on Open Stack. The framework divides the physical hyper visor host into multiple logical resource pools. It not only can configure global resources optimization strategy for individual resource pool, but also specify local resources optimization strategies for each resource pool. The results show that the multi-resource pool resource optimization scheduling optimization framework proposed in this article is good for Open Stack resource optimization, performance isolation and security isolation, and has a good extension.

Thermal characteristics of AlGaInP thin-film LED with transparent conducting ITO p-type contact by electrical method are presented and discussed. Samples without ITO fabricated from the same AlGaInP /GaAs epitaxial material are also prepared as references. The temperature coefficients of the samples are measured firstly and they are used as temperature sensitive parameters to determine the temperature rise. Heating response curves show that the temperature of chip in the sample with ITO is about 9K lower than the sample without ITO when the time of applying 60mA operation current exceeds 105µs. It can be also calculated that thermal resistance(from chip to ambient condition) of the sample with ITO is about 40K/W lower than the one without ITO. Finally we make the conclusion that the ITO layer is helpful for the thermal management of LED and it can improve the reliability the AlGaInP thin-film LED effectively.

According to the characteristics of Cluster of Workstation, we propose a new model called distribution of data before program running (DBR), and analyze the relationship between DBR and other parallel computation models in this paper. In the end, it proves that DBR can not only raise the performing efficiency of concurrent programs significantly, but also has better scalability.