Decision-making of Aircraft Optimum Configuration Utilizing Multidimensional Game Theory

As multi-discipline coupling and components interference often affect the aircraft configuration decision-making and analysis during conceptual design process, this article presents an approach of multidimensional game theory based on aircraft compo- nents to deal with this problem. The idea is that the configuration decision-making process is regarded as the game for different disciplines and technologies, and the aircraft components are players. The payoff function with highest total gain means that ac- cording to the game protocols and multidimensional theory, the optimal aircraft configuration within the strategy set will be cho- sen. The decision-making model is applied to conceptual design process of the high altitude long endurance （HALE） unmanned aerial vehicle （UAV） based on the assessment of technological risk. The obtained optimum configuration is quite consistent with the current HALE UAV development trends. Thus, taking into account the coupling and interference factors, the multidimensional gaming model based on aircraft components will be an effective analysis method in the decision-making process of aircraft optimum configuration.

An Efficient Multidimensional Fusion Algorithm for IoT Data Based on Partitioning

The Internet of Things （IoT） implies a worldwide network of interconnected objects uniquely addressable, via standard communication protocols. The prevalence of IoT is bound to generate large amounts of multisource, heterogeneous, dynamic, and sparse data. However, IoT offers inconsequential practical benefits without the ability to integrate, fuse, and glean useful information from such massive amounts of data. Accordingly, preparing us for the imminent invasion of things, a tool called data fusion can be used to manipulate and manage such data in order to improve process efficiency and provide advanced intelligence. In order to determine an acceptable quality of intelligence, diverse and voluminous data have to be combined and fused. Therefore, it is imperative to improve the computational efficiency for fusing and mining multidimensional data. In this paper, we propose an efficient multidimensional fusion algorithm for IoT data based on partitioning. The basic concept involves the partitioning of dimensions （attributes）, i.e., a big data set with higher dimensions can be transformed into certain number of relatively smaller data subsets that can be easily processed. Then, based on the partitioning of dimensions, the discernible matrixes of all data subsets in rough set theory are computed to obtain their core attribute sets. Furthermore, a global core attribute set can be determined. Finally, the attribute reduction and rule extraction methods are used to obtain the fusion results. By means of proving a few theorems and simulation, the correctness and effectiveness of this algorithm is illustrated.

Energy Politics and Security Concepts from Multidimensional Perspectives

Even though the foregoing theories on international relations give different interpretations on this issue,they are actually interactional and overlapping.Also they seem to share more and more common features.With the acceleration of economic globalization since the end of the Cold War,nation states are increasingly interdependent in the energy sector while competition and coordination become the mainstream of international energy politics.Consequently all parties have put growing importance on international energy cooperation and its institutional construction.They believe that energy security should be achieved through international cooperation and coordination,for it is closely linked with sustainable development of economy and society as well as the external political and economic relations of nation states.