Abstracts:This paper proposes a reliability evaluation model for a multidimensional network system, which has potential to be applied to the internet of things or other practical networks. A multidimensional network system with one source element and multiple sink elements is considered first. Each element can connect with other elements within a stochastic connection ranges. The system is regarded as successful as long as the source element remains connected with all sink elements. An importance measure is proposed to evaluate the performance of non-source elements. Furthermore, to calculate the system reliability and the element importance measure, a multi-valued decision diagram based approach is structured and its complexity is analyzed. Finally, a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the element importance measure.

Abstracts:To address the confrontation decision-making issues in multi-round air combat, a dynamic game decision method is proposed based on decision tree for the confrontation of unmanned aerial vehicle (UAV) air combat. Based on game theory and the confrontation characteristics of air combat, a dynamic game process is constructed including the strategy sets, the situation information, and the maneuver decisions for both sides of air combat. By analyzing the UAV's flight dynamics and the both sides' information, a payment matrix is established through the situation advantage function, performance advantage function, and profit function. Furthermore, the dynamic game decision problem is solved based on the linear induction method to obtain the Nash equilibrium solution, where the decision tree method is introduced to obtain the optimal maneuver decision, thereby improving the situation advantage in the next round of confrontation. According to the analysis, the simulation results for the confrontation scenarios of multi-round air combat are presented to verify the effectiveness and advantages of the proposed method.

Abstracts:Project construction and development are an important part of future army designs. In today's world, intelligent warfare and joint operations have become the dominant developments in warfare, so the construction and development of the army need top-down, top-level design, and comprehensive planning. The traditional project development model is no longer sufficient to meet the army's complex capability requirements. Projects in various fields need to be developed and coordinated to form a joint force and improve the army's combat effectiveness, At the same time, when a program consists of large-scale project data, the effectiveness of the traditional, precise mathematical planning method is greatly reduced because it is time-consuming, costly, and impractical. To solve above problems, this paper proposes a rnulti-stage program optimization model based on a heterogeneous network and hybrid genetic algorithm and verifies the effectiveness and feasibility of the model and algorithm through an example. The results show that the hybrid algorithm proposed in this paper is better than the existing meta-heuristic algorithm.