Abstract: This paper considers the model testing for partially linear models with instrumental variables. By combining the instrumental variable method and the empirical likelihood method, an instrumental variable type testing procedure is proposed. The proposed testing procedure can attenuate the effect of endogeneity of covariates. Some simulations imply that the instrumental variable based empirical likelihood testing method is more poweful.
Abstract: Group operations is a emerging key problem for flight simulator training course. No matter the radar array in the ground or flight formation in the air, all need to track multiple targets at the same time. That means analyzing the correlation between detecting targets of sensors and known multiple aircraft is essential. So Multiple target data association is the research focus in this paper. Aimed at the research focus, this paper does research for modeling based on combinatorial optimization multi-target data association and bionic algorithm.
Abstract: In this paper, the analysis of optimizing test sets of which the optimal solutions are already known is made first. Then the optimization results and execution time of Determinant Elimination Method, Ant Colony Algorithms as well as Genetic Algorithm are compared. At last, Based on the concept of optimal test set proposed in this paper, plenty of test sets which need to be optimized are randomly generated. The optimization algorithm proposed in this paper is also used to optimize the test sets and the consequences of optimization is desirable.
Abstract: In order to achieve the optimal detection performance with the limited radar resources in the given defense area, the reasonable and effective deployment of radar netting is needed. According to the degree of importance of the detection region and the setting of the appropriate weighting coefficients of each of coverage, a mathematical model is established at the beginning. And then, on the base ofthe shuffled frog leaping algorithm (SFLA) principle, the solving process ofthe SFLA for this optimization problem is discussed in detail and the SFLA to expedite the solving velocity is presented. Finally, by analyzing an example and comparing the resultswith that of the ant colony algorithm (ACA), it comes to a conclusion that several network schemes can be obtained much more quickly in this way with better operability.
Abstract: The substance of the deployment of radar network is a multi-parameter optimization problem. This paper presents an objective function to deploy the radar network and a shuffled frog leaping algorithm (SFLA) is proposed to implement the radar network deployment. The proposed cultural shuffled frog leaping algorithm (CSFLA) makes use of mechanism of cultural evolution to update the locations of cultural frogs. Simulation results show that the proposed CSFLA has stronger abilities of exploitation and exploration by designing new leaping equations based on knowledge strategy and information communication, which may obviously improve the performance of SFLA. The radar network deployment based on the CSFLA is superior to previous deployment based on particle swarm optimization (PSO) and the SFLA in the convergence speed and optimization results. It provides a new idea to the radar network deployment.
Abstract: With the rapid development of economics and technology; the number of vehicles has largely increased. In this paper, traffic guidance and traffic control systems were researched as well as the Internet of Things (IOT). The author tried to combine these three parts to send traffic data to road users so as to let them choose the best route to travel. Meanwhile, traffic network optimization has been realized to reduce traffic congestion areas. This paper has optimized regional traffic signal control systems based on IOT, traffic guidance as well as traffic assignment, involved data sources, IOT design patterns, data collection as well as the relationship between guidance obeisance rate and traffic jam. It also involved the definition of ideal traffic shortest routes, planning and designing of traffic control systems. Results and researches could hope to combine with reality in order to reduce traffic congestion.
Abstract: Model Driven Architecture (MDA) as a software independent of the specific platform and software suppliers architecture design and development methodology has been great concern. The system is expanding at the same time, in order to solve the high reliability of embedded software development code, real-time, and the resulting system efficiency of the implementation issues, the paper used in the field of embedded software development according to MDA, and achieved good results. And this research work is summarized and analyzed, pointing out the challenges facing the sector and future research work.
Abstract: In data gathering application of Wireless Sensor Networks, the unbalanced load causes premature death of sensor nodes and shortens the network lifetime.The Dynamic Load-Balancing algorithm for Data Gathering Application is proposed.Motivated by the idea of pressure transfers and pressure balancing, the pressure transfers model and load-balancing model are proposed, by which the network can reach the maximum degree load-balancing step by step. Experimental results validate the effectiveness of this approach.
Abstract: With the rapid development of computer technology,wireless sensor network (WSN) is widely used in many fields of society, This paper introduces the characteristics of wireless sensor network and its routing protocol. Based on the hierarchical model, a dynamic selection of the sink node and the hierarchical model of multipath routing protocol is proposed which can balance the energy consumption of nodes, and it also can prolong the network lifetime, improve the data transfer rate.
Abstract: Considering the problem that the traditional fuzzy c-means (FCM) image segmentation algorithm is often caught in a specific range in local search and fails to get the globally optimal solution, this paper proposed a modified FCM algorithm based on chaotic simulated annealing (CSA). It traverse all the states without repetition within a certain range to calculate the optimal solution. Experimental results show that our method converges more quickly and accurately to the global optimal and proves a promise global optimization method of high adaptability and feasibility.