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The domestic production network in China has been affected by multiple shocks in recent years, and this study reveals the dynamic changes of the shocks' effects. Based on a domestic trade model with industry-level unobserved factors, we examine the trends of multiple shocks to the domestic market of China's manufacturing industries and find that the domestic market has been bolstered by upward shocks until 2010, while has been depressed by downward shocks thereafter. Furthermore, based on multi-regional input–output analysis, we evaluate the impacts of domestic market shocks on industries' value-added in the domestic value chain (DVC). We find that from 2004 to 2012, the domestic market shocks significantly promoted industries to participate in DVC embodied in the global value chain (DVC1), while after 2012 the shocks began to promote industries to participate in DVC completely based on endogenous capabilities (DVC2). However, the DVC2 position has not been upgraded by domestic market shocks. From another perspective, we investigate the impacts of domestic market shocks on the industrial linkage structure and find that the impact on industries' centrality turns from negative to positive after the 2008 global financial crisis. [ABSTRACT FROM AUTHOR]

Air combat situation assessment is the basis of target assignment and maneuver decisions. The current air combat situation assessment models, whether nonparametric or parametric, ignore the continuity and timing of situation changes, making the situation assessment results lose tactical significance. Aimed at the shortcomings of current air combat situation assessment, a dynamic air combat situation assessment model based on situation knowledge extraction and weight optimization was proposed by combining a multiple regression model of hidden logic process, a weight optimization model based on grey prospect theory, a weight mapping model based on autoencoder and extreme learning machine (AE-ELM) and an air combat situation characteristic parameter prediction model based on dynamic weight online extreme learning machine (DWOSELM). Firstly, considering the timing and continuity of air combat situation change, a hidden logic process multiple regression model was introduced to realize the segmentation of air combat situation time series data and the extraction of air combat situation primitives. Secondly, the weight optimization method based on grey prospect theory was used to obtain the weight of the evaluation index under different air combat situations. On this basis, the dynamic mapping model between air combat situation characteristic parameters and the weight of index was constructed by using AE-ELM. Then, the dynamic weighted extreme learning machine was used to build the target maneuver trajectory prediction model, and the future position information of the target was predicted. On this basis, the future situation information between the enemy and us was obtained. Finally, the time weight calculation model based on normal cumulative distribution was used to determine the importance of the situation at each time. The situation information at multiple times in the air combat process was fused to obtain the comprehensive air combat situation assessment results at the current time. The simulation results show that the model can fully exploit the influence of historical information, effectively integrate the air combat situation information at multiple moments, and generate the air combat situation assessment results with practical tactical significance according to the individual differences of different pilots. [ABSTRACT FROM AUTHOR]

As the only low‐latitude connection along the return branch of the Great Conveyor Belt, the Indonesian Throughflow (ITF) plays an important role in the large‐scale ocean–atmosphere interaction in the tropical region. However, the heat transport processes of the ITF along the outflow pathway in the eastern Indian Ocean over the recent geologic period is still debated. In this study, by using Mg/Ca ratios of the surface‐dwelling and thermocline‐dwelling planktonic foraminifera Globigerinoides ruber and Pulleniatina obliquiloculata, we reconstruct sea surface temperature and thermocline water temperature (TWT), and thermocline structure at two sites in the main outflow path of the ITF in the eastern Indian Ocean for the last 160 Kyr, and compare these new data with those from two cores in the central Indo‐Pacific Warm Pool. Our results show that, on the orbital time scale, the thermocline structure changes above the equatorial 90°E Ridge mimic those of the eastern Timor Sea, indicating that the ITF vertical structure remained unchanged during its penetration into the Indian Ocean. The TWT in the equatorial western Pacific and eastern Indian Ocean presents similar change trend, suggesting that the ITF is likely to be an important route for thermocline water transport into the Indian Ocean. However, the vertical structure of the ITF varied through time, reflecting the effects of sea level and orbitally‐driven monsoonal activity. This impacted heat transport processes, resulting in changes in the surface water temperature along the outflow pathway in the eastern Indian Ocean. Key Points: Sea surface and thermocline water temperatures and vertical structure of the Indonesian Throughflow (ITF) outflow for the last 160 Kyr were reconstructedVertical structure of the ITF remained unchanged during its penetration into the Indian OceanVariation of the ITF through time impacted the heat transport processes along the outflow pathway in the eastern Indian Ocean [ABSTRACT FROM AUTHOR]

This study examines multiple shocks to the external market of China's manufacturing industry based on a trade model with multi-level unobserved factors. We find that the global external market of main industries is suffering constant downward shocks since 2008, while the traditional (non-traditional) markets are further affected by downward (upward) shocks. Private enterprises are more sensitive to shocks. Further, the adjustment of US trade policy toward China has caused China's exports to the US to deviate from the normal path by around 10% from 2015 to 2019, while having no significant effect on China's exports to the other traditional markets. [ABSTRACT FROM AUTHOR]

Autonomous air combat by the unmanned aerial vehicle (UAV) will be one of the main forms of air combat in the future. To solve the problems of simple assumption, complicated calculation and large scale on close range autonomous air combat, an autonomous air combat decision-making method based on basic flight maneuver (BFM) is proposed to ensure the effectiveness and timeliness in the research on the lvsl autonomous air combat with short-range missiles. Firstly, a score function to quantitatively evaluate the air combat situation is designed according to the missile attack zone (AZ). Secondly, a geometric model to predict the target position is established. Then, a guidance method is proposed based on the error compensation of position and velocity. Finally, offensive and defensive situations are set up in the simulation, and the experimental results show the effectiveness and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

In view of the problem that the existing air combat decision-making methods do not have an complete consideration for multi-fighter air combat, in the context of air combat before contacting enemy, this paper improves the existing methods from three aspects. The substitutes the combat power field for superiority functions. This reflects the influence of equipment performance on decition-making, second, it achieves preliminary target assignment based on giving full play to the multi-target attack abiliy and improving cooperative efficiency. Third, it introduces the coefficient of target importance and yield, aiming to take the multi-objective processing capability of radar and the rationality of attack resources allocation into consideration Finally, tt solves the index function based on the extrapolation and particle swarm optimization simulation result proves the effectiveness of the improved content The result of research shows that the improved decision-making method is more consistent wtth the ar combat reality. It also has a better cooperative efficiency than the method before improvement [ABSTRACT FROM AUTHOR]

The present paper attempts to find the optimal coverage path for multiple robots in a given area including obstacles. For single robot coverage path planning (CPP) problem, an improved ant colony optimization (ACO) algorithm is proposed to construct the best spanning tree and then obtain the optimal path, which contributes to minimizing the energy/time consumption. For the multirobot case, first the DARP (Divide Areas based on Robots Initial Positions) algorithm is utilized to divide the area into separate equal subareas, so much so that it transforms the mCPP problem into several CPP problems, degrading the computation complexity. During the second phase, spanning tree in each subarea is constructed by the aforementioned algorithm. In the last phase, the specific end nodes are exchanged among subareas to achieve ideal-shaped spanning trees, which can also decrease the number of turns in coverage path. And the complete algorithms are proven to be approximately polynomial algorithms. Finally, the simulation confirms the complete algorithms’ advantages: complete coverage, nonbacktracks, minimum length, zero preparation time, and the least number of turns. [ABSTRACT FROM AUTHOR]

The Perron–Frobenius eigenvalue (PFE) is widely used as measurement of the number of loops in networks, but what exactly the relationship between the PFE and the number of loops in networks is has not been researched yet, is it strictly monotonically increasing? And what are the relationships between the PFE and other measurements of loops in networks? Such as the average loop degree of nodes, and the distribution of loop ranks. We make researches on these questions based on samples of ER random network, NW small-world network and BA scale-free network, and the results confirm that, both the number of loops in network and the average loop degree of nodes of all samples do increase with the increase of the PFE in general trend, but neither of them are strictly monotonically increasing, so the PFE is capable to be used as a rough estimative measurement of the number of loops in networks and the average loop degree of nodes. Furthermore, we find that a majority of the loop ranks of all samples obey Weibull distribution, of which the scale parameter A and the shape parameter B have approximate power-law relationships with the PFE of the samples. [ABSTRACT FROM AUTHOR]

Multiobjective weapon-target assignment is a type of NP-complete problem, and the reasonable assignment of weapons is beneficial to attack and defense. In order to simulate a real battlefield environment, we introduce a new objective—the value of fighter combat on the basis of the original two-objective model. The new three-objective model includes maximizing the expected damage of the enemy, minimizing the cost of missiles, and maximizing the value of fighter combat. To solve the problem with complex constraints, an improved nondominated sorting algorithm III is proposed in this paper. In the proposed algorithm, a series of reference points with good performances in convergence and distribution are continuously generated according to the current population to guide the evolution; otherwise, useless reference points are eliminated. Moreover, an online operator selection mechanism is incorporated into the NSGA-III framework to autonomously select the most suitable operator while solving the problem. Finally, the proposed algorithm is applied to a typical instance and compared with other algorithms to verify its feasibility and effectiveness. Simulation results show that the proposed algorithm is successfully applied to the multiobjective weapon-target assignment problem, which effectively improves the performance of the traditional NSGA-III and can produce better solutions than the two multiobjective optimization algorithms NSGA-II and MPACO. [ABSTRACT FROM AUTHOR]

We build a complex networks model of combat System-of-Systems (SoS) based on empirical data from a real war-game, this model is a combination of command & control (C2) subnetwork, sensors subnetwork, influencers subnetwork and logistical support subnetwork, each subnetwork has idiographic components and statistical characteristics. The C2 subnetwork is the core of whole combat SoS, it has a hierarchical structure with no modularity, of which robustness is strong enough to maintain normal operation after any two nodes is destroyed; the sensors subnetwork and influencers subnetwork are like sense organ and limbs of whole combat SoS, they are both flat modular networks of which degree distribution obey GEV distribution and power-law distribution respectively. The communication network is the combination of all subnetworks, it is an assortative Small-World network with core–periphery structure, the Intelligence & Communication Stations/Command Center integrated with C2 nodes in the first three level act as the hub nodes in communication network, and all the fourth-level C2 nodes, sensors, influencers and logistical support nodes have communication capability, they act as the periphery nodes in communication network, its degree distribution obeys exponential distribution in the beginning, Gaussian distribution in the middle, and power-law distribution in the end, and its path length obeys GEV distribution. The betweenness centrality distribution, closeness centrality distribution and eigenvector centrality are also been analyzed to measure the vulnerability of nodes. [ABSTRACT FROM AUTHOR]

The weapon-target assignment (WTA) problem, known as an NP-complete problem, aims at seeking a proper assignment of weapons to targets. The biobjective WTA (BOWTA) optimization model which maximizes the expected damage of the enemy and minimizes the cost of missiles is designed in this paper. A modified Pareto ant colony optimization (MPACO) algorithm is used to solve the BOWTA problem. In order to avoid defects in traditional optimization algorithms and obtain a set of Pareto solutions efficiently, MPACO algorithm based on new designed operators is proposed, including a dynamic heuristic information calculation approach, an improved movement probability rule, a dynamic evaporation rate strategy, a global updating rule of pheromone, and a boundary symmetric mutation strategy. In order to simulate real air combat, the pilot operation factor is introduced into the BOWTA model. Finally, we apply the MPACO algorithm and other algorithms to the model and compare the data. Simulation results show that the proposed algorithm is successfully applied in the field of WTA which improves the performance of the traditional P-ACO algorithm effectively and produces better solutions than the two well-known multiobjective optimization algorithms NSGA-II and SPEA-II. [ABSTRACT FROM AUTHOR]

The paper aims at developing an efficient method to acquire a proper UCAV formation structure with robust and synchronized features. Here we introduce the RTBA (Route Temporary Blindness Avoidance) model to keep the structure stable and the HPSO (hybrid particle swarm optimization) method is given to find an optimal synchronized formation. The major contributions include the following: (1) setting up the dynamic hierarchy topologic structure of UCAV formation; (2) the RTB phenomenon is described and the RTBA model is put forward; (3) the node choosing rules are used to keep the invulnerability of the formation and the detective information quantifying method is given to measure the effectiveness of the connected nodes; and (4) the hybrid particle swarm optimization method is given to find an optimal synchronized topologic structure. According to the related principles and models, the simulations are given in the end, and the results show that the simplification of the model is available in engineering, and the RTBA model is useful to solve the real problems in combat in some degree. [ABSTRACT FROM AUTHOR]