Considering the phenomenon that false information is diffused before real information in social networks, an information competition diffusion model is studied and the effects of different probabilities, the initial diffusion time of real information and the number of real information spreader nodes are analyzed and compared. It is found that reduing the probability of unknown nodes to diffuse false information can reduce the diffusion scope of false information. In addition, only when the delay diffusion time of real information is short, can the diffusion scope of false information be reduced and the coverage of real information be increased by increasing the probability of nodes to diffuse real information, increasing the initial number of real information spreader nodes and selecting nodes with greater degree to diffuse real information.

The current similarity-based link prediction methods ignore the ability of the optimal path to transfer similarity between nodes. To solve this problem, a link prediction method based on the optimal path similarity transmission matrix is proposed. Firstly, the influence of the optimal path between nodes on the information transmission capacity is analyzed, then the tight centrality between nodes is defined; secondly, the number of optimal paths and centrality is used to construct the similarity transmission matrix, and the local information between nodes and global attributes are integrated to evaluate the similarity between nodes. Finally, the proposed method is compared with other similarity-based algorithms in six real networks. The results show that the proposed algorithm has more accurate prediction accuracy and is more stable.

According to the study of “new” new economic geography, there are three “black boxes” in terms of the setting of firm productivity, the mechanism of knowledge spillover between firms, and the sources of the increase in agglomerated areas’ productivity. Based on the ideas and methods of Complexity and Agent-based Computational Economics, we use Genetic Algorithms to encode firms’ knowledge structure and develop an agent-based spatial economic evolution simulation platform to simulate the process of firms’ productivity improvement and spatial agglomeration through knowledge spillover and innovation. Simulation experiments demonstrate that the knowledge spillover leads to dynamic heterogeneity of firms, and the flow of firms between regions is progressive and bidirectional. Then, in the early stage of the spatial agglomeration process, the increase in regional productivity is due to the “pull-up effect” formed by the entry of high-efficiency firms and the combined effect of knowledge spillover, while in the later stage of the agglomeration process, the increase in regional productivity is mainly due to local knowledge spillover and the “pull-down effect” of the entry of low-efficiency firms.

Constructing an epidemic dynamic model and exploring the spreading law of epidemic have very important theoretical significance for epidemic prevention and control. Based on the existing homogeneous mixing model, in view of the increasingly obvious heterogeneity of individual contact relationships, and each individual is in a different contact relationship, a dynamic small-world network model that takes into account individual status. Contact tracking has been established to simulate the spread of the COVID-19 in society. By comparing the simulation results, the rationality of the built model is explained. On this basis, the simulation calculated the impact of the network topology and the proportion of vaccinated people on the spread of the COVID-19, analyzed the critical value of herd immunity. The established propagation model is reasonable, and feasible to achieve herd immunization by vaccination.

The Covid-19 crisis impacts the economy with non-equilibrium and non-linear shocks. This paper builds a trading network model based on the theory of trading economics. Using the network model, the evolutionary procedure of the economic depression triggered by the shocks are researched. The study shows that under the impact of shocks, small and medium-sized trading agents with weak profitability will first experience cash flow crisis. Then the crisis contagion is formed in upstream and downstream through the trading network. The credit reduction caused by the business deterioration will make the interest rate in the economy increase and promote each other with the bankruptcy of trading entities. Eventually, it leads to the feedback loop in liquidity crisis and debt crisis, which accelerates the bankruptcy of enterprises and possibly causing a debt crisis in the banking sector. It is found that after the shock, the economic recovery may take three patterns: stable recovery, slow recession and secondary crisis. Finally, the paper proposes relevant policy recommendations to reduce the impact of the crisis.

In order to explore the effect of network structure and shadow banking on systematic risks, this paper introduces shadow banking and constructs a dynamic interbank network system model considering different interbank network structures based on the complex network and evolving balance sheet model. The results show that shadow banks are the main carriers of risk contagion, and the banking system with shadow banking has high systematic risk and the systemic risk is closely related to the interbank network structure; relatively concentrated scale-free and small-world networks are more likely to spread risks. Scattered random networks can mitigate risk contagion, but too strong external shocks will make the mitigation ineffective.

In order to solve the problem that the complex structure of air-rail combined transportation system cannot be described effectively based on the single-layer network, considering the heterogeneity of nodes, connecting edges and side weights, an air-rail double-layer weighted network model is proposed based on multilayer network. The structure characteristics of the air-rail network of China Eastern Airlines are empirically analyzed from four aspects: scale-free characteristic, small-world characteristic, centrality and interlayer correlation. The results show that both the air-rail double-layer network and its subnets have scale-free characteristics and small-world characteristics. The centrality of China Eastern Airport network layer is prominent, and the centrality distribution of air-rail double-layer network is not balanced. There is a weak correlation between airport layer and high-speed rail layer, and the tightness of the relationship between them needs to be strengthened. The overall structure and function of East-China Airlines’ air-rail network are good. It is conducive to improve the matching degree between airports and high-speed rail stations for improving the efficiency of air-rail.

In order to enhance the resilience of urban transit network system after being attacked by external factors, a resilience repair scheme for urban transit network system is developed. Firstly, urban transit network system resilience is defined and urban transit network system resilience model is constructed. The change of network system resilience after suffering from external attacks is divided into two phases: absorption and repair. In the absorption phase, the load distribution of the failed nodes is considered; in the repair phase, two types of network resilience repair schemes are developed according to the different intervention phases, namely, repairing while absorbing and repairing after absorbing. The urban transit network in Huangdao district of Qingdao is selected for simulation analysis to verify the feasibility of the rehabilitation strategy.

To improve the robustness of urban public transport system, an edge adding strategy based on transfer is formulated. Take the bus-subway composite network in Jinan as an example, the characteristic parameters and robustness of the network are studied, and an edge adding strategy based on transfer is proposed to improve the network robustness. The research shows that the composite network has the characteristics of small world and scale-free network; The network is more vulnerable than random attack under intentional attack; The network robustness is improved significantly by the high-degree edge addition strategy under betweenness attacks, which increases the proportion of attacked stations by 50.46% when the network is paralyzed; The network robustness is improved significantly by the high-betweenness edge addition strategy under random attacks and degree attacks, which increases the proportion of attacked stations by 23.35% and 39.81% respectively.

Aiming at the problems of inaccurate keywords extraction and only considering single correlation in subject words extraction, a subject words extraction algorithm combining integration idea with complex network is proposed. Firstly, the keywords of topic data are extracted through the integration algorithm to improve the accuracy of keywords extraction. Secondly, the traditional word co-occurrence formula is improved to calculate the co-occurrence degree of keywords, and a keywords co-occurrence network is established. Based on the network, the optimal connected subgraph is obtained. At the same time, the importance of keywords is measured by taking the centrality of node degree as the weight, and the subject words are mapped. Finally, the micro-blog topic data set is used to verify the example, which proves that the algorithm is effective and better than the traditional word co-occurrence algorithm, and it is applied in the Qingdao community topic data set.

Exploring complementary technology convergence and similar technology convergence is conducive to enhancing enterprise innovation capability. This paper analyzes the impact of partner diversity on technology convergence by building a multi-layer network model of organizational cooperation and technology convergence. The research shows that the geographic diversity of partners is not conducive to the occurrence of complementary technology convergence and similar technology convergence. The technological diversity of partners is conducive to complementary technology convergence but not conducive to similar technology convergence. The relationship strength between enterprises and different types of partners has different effects on complementary technology convergence and similar technology convergence. The research results can help enterprises choose appropriate partners to achieve different innovation strategies.

Aiming at the problem that the influence mechanism of user group structure on the stability of complex product group intelligent collaborative design network is not clear, a new stability analysis method of complex product group intelligent collaborative design network is proposed. Based on niche theory, this paper analyzes the ecological role in the intelligent collaborative design network of complex product groups, defines the individual niche representation model, and makes an empirical study by removing network nodes. It is found that generalists with large niche width, ordinary designers and generalists with small niche width are the key roles affecting the stability of the network. The research results provides a reference for the precise regulation of complex product group intelligent collaborative design network.

Standardizing the waste disposal behavior of manufacturing enterprises and environmental protection enterprises and forming a symbiotic governance mechanism are the basis for the ecological transformation of the industrial park. Based on the concept of mutual benefit and win-win, the network evolutionary game is used to simulate the influence of the decision-making behavior of enterprises under different scales and structures on the establishment of symbiosis process. The results show that there are differences in the sensitivity of manufacturing enterprises and environmental protection enterprises to government subsidies, and a reasonable subsidy policy can stimulate the enthusiasm of both parties at the same time. On the one hand, the government's guidance and supervision in the early stage can cultivate the sense of responsibility of the two types of enterprises. On the other hand, it can effectively prevent the occurrence of speculative behavior, which plays a key role in speeding up the construction process of symbiotic relationship.

SeqSLAM is a widely used loop closure detection algorithm in mobile robot and autonomous vehicle field. It could recognize revisited places by comparing sequences of images even under dramatic changes of season, illumination, and weather. However, SeqSLAM is vulnerable to viewpoint changes. In addition, SeqSLAM compares sequences of images by brute force method, which prevents its real-time application to large-scale image datasets. To address these problems, we first represent each image by a kind of low dimensional description — vector of locally aggregated descriptors (VLAD) which is robust to viewpoint changes, and then replace the brute force method by an approximate nearest neighbor search algorithm — hierarchical navigable small world graphs (HNSW). Tests on publicly available datasets show that, the improved SeqSLAM with VLAD and HNSW could obtain much better detection results in the respect of precision-recall evaluation and the search time is reduced by orders of magnitude. We make code publicly available at https://github.com/qipengliuNTU/Efficient-SeqSLAM-with-HNSW.