For the parameter estimation problem in research related to the fractional-order chaotic systems (FOCSs), a modified optimization algorithm based on Salp Swarm Algorithm (SSA) was developed in this paper. The proposed algorithm introduced several improvements on SSA: adding a grouping step, introducing “betrayal” behavior, and improving the update method of the followers. We applied multiple classical optimization algorithms to conduct the parameter estimation experiments on the fractional-order Lorenz chaotic system (Lorenz-FOCS) and the fractional-order Financial chaotic system (Financial-FOCS). In addition, we explored the impact of searching space on parameters estimation through experiments. The experimental results confirmed the feasibility of the modified Salp Swarm Algorithm (MSSA). The MSSA performed better than the SSA and other classical optimization algorithms in terms of the estimation accuracy and convergence rate.

The traditional public opinion dissemination model studies the dissemination of single opinion public opinion, while manual processing limits the division of multiple opinions, reducing the efficiency of public opinion dissemination. Therefore, combined with the topic recognition model, the SnCIR multi-opinion public opinion competition propagation model is constructed. The comparative experiment on the ca-GrQc dataset shows that the SnCIR model has a lower propagation density than the SCIR, SEIR and SIR models before the public opinion spreads stably. At the inflection point, SnCIR is 0.02 smaller than the SCIR model propagation density, 0.04 smaller than SEIR, and 0.65 smaller than SIR. Through the guidance of mainstream and official media, the management of the Weibo platform, and the government’s supervision, this paper studies the impact on the dissemination of network public opinion. Combined with the analysis of the evolution characteristics of the network public opinion situation, some countermeasures and suggestions are given, which provide management ideas for the response and governance of network public opinion in emergencies.

To improve the traffic capacity of scale-free networks, we propose an improved local efficient routing (ILER) strategy based on node degree and network constraint index (NCI). NCI describes how closely a node is maintained directly or indirectly with other nodes, and it only considers the relationship between nodes and their neighbors, not the topology of the network. Both the node degree and NCI are a parameter to describe the importance of nodes, and the combination of the two can make up for their own shortcomings, making it particularly important. Under the ILER strategy, packets can bypass some central nodes in the network for transmission, so that the central nodes in the network are not prone to congestion, thereby increasing the network traffic capacity. Through simulation comparison, the network traffic capacity under ILER strategy is significantly higher than that under probability routing (PR) strategy and efficient routing (ER) strategy. Under the ILER strategy, the average path length (APL) of the network is also shorter than that under the PR and ER strategies. In addition, whether target attack or random attack, the network has strong robustness under ILER strategy.

Most of the conventional cellular automaton (CA) traffic flow models have two shortcomings: unlimited deceleration capabilities and incapability of reproducing the synchronized flow in the three-phase traffic flow theory. Based on an original deceleration CA model that emphasizes limited mechanical capabilities and human overreaction as the origin of congested traffic states, this paper proposes a new deceleration CA model where the slow-to-start rules are incorporated. For periodic boundary conditions, one also finds that the present model can reproduce well the three different phases of traffic flow (free flow, synchronized traffic flow, wide moving jam) as well as two first-order phase transitions (the transitions from free flow to synchronized flow and from synchronized flow to wide moving jam) among them. Compared to the original deceleration CA model, one notes that the phase transition from the synchronized flow to wide moving jam becomes distinguishable. Furthermore, the present model can reliably reproduce most empirical findings including synchronized flow with different slopes, the so-called pinch effect, and the time-headway distribution of free flow and so on. Importantly, the synchronized flow with different slopes is supported by spatiotemporal diagrams and the statistical distribution of velocity and so on. For open boundary conditions, the present model can reproduce the spatiotemporal diagrams of well-known five patterns including moving synchronized flow pattern, localized synchronized flow pattern, widening synchronized flow pattern, dissolving general pattern and general pattern.