Discrete Dynamics in Nature and Society

Aiming at the production-distribution problem of perishable food, considering the interference caused by the change of the customer’s time window in actual distribution process, using the ideas of disruption management, analyzing the disturbance of the interference event to the production-distribution system, and constructing the perishable food production-distribution problem disturbance identification and disturbance measurement, and with the minimum deviation between the new scheme and the original scheme as the goal, a mathematical model of disturbance recovery is established. An improved ant colony algorithm-mixed ant colony algorithm based on the change of customer time window for perishable food production-distribution problem was designed to solve the problem. Finally, the simulation experiments are carried out by examples, and compared with the rescheduling results, the effectiveness of the disruption management model and the algorithm-mixed ant colony algorithm are also verified. The research results show that the disruption management can effectively reduce the degree of program deviation and control the cost reasonably.

The entity recognition of Chinese electronic medical record is of great significance to medical decision-making. The main process of entity recognition is sequence tagging, which has problems such as nested entity and boundary prediction. In this paper, we proposed a NER method called Bert-MRC-Biaffine, which formulates the NER as an MRC task. The approach of the machine reading comprehension framework is to introduce prior knowledge, the query about entities. The biaffine mechanism scores pair start and end tokens in a sentence so that the model is able to predict named entities accurately. The proposed method outperforms from the electronic medical record dataset, called CCKS2017 data, and the TCM dataset. We also remove components to evaluate the contribution of individual components of our model. Experiments on two datasets demonstrate the effectiveness of our model.

Banks, financial, and credit institutions encountering the weakening financial system and increased risk factors cause high inflation and great losses for an economy. Detecting financial risks in advance could help financial institutions avoid losses, and the financial system could be eventually affected less. Early warning systems for banks could be helpful to identify financial risks and take measures to deal with hazardous situations. Various approaches have already been put forward. However, inaccuracy issues in risk detection are one of the main issues. Combining semantic hierarchy with the GMDH neural network to predict financial risks is proposed. A semantic hierarchy approach based on converting risk-related values and picking influential variables could be practical in risk detection. Besides, the GMDH algorithm utilizing neural networks based on available data has the capability of predicting possible risks that could occur in the future. The outcomes of the proposed method when compared to non-data mining methods suggest that it improves accuracy by almost 20%.

This paper aimed to explore the difference in the spatial distribution of compulsory education resource allocation. Raw data were collected from the 2020 China Statistical Yearbook (county/district level) and Guangxi Province Statistical Yearbook of China. Data analysis was conducted using the entropy method, comprehensive evaluation method, K-means clusters analysis, analysis of variance, and spatial statistical analysis (Moran’s I index). It was determined that there were significant differences in the spatial distribution of compulsory education. The equilibrium degree to mandatory education resource allocation was divided into three classes: high level, medium level, and low level, and each class presented a spatial aggregation effect in the spatial distribution. Compared with the primary schools, the equilibrium degree of junior secondary school was higher. However, the equilibrium fluctuation of junior secondary schools was more significant among different counties/districts. The equilibrium of educational resources of junior secondary schools in the urban areas was higher than that in the rural areas, but there was no significant difference for the primary school.

In this paper, the bifurcation, phase portraits, traveling wave solutions, and stability analysis of the fractional generalized Hirota–Satsuma coupled KdV equations are investigated by utilizing the bifurcation theory. Firstly, the fractional generalized Hirota–Satsuma coupled KdV equations are transformed into two-dimensional Hamiltonian system by traveling wave transformation and the bifurcation theory. Then, the traveling wave solutions of the fractional generalized Hirota–Satsuma coupled KdV equations corresponding to phase orbits are easily obtained by applying the method of planar dynamical systems; these solutions include not only the bell solitary wave solutions, kink solitary wave solutions, anti-kink solitary wave solutions, and periodic wave solutions but also Jacobian elliptic function solutions. Finally, the stability criteria of the generalized Hirota–Satsuma coupled KdV equations are given.

We investigate the complete th moment convergence for weighted sums of independent, identically distributed random variables under sublinear expectations space. Using moment inequality and truncation methods, we prove the equivalent conditions of complete th moment convergence of weighted sums of independent, identically distributed random variables under sublinear expectations space, which complement the corresponding results obtained in Guo and Shan (2020).