Encouraging the adoption and diffusion of low-carbon agricultural technology innovation is an important measure to cope with climate change, reduce environmental pollution, and achieve sustainable agricultural development. Based on evolutionary game theory, this paper establishes a game model among agricultural enterprises, government, and farmers and analyzes the dynamic evolutionary process and evolutionary stable strategies of the major stakeholders. The impact of innovation subsidies, carbon taxes, and adoption subsidies on low-carbon agricultural innovation diffusion is simulated using Matlab software. The results show that the government’s reasonable subsidies and carbon taxes for agricultural enterprises and farmers can increase the enthusiasm of agricultural enterprises and farmers to participate in low-carbon agriculture. This study can be used as a basis for the government to formulate more targeted policies to promote the diffusion of low-carbon agricultural innovation.

This paper aims at identifying the key factors to maintain the quality and safety of agricultural products in the agricultural product quality and safety information system (APQSIS). Based on the theoretical framework of information entropy and complexity, this paper uses the dynamic evolutionary game model and the multiagent modeling and simulation to discuss the APQSIS agents’ equilibrium strategies and the effects of their interactive behaviors on the APQSIS evolutionary stability with asymmetric information. The results show that the governmental supervision and intermediary organizations are significant to assuring agricultural product quality and safety (APQS) as well as the effective transmission of APQS information in stable environments with low complexity.

With the levels of confidence and system complexity, interval forecasts and entropy analysis can deliver more information than point forecasts. In this paper, we take receivers’ demands as our starting point, use the trade-off model between accuracy and informativeness as the criterion to construct the optimal confidence interval, derive the theoretical formula of the optimal confidence interval and propose a practical and efficient algorithm based on entropy theory and complexity theory. In order to improve the estimation precision of the error distribution, the point prediction errors are STRATIFIED according to prices and the complexity of the system; the corresponding prediction error samples are obtained by the prices stratification; and the error distributions are estimated by the kernel function method and the stability of the system. In a stable and orderly environment for price forecasting, we obtain point prediction error samples by the weighted local region and RBF (Radial basis function) neural network methods, forecast the intervals of the soybean meal and non-GMO (Genetically Modified Organism) soybean continuous futures closing prices and implement unconditional coverage, independence and conditional coverage tests for the simulation results. The empirical results are compared from various interval evaluation indicators, different levels of noise, several target confidence levels and different point prediction methods. The analysis shows that the optimal interval construction method is better than the equal probability method and the shortest interval method and has good anti-noise ability with the reduction of system entropy; the hierarchical estimation error method can obtain higher accuracy and better interval estimation than the non-hierarchical method in a stable system.

In capable person governing agricultural cooperatives, the internal governance is essential for cooperatives to achieve sustainable development. As an important mechanism of cooperative internal governance, relational governance is the focus of the current research in the field of cooperative internal governance. Based on the theory of organizational justice, relational embeddedness theory, and relational governance theory, this paper constructs the relationship between interactive justice, relational embeddedness, and governance performance based on fuzzy cognitive map and discusses the influence mechanism of interactive justice on relational governance performance. Taking 245 members of 18 agricultural cooperatives as samples, this paper makes an empirical test by using the machine learning method. Through the analysis of the data, we find that interactive justice has a significant positive impact on the governance performance. Relational embeddedness also has a significant positive impact on the governance performance. And relational embeddedness plays an intermediary role in the positive impact of interactive justice on governance performance. To some extent, the research results broaden the relationship between interactive justice and relational governance performance and provide useful reference for cooperatives to strengthen internal governance and achieve sustainable growth.

China’s soybean price fluctuates due to the current economic and trade frictions between China and the United States. Brazil and the United States are regarded as two oligarchs in China’s soybean import market. A dynamic price game model is established, and price elasticity parameters are estimated by using statistical data and Rotterdam model. The stability of Nash equilibrium point is discussed through bifurcation diagram, maximum Lyapunov exponent, evolutionary trajectory, and time series diagram. The influence of price adjustment speed on equilibrium price is analyzed. The numerical simulation of price adjustment speed is carried out, which is compared with the actual situation of imported soybean price before and after the trade friction. The results show that the model constructed in this paper can reflect the changing trend of price and demand and predict the short‐term import soybean prices of Brazil and the United States. The forecast accuracy of price fluctuation is high. The results provide model and theoretical reference for price game under trade disputes and provide methodological reference for forecasting the price of imported goods.

In this paper, based on chaos theory and dynamic system simulation, a dynamic model of a relational leadership system with pressure factors is established and simulated. The study found that the excessive self-leadership and the relational leadership cannot effectively improve the leadership effectiveness of leaders. In addition, with the adjustment of the self-leadership adjustment coefficient, leadership effectiveness will change from a stable state to a chaotic state. Only by adopting limited rational decision-making strategies in multicycle decision-making can leaders maintain a high level of leadership effectiveness. Previous research mainly focuses on the theoretical analysis of the complexity of the leadership system or the issuance of questionnaires, but seldom on the dynamic complex process of the leadership system. This study reveals the complexity and chaos characteristics of the dynamic evolution of the multifactor relational leadership system, puts forward the relational leadership theory and the complex leadership theory under the influence of pressure, and makes some suggestions on how to improve the leadership effectiveness under the complex environment. The research results are of great significance to theoretical innovation and practical application.