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Objective To explore the application of fuzzy mathematics calculation in quantitative evaluation of students’ basketball jump shot performance. Methods Using the basic theory of fuzzy mathematics and the calculation method of fuzzy correlation, the correlation degree between the training means and the free throw hit rate was obtained, and further, the best training means to improve the free throw hit rate of basketball players were selected. As a result, when the ball reaches the highest point or falls after reaching the highest point, it is pushed out towards the 45° Angle, making the basketball fly to the basket in an arc. The jump shot is designed to avoid being blocked by a defender and is very effective against players of similar size or when no one is guarding. Conclusion The method proposed in this paper is suitable for the evaluation of college basketball teaching and ball skill training, and provides theoretical basis and quantitative data for training.

Condensing the multi-dimensional digital model of green urban design, and constructing a digital method system of it progressively layer by layer. Based on this research background, the dissertation designs the spatial form of landscape architecture based on the data visualisation of nonlinear technology. The article uses the colour zoning method to design the actual scene of the garden landscape with nonlinear parameteriszation. The simulation result analyses that the proposed nonlinear algorithm has realised the efficiency improvement purpose of landscape architecture design.

The article analyzes why colleges and universities should strengthen innovation and entrepreneurship education based on “mass entrepreneurship and innovation”’ First, we conduct a questionnaire survey on the status of college students’ innovation and entrepreneurship attitude and use nonlinear methods to construct an evaluation model of innovation and entrepreneurship capabilities to evaluate students’ innovation and entrepreneurship capabilities quantitatively. Finally, we verify the effectiveness of the combined evaluation model through data on the innovation and entrepreneurship activities of college students. The research results can provide a new idea for appraisal of college students’ innovation and entrepreneurship ability.

The behaviours of the pig are often closely related to their health. Pig recognition is very important for pig behaviour analysis and digital breeding. Currently, the early signs and abnormal behaviours of sick pigs in breeding farms are mainly completed by human observation. However, visual inspection is labour intensive and time-consuming, and it suffers from the problems of individual experiences and varying environments. An improved ResNet model was proposed and applied to detect individual pigs in this study based on deep learning knowledge. The developed model captured the features of pigs applying across layer connections, and the ability of feature expression was improved by adding a new residual module. The number of layers was reduced to minimise the net complexity. Generally, the ResNet frame was developed by reducing the number of convolution layers, constructing different types of the residual module and adding the number of convolution kernels. The training accuracy and testing accuracy reached 98.2% and 96.4%, respectively, when using the improved model. The experiment results showed that the method proposed in this paper for checking living situations and disease prevention of commercial pigs in pig farms is potential.