Mathematical Modeling: A Key Course for Promoting Sustainable Development

In the mathematics department's "Mathematical Modeling" course, students will learn how to utilize mathematical tools to establish and analyze problems in the real world, with a particular focus on the application of deep learning models. The course covers models such as neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs), integrating statistical analysis, optimization methods, and computational techniques to help students understand the value of deep learning in scientific research, industrial applications, and social development. This course not only emphasizes theoretical foundations but also encourages students to apply mathematical modeling to solve practical problems, thus generating a profound connection to the United Nations Sustainable Development Goals (SDGs), specifically SDG 4, SDG 9, SDG 12, and SDG 15.

How the Mathematical Modeling Course Promotes the SDGs

SDG 4: "Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all"

• The course develops intelligent education systems via deep learning models, such as personalized learning recommendations, intelligent assessments, and learning behavior analysis, helping teachers enhance teaching quality and reduce inequities in educational resource distribution.
• Students can use deep learning to develop adaptive learning platforms that provide tailored digital materials, promoting lifelong learning.

SDG 9: "Build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation"

• Through mathematical modeling, students can analyze and optimize smart transportation, energy distribution, and automated manufacturing, improving the operational efficiency of infrastructure.
• The application of AI and deep learning in smart industries (such as Industry 4.0 and automated production) can enhance production efficiency while reducing costs, thereby promoting industrial innovation.

SDG 12: "Ensure sustainable consumption and production patterns"

• The course guides students to apply mathematical modeling to optimize supply chain management and reduce resource waste, using AI to predict market demand, thus lowering overproduction and environmental burdens.
• Deep learning techniques can be utilized in waste sorting, food waste management, and carbon footprint analysis, helping businesses and consumers make more environmentally friendly choices.

SDG 15: "Protect, restore, and promote sustainable use of terrestrial ecosystems"

• Students can use deep learning to analyze satellite images and ecological data for monitoring deforestation, protecting biodiversity, and predicting land degradation, providing data support for environmental protection.
• AI can help monitor changes in wildlife populations and curb illegal hunting, promoting the sustainable development of ecosystems.

Conclusion

The mathematical modeling course is more than just an application practice of mathematical theory; it is a course that combines AI technology and sustainable development. By learning deep learning models, students can apply mathematical tools in areas such as educational innovation, industrial development, environmental protection, and sustainable production, contributing the power of mathematics and AI to solving global challenges.