The Agriculture Trading Platform (ATP) represents a significant innovation in the realm of agricultural trade in Malaysia. This web-based platform is designed to address the prevalent inefficiencies and lack of transparency in the current agricultural trading environment. By centralizing real-time data on agricultural production, consumption, and pricing, ATP provides a comprehensive dashboard that facilitates data-driven decision-making for all stakeholders in the agricultural supply chain. The platform employs advanced deep learning algorithms, including Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to forecast market trends and consumption patterns. These predictive capabilities enable producers to optimize their market strategies, negotiate better prices, and access broader markets, thereby enhancing the overall efficiency and transparency of agricultural trading in Malaysia. The ATP’s user-friendly interface and robust analytical tools have the potential to revolutionize the agricultural sector by empowering farmers, reducing reliance on intermediaries, and fostering a more equitable trading environment.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.

Under the background of the continuous development of science and technology, the era of big data has come in an all-round way, and big data technology has also been widely used in the education industry. The course of financial management in applied colleges and universities is a highly applied course, which focuses on the substance of the course. Teachers need to create a good learning environment for students with the help of information technology, and constantly cultivate students' professional skills and professionalism. In order to improve the quality of financial management courses in colleges and universities, this paper mainly analyzes the management courses in application-oriented colleges and universities, expounds the factors affecting the practical teaching quality of management courses in colleges and universities, and analyzes the teaching methods of management courses in application-oriented colleges and universities. Finally, it is concluded that only when teachers constantly improve their teaching level, can students' learning level be improved by combining theory with practice.

This paper aims to explore how to build a sustainable peace and development model for China’s peacekeeping efforts through the application of data-driven methods from UN Global Pulse. UN Global Pulse is a United Nations agency dedicated to using big data and artificial intelligence technologies to address global challenges. In this paper, we will introduce the working principles of UN Global Pulse and its application in the fields of peacekeeping and development. Then, we will discuss the current situation of China’s participation in peacekeeping operations and how data-driven methods can help China play a greater role in peacekeeping tasks. Finally, we will propose a sustainable peace and development model that combines data-driven methods with the advantages of China’s peacekeeping efforts to achieve long-term peace and development goals.

In the context of big data, the teaching of financial accounting for vocational undergraduate students needs to be continuously optimized and innovated. This article provides a brief analysis of the current situation of financial accounting teaching for vocational undergraduate students. It also analyzes the phenomena of outdated teaching concepts, outdated teaching content, and unreasonable teaching objectives in the current teaching of financial accounting for vocational undergraduate students. It proposes the idea of innovating teaching concepts in current teaching work, clarifying teaching objectives, integrating flipped classroom reform teaching mode, and introducing project-based teaching method to improve teaching efficiency, so as to achieve more efficient teaching guidance for students.