# Achievement Prediction and Performance Assessment System for Nations in the Asian Games
## 2 Materials and Methods
### Back-Propagation DEA Algorithm
Moreover, creating a system performance assessment for diagnosis, planning, monitoring, and revising the impact of implementing measures in the Asian nations constitutes a step forward. These approaches have rarely been applied to the different stages of the planning process or types of collective systems for comparative analysis [42]. ## 4 Discussion

Contemporary predictive analytics leverages machine learning, deep learning, and artificial neural network technologies to enhance predictions. These enhanced predictive analytics can rapidly analyze large volumes of data and reveal insights that humans may overlook, and such insights may increase the likelihood of predicting future events with greater precision and accuracy. Integrating data envelopment analysis (DEA) and artificial neural networks (ANN) serves three primary purposes. (1) The optimization process established by the DEA can identify the analytical performance of each Asian nation concerning every relevant variable under consideration. (2) The corresponding slack values are used to design indicators that highlight the relative performance of each Asian nation while simultaneously considering multiple outputs. Standard ANN models are often constrained by having a single output variable distributed across different categories, although slightly more complex combination environments can be defined. (3) The obtained variables can be retroactively applied to and utilized in ANN prediction results. Research trends and applications encompass the topics of efficiency and productivity (DEA), artificial neural networks (AI and deep learning), the integration of DEA and an ANN, and simultaneous longitudinal research (time series) and form a comprehensive landscape of the contemporary field. We explore the development focus of big data, including big data in sports, and discuss research and applications in the context of Asian nations participating in the Asian Games. In today's context, big data serves as a tool for data processing and shapes a research trend and direction. This evolution enables data analysis to transition from merely understanding history to predicting the future, creating a new context and management paradigm. AI is more than a trend, and prediction is not its only purpose; in the comparative analysis of the Asian Games, the objective of Asian nations is to grasp advantages for strategic positioning proactively. China, India, Chinese Taipei, the Philippines, and Singapore exceeded the predicted performance, leading to an upward trend in Asian game participation efficiency. China, as the host nation, excelled in creating outstanding achievements; India achieved a historic milestone with a total of 107 medals; Chinese Taipei matched its best-ever performance in terms of gold medals; the Philippines maintained its best performance since the 1990 Asian Games with four gold medals; and Singapore exceeded expectations in both gold and silver medal counts. On the other hand, the actual medal counts for the remaining nine nations were lower than the predicted values, which could be attributed to the allocation of resources at different levels of mega-sports events, including the Olympic Games. Additionally, sports achievements did not reach the desired level, possibly influenced by a lack of economic and political resources to drive national sports development. Consequently, the development of national sports still requires improvement. A higher GDP signifies more substantial national economic power, indicating that wealthier nations can provide better public sports facilities, and in such nations, sports professionals are more likely to receive social support [2;3]. [PERSON] and [PERSON] [50] investigated the uniqueness of Asian nations in the Olympic Games and reached four main conclusions.