Construction of Computer Mathematical Model Based on Improved Algorithm

Computer mathematical models play an important role in scientific research and practical applications. However, the traditional mathematical model construction process may be limited by algorithms, resulting in insufficient accuracy and reliability of the model. Therefore, this article proposes a computer mathematical model construction method based on improved algorithms, aiming to improve the performance and application effectiveness of the model. This article first introduces the traditional process of building mathematical models and points out potential problems, such as overfitting of data features and difficulties in solving complex problems. Next, we proposed a mathematical model construction method based on improved algorithms to overcome the limitations of traditional methods. The mathematical model construction method based on improved algorithms focuses on the following aspects: firstly, we adopt more accurate and efficient data collection and preprocessing methods to ensure the quality and accuracy of input data. Secondly, we introduce advanced algorithms and technologies, such as genetic algorithm, Ant colony optimization algorithms, neural network, etc., to improve the optimization and solution process. These algorithms can better handle complex problems and provide more accurate model parameters and results. Through experimental simulation, we can know that the accuracy of the improved algorithm in this paper reaches 96%. Compared to other algorithms, the accuracy of our algorithm has improved by 2 percentage points.