矿山涌水量预测方法对比分析

Comparative analysis of mine water inflow prediction methods

矿山涌水问题长期困扰着矿业安全与环保工作。为了有效应对,本文对比分析了数学模型、统计模型和智能预测模型在矿山涌水量预测中的应用。数学模型,如有限元法、有限差分法及连续介质机械原理等,理论基础明确,预测结果准确。然而,这些方法计算过程繁杂,对参数需求较高,实际应用中可能面临挑战。统计模型,如多元线性回归、指数平滑法及时间序列分析等,虽然预测过程相对简洁,但对样本数量和质量要求较高。在样本不足或质量不高的情况下,预测结果可能受到影响。通过分析模型的原理、优缺点对比应用效果,本文为工程实践中选择最适合涌水预测模型提供理论依据和实际参考。

The issue of mine inflow has long plagued mining safety and environmental protection efforts.To effectively address this issue,this article compares and analyzes the application of mathematical models,statistical models,and intelligent prediction models in mine inflow prediction.Mathematical models,such as finite element methods,finite difference methods,and continuous medium mechanics principles,have a clear theoretical foundation and accurate prediction results.However,these methods can be computationally intensive and have high demands for parameters,posing challenges in practical applications.Statistical models,such as multiple linear regression,exponential smoothing,and time series analysis,have relatively simple prediction processes but require a significant amount and quality of samples.When sample sizes are insufficient or quality is low,prediction accuracy may be compromised.By analyzing the principles of these models,comparing their advantages and disadvantages,and evaluating their application effects,this article provides theoretical support and practical guidance for selecting the most suitable inflow prediction model in engineering practice.