AI让土木工程应对复杂多变现实，提升预测与决策能力
Application of Artificial Intelligence (AI) in Civil Engineering
- 用神经网络、模糊逻辑等软计算方法处理非线性问题
- 在边坡稳定、材料性能等领域显著提高分析精度
- 适合土木工程研究人员和智能建造从业者参考
传统硬计算依赖精确数据，但在土木工程中，现实系统持续变化，难以满足。为此需引入软计算与人工智能技术。人工神经网络（ANNs）、模糊逻辑、遗传算法（GAs）及概率推理等先进计算模型，已显著推动土木工程多个子领域的发展。这些方法在边坡稳定性分析、地基承载力评估、水质监测与处理、交通系统优化、空气质量预测、结构材料性能研究等方面提供了创新解决方案，并提升了分析能力。其中，ANNs能有效捕捉非线性关系，提供高精度预测；模糊逻辑通过高效决策流程实现更精准的系统评估；遗传算法基于进化机制优化模型参数以获得更优结果；概率推理则有效降低统计不确定性。
原文摘要 · Abstract (English)
Hard computing generally deals with precise data, which provides ideal solutions to problems. However, in the civil engineering field, amongst other disciplines, that is not always the case as real-world systems are continuously changing. Here lies the need to explore soft computing methods and artificial intelligence to solve civil engineering shortcomings. The integration of advanced computational models, including Artificial Neural Networks (ANNs), Fuzzy Logic, Genetic Algorithms (GAs), and Probabilistic Reasoning, has revolutionized the domain of civil engineering. These models have significantly advanced diverse sub-fields by offering innovative solutions and improved analysis capabilities. Sub-fields such as: slope stability analysis, bearing capacity, water quality and treatment, transportation systems, air quality, structural materials, etc. ANNs predict non-linearities and provide accurate estimates. Fuzzy logic uses an efficient decision-making process to provide a more precise assessment of systems. Lastly, while GAs optimizes models (based on evolutionary processes) for better outcomes, probabilistic reasoning lowers their statistical uncertainties.
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