Asset deterioration analysis using multi-utility data and multi-objective data mining
Asset deterioration analysis using multi-utility data and multi-objective data mining
复制标题
使用多用途数据和多目标数据挖掘进行资产恶化分析
DOI：
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发表时间：
2009
期刊：
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通讯作者：
D. Laucelli
中科院分区：
文献类型：
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作者：
D. Savić;O. Giustolisi;D. Laucelli
基于物理的模型源于第一原理（例如物理定律），并依赖于已知的变量和参数。因为它们具有物理意义，它们也解释了系统的潜在关系，并且通常可以作为结构实体从一个系统转移到另一个系统。它们只需要更新模型参数。数据驱动或回归技术涉及建模的数据挖掘，其主要缺点之一是描述变量和数值参数之间关系的函数形式不能像经典的基于物理的对应物那样传输到其他物理系统。为了达到平衡，进化多项式回归（EPR）提供了一种方法来建模资产退化的多效用数据，以使模型结构可跨物理系统移植。EPR是一种最近开发的混合回归方法，为模型提供符号表达式，并使用基于伪多项式表达式的公式，通常在多目标情况下，从单个案例研究中的数据中选择最佳帕累托最优模型（简约性与准确性）。本文讨论了EPR在处理多效用数据（多案例研究）方面的改进，其中尝试实现跨不同水系统的资产劣化预测的通用模型结构。
Physically-based models derive from first principles (e.g. physical laws) and rely on known variables and parameters. Because these have physical meaning, they also explain the underlying relationships of the system and are usually transportable from one system to another as a structural entity. They only require model parameters to be updated. Data-driven or regressive techniques involve data mining for modelling and one of the major drawbacks of this is that the functional form describing relationships between variables and the numerical parameters is not transportable to other physical systems as is the case with their classical physically-based counterparts. Aimed at striking a balance, Evolutionary Polynomial Regression (EPR) offers a way to model multi-utility data of asset deterioration in order to render model structures transportable across physical systems. EPR is a recently developed hybrid regression method providing symbolic expressions for models and works with formulae based on pseudo-polynomial expressions, usually in a multi-objective scenario where the best Pareto optimal models (parsimony versus accuracy) are selected from data in a single case study. This article discusses the improvement of EPR in dealing with multi-utility data (multi-case study) where it has been tried to achieve a general model structure for asset deterioration prediction across different water systems.