Modelling macronutrients in shelf sea sediments: fitting model output to experimental data using a genetic algorithm
Modelling macronutrients in shelf sea sediments: fitting model output to experimental data using a genetic algorithm
复制标题
陆架海沉积物中大量营养素的建模：使用遗传算法将模型输出与实验数据拟合
DOI：
10.1007/s11368-013-0793-0
复制
发表时间：
2013
影响因子：
3.6
通讯作者：
Wood C
中科院分区：
文献类型：
--
作者：
Wood C
目的成岩建模，数学模拟的分解沉积有机质和随后的命运相关的营养物质，已经发展到一个点，复杂的，非稳态环境可以准确地模拟。遗传算法从未与早期成岩模型结合使用，因此我们的目标是发现这种方法是否可行，以确定一组现实的模型参数，材料和方法在微遗传算法（μGA）之前，进行了一系列的敏感性分析，以确定模型最敏感的参数被用来拟合输出从以前发表的成岩模型（OMEXDIA）的观测数据，采取在北Dogger网站从北海的一系列巡航。被认为是碳，氧，硝酸盐和氨的配置文件。该方法允许以类似于自然选择的方式确定一组参数。在每个实验中的遗传算法的每次迭代减少所观察到的配置文件和OMEXDIA.Results和discussionDespite的一些所观察到的配置文件，特别是碳，显示不寻常的模式之间的方差，遗传算法是能够生成一组参数，这是能够适合的意见。因此，遗传算法可以帮助确定模型中使用的其他参数的值，这些参数的观测值难以测量（例如，有机物从上覆水柱流入沉积物的流量和有机物的降解率）。我们还表明，由μGA技术确定的参数的值能够被用于在一个潜在的时间predictive martens.ConclusionsThe μGA使用是一个可行的方法，以适应碳和营养沉积剖面观察到的复杂的，动态的陆架海系统，尽管OMEXDIA最初被设计为不同的沉积环境。因此，结果表明，这种新的使用的遗传算法是一种合适的方法，模型校准和验证，该技术可能有助于解释的过程是知之甚少。
PurposeDiagenetic modelling, the mathematical simulation of the breakdown of sedimentary organic matter and subsequent fate of associated nutrients, has progressed to a point where complex, non-steady state environments can be accurately modelled. A genetic algorithm has never been used in conjunction with an early diagenetic model, and so we aim to discover whether this method is viable to determining a set of realistic model parameters, which itself is often a difficult task.Materials and methodsA range of sensitivity analyses were conducted to establish the parameters for which the model was most sensitive before a micro-genetic algorithm (μGA) was used to fit an output from a previously published diagenetic model (OMEXDIA) to observational data, taken at the North Dogger site from a series of cruises in the North Sea. Profiles of carbon, oxygen, nitrate and ammonia were considered. The method allows a set of parameters to be determined in a manner analogous to natural selection. Each iteration of the genetic algorithm within each experiment decreases the variance between the observed profiles and those calculated by OMEXDIA.Results and discussionDespite some of the observed profiles, particularly for carbon, showing unusual patterns, the genetic algorithm was able to generate a set of parameters which was able to fit the observations. The genetic algorithm can therefore help to determine the values of other parameters used in the model, for which observational values are difficult to measure (e.g. the flux of organic matter to the sediment from the overlying water column and the rates of degradation of organic matter). We also show that the values of the parameters determined by the μGA technique are able to be used in a potentially temporally predictive manner.ConclusionsThe μGA used is a viable method to fit carbon and nutrient sedimentary profiles observed in complex, dynamic shelf sea systems, despite OMEXDIA originally being designed for a different sedimentary environment. The results therefore show that this novel use of a genetic algorithm is a suitable method for both model calibration and validation and that the technique may help in explaining processes which are poorly understood.
登录
查看更多内容
北海东北部斯卡格拉克最近的沉积物堆积
DOI：
--
发表时间：
1987
期刊：
影响因子：
--
作者：
T. V. Weering;G. Berger;J. Kalf
通讯作者：
J. Kalf
淡水体底部沉积物铵态氮释放研究-Ⅰ
DOI：
--
发表时间：
1976
期刊：
影响因子：
--
作者：
K. Kamiyama;S. Okuda;A. Kawai
通讯作者：
A. Kawai
天然水体和沉积物中有机物的微生物分解和养分再生：文献研究报告
DOI：
--
发表时间：
1980
期刊：
影响因子：
--
作者：
J. Smits
通讯作者：
J. Smits
作为硅藻细胞添加到含氧和缺氧海洋沉积物微观世界中的有机碳的命运
影响因子：
2.5
作者：
Andersen Fø
通讯作者：
Andersen Fø
影响因子：
4.5
作者：
N. Revsbech;J. Sørensen;T. Blackburn;J. P. Lomholt
通讯作者：
N. Revsbech;J. Sørensen;T. Blackburn;J. P. Lomholt