Application of an evolutionary algorithm to the inverse parameter estimation of an individual-based model

Inverse parameter estimation of individual-based models (IBMs) is a research area which is still in its infancy, in a context where conventional statistical methods are not well suited to confront this type of models with data. In this paper, we propose an original evolutionary algorithm which is designed for the calibration of complex IBMs, i.e. characterized by high stochasticity, parameter uncertainty and numerous non-linear interactions between parameters and model output. Our algorithm corresponds to a variant of the population-based incremental learning (PBIL) genetic algorithm, with a specific “optimal individual” operator. The method is presented in detail and applied to the individual-based model OSMOSE. The performance of the algorithm is evaluated and estimated parameters are compared with an independent manual calibration. The results show that automated and convergent methods for inverse parameter estimation are a significant improvement to existing ad hoc methods for the calibration of IBMs.     

Quantifying parameter uncertainty in a coral reef model using Metropolis-Coupled Markov Chain Monte Carlo

Coral reefs are threatened ecosystems, so it is important to have predictive models of their dynamics. Most current models of coral reefs fall into two categories. The first is simple heuristic models which provide an abstract understanding of the possible behaviour of reefs in general, but do not describe real reefs. The second is complex simulations whose parameters are obtained from a range of sources such as literature estimates. We cannot estimate the parameters of these models from a single data set, and we have little idea of the uncertainty in their predictions.We have developed a compromise between these two extremes, which is complex enough to describe real reef data, but simple enough that we can estimate parameters for a specific reef from a time series. In previous work, we fitted this model to a long-term data set from Heron Island, Australia, using maximum likelihood methods. To evaluate predictions from this model, we need estimates of the uncertainty in our parameters. Here, we obtain such estimates using Bayesian Metropolis-Coupled Markov Chain Monte Carlo. We do this for versions of the model in which corals are aggregated into a single state variable (the three-state model), and in which corals are separated into four state variables (the six-state model), in order to determine the appropriate level of aggregation. We also estimate the posterior distribution of predicted trajectories in each case.In both cases, the fitted trajectories were close to the observed data, but we had doubts about the biological plausibility of some parameter estimates. We suggest that informative prior distributions incorporating expert knowledge may resolve this problem. In the six-state model, the posterior distribution of state frequencies after 40 years contained two divergent community types, one dominated by free space and soft corals, and one dominated by acroporid, pocilloporid, and massive corals. The three-state model predicts only a single community type. We conclude that the three-state model hides too much biological heterogeneity, but we need more data if we are to obtain reliable predictions from the six-state model. It is likely that there will be similarly large, but currently unevaluated, uncertainty in the predictions of other coral reef models, many of which are much more complex and harder to fit to real data.     

国外家畜粪便肥料成分含量快速预测方法的研究

研究家畜粪便的物理指标与其肥料成分含量的关系,用来预测家畜粪便肥料成分含量.目前国外主要研究的预测家畜粪便肥料成分含量的物理指标主要有:干物质含量、比重、电导率、流变学特性、pH值及几个指标的组合.研究表明,预测牛、奶牛和猪粪便中氮和磷的含量可用比重和干物质含量,并且用比重代替干物质含量更易于实现畜禽粪便营养成分含量的快速和在线检测;电导率可预测牛、猪粪便中铵态氮和钾的含量;此外家畜粪便的流变学特性ln(k)和pH值也可用来预测某些成分,但效果较差.同时采用某2个物理指标来预测的效果优于单个指标的预测效果.     

Odour from municipal solid waste (MSW) landfills: a study on the analysis of perception

The objective of this work was to develop a relationship between odour intensity and odour concentration by using data collected from various sensitive areas of the municipal solid waste (MSW) landfill site. A number of well-known psychophysical models (e.g., Weber-Fechner law, Steven's power law, Beidler's and Laffort's models) have been discussed that can successfully relate the perceived intensity with the odour concentration. Respective parameters for each of the models were estimated by the nonlinear Levenburg-Marquardt parameter estimation method. The overall performance of the model was tested statistically against sets of data from the olfactometry analysis. The model based on the Weber-Fechner law was ranked 1 in case of five out of nine samples and it has been found more representative of the less intense odour samples. The model based on Laffort's equation has represented the intensity-concentration relationship better with extremely low uncertainties on both parameters k1 and k2 for comparatively more intense odour samples.     

复杂矿井通风系统分支阻力可调性数值研究

笔者应用数字实验方法 ,通过调节分支阻力 ,研究它对通风系统的影响。研究结果表明 :当一些分支的阻力调到接近完全隔断风流的极大值时 ,网络分析结果仍然正常 ,不影响迭代技术 ;同样也说明了分支阻力预先输入的可行性 ;各分支阻力的变化对通风系统的影响程度是不一样的 ,这由分支在通风网络中的位置决定 ;通过分析 ,给出了通风系统中两风机的相互影响的情况。     

The indicator performance estimate approach to determining acceptable wilderness conditions

Using data from a study conducted in the Cranberry Wilderness Area of West Virginia, United States, this paper describes how a modified importance—performance approach can be used to prioritize wilderness indicators and determine how much change from the pristine is acceptable. The approach uses two key types of information: (1) indicator importance, or visitor opinion as to which wilderness indicators have the greatest influence on their experience, and (2) management performance, or the extent to which actual indicator conditions exceed or are within visitor expectations. Performance was represented by calculating indicator performance estimates (IPEs), as defined by standardized differences between actual conditions and visitor preferences for each indicator. The results for each indicator are then presented graphically on a four-quadrant matrix for objective interpretation. Each quadrant represents a management response: keep up the good work, concentrate here, low priority, or possible overkill. The technique allows managers to more systematically and effectively utilize information routinely collected during the limits of acceptable change wilderness planning process. This paper is submitted with the approval of the Director of the West Virginia Agricultural and Forestry Experiment Station as Scientific Article No. 541. The study was funded in part, through a grant from the USDA Forest Service, Monongahela National Forest.     

煤矿企业成长性评价指标与评价方法

本文从煤矿企业生产经营和技术的特点出发,用总资产收益率及增长率与每元经营现金流量及增长率,来定量描述企业成长性的量的表现,从而构造了企业成长性评价指标体系和综合评价方法,定量地测度企业成长性。用企业技术五要素结构分析方法,具体研究了煤矿企业的技术结构,用未确定测度理论定量测度企业技术含量及增长率,来描述煤矿企业成长性的质的表现。根据煤矿企业的特点,研究煤矿企业的成长性及其建立适合煤炭评价指标和方法,为矿业企业可持续发展进行理论指导。     

Maximum likelihood fitting of the Poisson lognormal distribution

In this paper some properties and analytic expressions regarding the Poisson lognormal distribution such as moments, maximum likelihood function and related derivatives are discussed. The author provides a sharp approximation of the integrals related to the Poisson lognormal probabilities and analyzes the choice of the initial values in the fitting procedure. Based on these he describes a new procedure for carrying out the maximum likelihood fitting of the truncated Poisson lognormal distribution. The method and results are illustrated on real data. The computer program for calculations is freely available.

Testing of the Storm Water Management Model Low Impact Development Modules

Stormwater infrastructure designers and operators rely heavily on the United States Environmental Protection Agency’s Storm Water Management Model (SWMM) to simulate stormwater and wastewater infrastructure performance. Since its inception in the late 1970s, improvements and extensions have been tested and evaluated rigorously to verify the accuracy of the model. As a continuation of this progress, the main objective of this study was to quantify how accurately SWMM simulates the hydrologic activity of low impact development (LID) storm control measures. Model performance was evaluated by quantitatively comparing empirical data to model results using a multievent, multiobjective calibration method. The calibration methodology utilized the PEST software, a Parameter ESTimation tool, to determine unmeasured hydrologic parameters for SWMM’s LID modules. The calibrated LID modules’ Nash–Sutcliffe efficiencies averaged 0.81; average percent bias (PBIAS) ?9%; average ratio of root mean square error to standard deviation of measured values 0.485; average index of agreement 0.94; and the average volume error, simulated vs. observed, was +9%. SWMM accurately predicted the timing of peak flows, but usually underestimated their magnitudes by 10%. The average volume reduction, measured outflow volume divided by inflow volume, was 48%. We had more difficulty in calibrating one study, an infiltration trench, which identified a significant limitation of the current version of the SWMM LID module; it cannot simulate lateral exfiltration of water out of the storage layers of a LID storm control measure. This limitation is especially severe for a deep LIDs, such as infiltration trenches. Nevertheless, SWMM satisfactorily simulated the hydrologic performance of eight of the nine LID practices.     

电子设备的可靠性设计

对电子设备的可靠性设计进行了介绍,其中包括可靠性设计的任务和意义、可靠性设计基本任务、电子设备可靠性设计的基本方法等,其目的在于提高电子设备的可靠性和质量.