基于最大熵模型的福建省红树林潜在适生区评估

本研究利用生物气候、地形、底质类型、海温等环境因子和红树林分布数据建立了福建省红树林分布模型,基于最大熵方法分析了福建省沿岸红树林潜在适生区的空间分布.根据模型输出结果对福建省红树林的生境适宜性进行了评估,识别了影响红树林分布的关键环境因子及其适生值区间,并通过空间叠加分析获取了福建省红树林保护与修复的优先区与空缺区域.结果表明,影响福建省红树林适生区分布格局的主要环境因子包括海表温度、气温和降水等,福建省红树林潜在适生区主要位于沙埕港-三沙湾-兴化湾沿岸、泉州湾-厦门湾-九龙江口沿岸、漳江口-东山湾沿岸等地,其中最优适生区面积约为91km².全省共识别出8处红树林保护与修复的优先区域,现存红树林保护率约为64.4%,保护修复空缺主要出现在沙埕港、三沙湾、罗源湾、福清湾等处,研究结论可为未来福建省红树林保护和修复行动提供科学参考.     

熵法估参在环境监测数据频率分析中的应用

以最大信息熵原理为理论基础的熵法估参方法，是一种具有严格物理和数学意义的新型参数估计方法，本文针对珠江广州河段主要污染物含量长年监测数据，对比熵法与传统方法矩法对四参数Г分布的估参结果，并以频率绝对离盖和最小为准则进行判定，结果表明，熵法估参结果与矩法总体上相当接近，且大部分样本的熵法估计参数优于矩法，在环境监测数据频率分析中具有实用性和推广价值。     

System safety assessment using safety entropy

Safety assessment has a primary role in hazardous operations. Most studies on safety assessment focus on risk and accident modeling, in which safety is absent. These top-down methods are highly dependent on the occurred accidents to establish accidental scenarios, which may make the assessment approach lagging behind the evolving modern systems. Moreover, this “special to general” logic is scientifically suspect in safety assessment. There is a call for the development of safety assessment methods in the presence of system safety to complement risk-focused safety analysis. These methods should provide a framework based on a bottom-up approach to examine system safety from the operational perspective. This paper has attempted to provide a potential solution. In particular, a novel concept of safety entropy is proposed to integrate with The Functional Resonance Analysis Method (FRAM), which is used to form the qualitative understanding of a system. A formula consisted of safety entropy, functional conformability, and system complexity has been established to determine the spontaneity of the safety state-changing process. The proposed method is applied to the safety assessment of a propane feed-control system. The results show the applicability of the method. Nevertheless, the model still needs to be further improved to fulfill better support for safety-related decision problems.     

Ontic openness: An absolute necessity for all developmental processes

The physicist Walter M. Elsasser is mostly known for his work on the Earth's magnetism. Less attention has been paid to his efforts toward identifying what are the real differences between physical and biological systems. One essential distinction he recognized was that physical systems are largely homogenous while biological systems always revealed what he called ordered heterogeneity. Calculation of the possible configurations of such heterogeneous systems almost always leads to combinatorial explosions and to what Elsasser referred to as immense numbers. Such calculations have the consequence that any such systems are necessarily unique - mathematically speaking they represent one-sets.Another consequence is that immense numbers automatically introduce enormous uncertainty and indeterminacy into the system. Such systems are said to be ontically open. Applying this perspective to the genome and employing the notion of informational entropy reveals a common drive behind all development. This means that both conventional Darwinian evolution as well as the genomic mistakes that are believed to lie behind processes like aging and diseases can be interpreted against the background of one and the same process.At the same time the approach demonstrates how Darwinian evolution encompasses other notions such as Kauffman's “adjacent possible” ( [Kauffman, 1995] and [Kauffman, 2000]) and Eldrege's and Gould's “evolution via punctuated equilibria” (e.g., [Eldredge and Gould, 1972] and [Gould and Eldredge, 1977]).     

Estimation of thermodynamic parameters of the biosphere, based on remote sensing

A method that allows the estimation of the thermodynamic parameters of the biosphere has been developed. It results in the subdivision of the following four phase states of the biosphere: three equilibrium states: “white planet” with high albedo and low entropy; temperate forest in winter with high entropy; and desert with high entropy; and one nonequilibrium state: the “active forests” with low entropy, high information gain and the highest exergy values. The phase shift to a nonequilibrium state happens when albedo is less than 0.2.     

基于云模型的页岩气开发环境影响评价

从大气环境、噪声与土壤环境、水环境和生态、安全与可持续4个方面构建页岩气开发环境影响指标体系,并建立基于熵权法和云模型评价法的页岩气环境影响评价模型。针对四川省某国家级页岩气示范区进行实证分析,结果表明:该地区页岩气开发环境影响处于中等程度。页岩气开发对水环境影响最大,其次是对大气环境的影响,再次是对噪声与土壤环境,对生态、安全与可持续方面影响相对最小。该模型的评价结果与页岩气开发环境影响现状相符,最后根据评价结果提出相关政策建议。     

基于信息熵与KPSO聚类法滑坡敏感性分析

选取南京地区滑坡为研究对象。基于DEM及遥感影像数据,选取样本,提取滑坡影响因素,计算影响因素熵值。利用K折粒子群优化(K PSO)方法,在GIS环境下针对地质资料缺乏情况,生成一个可靠的南京地区滑坡敏感图。自组织特征映射网络(SOM)法用作一个并行研究,结果作为K PSO法结果对比。结果表明,K PSO法聚类准确率为85%,自组织映射(S OM)法聚类结果准确率为80%,由此说明K PSO聚类法在地质资料不足前提下形成滑坡敏感区是一种行之有效的方法。