应用属性识别模型评价洛阳市大气环境质量

通过将熵值法与属性识别理论相结合,建立了基于熵权的属性识别理论模型,并根据"大气环境质量标准"(GB3095-1996),对洛阳市2005年至2009年的大气环境质量进行了综合评价。结果表明:2005年至2009年洛阳市的大气环境质量均为Ⅱ级。评价结果与模糊数学综合评判法分析结果一致,说明运用属性识别理论应用于大气环境质量评价是合理可信的。     

人工神经网络在矿井多水源识别中的应用

以焦作矿区水化数据为例,选用Na++K+、Ca2+、Mg2+、Cl-、SO2-4、HCO-36种水化离子浓度作为识别矿井水源的依据,运用Matlab软件分别建立BP神经网络与Elman神经网络的矿井多水源识别模型。应用结果表明:与静态的BP神经网络相比,在结构上增加承接层的Elman神经网络在训练和仿真中拟合能力更强,识别精度更高和泛化能力更好;矿井地下水随着地下开采与扰动具有动态性,将具有非线性动态特征的Elman神经网络应用于矿井多水源的识别,对准确判断突水来源和分析地下水运移规律具有一定的辅助和指导意义。     

溧阳电站整流锥支撑系统施工安全影响因素识别研究

溧阳电站整流锥施工难度大,支撑系统安全性的高低直接关系整流锥浇筑安全。为实施安全重点监控,基于人员操作、工作环境、设备设施、现场管理等四个方面,系统分析整流锥支撑系统施工安全影响因素;综合运用二元语义基本理论,集结专家语言评价信息,结合DEMATEL(传统决策试验和评价实验法)核心思路,提出一种考虑因素间关联性的影响因素识别方法;辨析溧阳电站整流锥支撑系统施工安全影响因素重要程度与因果关系。结果表明:现场监督是影响其施工安全最重要的外部因素,基本素质是最易影响其他因素的原因因素,验收管理是最易受其他因素影响的结果因素。     

重金属污染土壤属性区间识别模型的赋权分析

土壤重金属污染评价为土壤重金属污染的及时防范和综合治理提供重要的理论依据。文章在属性区间识别理论的基础上,构建土壤重金属污染评价的属性区间识别模型：选取土壤重金属污染中普遍存在的Hg、Cd、As、Pb、Cu、Zn作为评价指标,采用均化系数将各评价指标的属性测度区间转化为综合属性测度;为避免主观因素,利用主成分分析法、熵权法、CRITIC法对各评价指标进行3次客观赋权;最后根据置信度准则和分级标准进行土壤重金属污染的综合评价。对3种赋权法得到的权重和评价结果进行比较,表明：属性识别模型在土壤重金属污染评价中适用且有利于评价结果准确性的提高;3种客观赋权法算得的权重合理,且其优异程度为主成分分析法〈熵权法〈CRITIC法。     

同位素示踪技术在沉积物重金属污染溯源中的应用

沉积物重金属污染及其防治愈来愈受重视,查明污染源是有效治理污染的前提。文章概述了近年来国内外铅、锶等同位素、放射性核素示踪技术在沉积物重金属污染溯源研究中的应用,针对以往研究工作的不足和存在的问题,指出了今后沉积物中重金属污染源解析研究中的重点:采用Pb、Sr、Zn等同位素示踪法,结合多元统计及其它元素地球化学信息追踪重金属污染源和评价污染程度。     

基于大数据挖掘技术的地震舆情感知研究

对地震舆情信息的深入感知和有效管理,能够保障社会和谐发展。提出一个基于大数据技术和深度学习的地震舆情感知平台,基于Hadoop和MongoDB大数据技术实现对海量实时地震舆情数据的处理和存储。基于Word2vec和LSTM的融合模型能够有效实现震后网民的情感识别,为舆情预警提供支持。以台湾5.8级地震舆情数据为例,对该平台进行了验证。实验结果表明,该平台能够有效对海量地震舆情信息进行监测和分析,对地震舆情情感识别精确率达到93.76%;在准确率和收敛速度性能上均高于传统CNN神经网络,能够为后续谣言的准确识别提供有力的支持。本研究可为相关灾害类舆情研究提供一些思路。     

基于指标协调性的水体富营养化状况的模糊识别

在湖泊富营养化评价指标体系中,同一指标的分级界点值差异很大,近似地呈现几何级数变化,同时各指标权重的选择与内涵存在不确定性,基于这两种认识,构建基于指标协调性和模糊权下的湖泊水质评价模型。对评价标准及待评价水质监测值进行对数变换,运用层次分析法求出指标的模糊权重;以此构造隶属函数,按最大隶属原则来评判地表水质量等级。应用此模型对巢湖西半湖水体进行富营养化识别,得出结果与生态评估结果基本一致。     

基于时序片段的油气管道运行工况识别方法*

为准确识别管道系统运行工况,提高对油气管道突发事故的响应速度,综合提升管网安全管理水平,提出1种基于时序片段的油气管道运行工况识别方法。首先,构建基于概率分布的状态变化识别模型,提取油气管道中不同运行状态点;其次,建立基于时间序列片段的工况识别模型,快速识别不同时间长度内油气管道运行工况;最后,以国内某成品油管道为例进行方法验证。研究结果表明:该方法可有效识别成品油管道阀门开关状态、泵异常停机和阀门内漏3种运行工况。对比传统的识别方法,该方法可降低状态变化点的漏报率,提升管道运行工况识别的准确率。研究结果可为油气管道系统运行工况识别提供新的借鉴方法。     

Hierarchical perception of fertility signals and nestmate recognition cues in two dolichoderine ants

In social insects, queens are likely to “honestly” inform their nestmates of their presence and fertility status through pheromonal communication. Cuticular hydrocarbons (CHCs) have been reported to be effective nestmate discriminators and strongly suspected to act as fertility signals, at least in some species. The use of the same chemical bouquet (i.e., the CHC profile) to convey two fundamentally different information seems puzzling. However, a recent threshold model proposes a hierarchy in the discriminating processes, i.e., fertility signals can only be perceived if nestmate recognition has been reached (Le Conte and Hefetz, Annu Rev Entomol 53:523–542, 2008). Here, we developed a simple behavioral bioassay based on chemical recruitment toward a queen placed outside the nest in two dolichoderine ants (Linepithema humile and Tapinoma erraticum), which allowed us to investigate the interplay between fertility signaling and colonial recognition. Using queen corpses of various origins (nestmates or aliens) and physiological states (fertile or infertile; mated or unmated), we demonstrated that nestmate recognition cues clearly override fertility signals under our experimental conditions. Indeed, while nestmate infertile queens were largely ignored by the workers, nestmate fertile queens (mated or not) induced worker recruitment, whereas alien fertile queens did not and were aggressed by the workers.     

Spatio-temporal dissolved oxygen dynamics in the Orbetello lagoon by fuzzy pattern recognition

This paper models the dissolved oxygen (DO) dynamics in the Orbetello lagoon as a function of the physico-chemical and ecological system variables, including the submerged vegetation, nutrients, and hydrodynamics. It should be viewed as the concluding sequel to a previous paper describing the dynamics of the lagoon ecosystem [Giusti, E., Marsili-Libelli, S., 2006. An integrated model for the Orbetello lagoon ecosystem, Ecol. Model. 196, 379–394] by introducing the missing DO dynamics. The model considers the oxygen demand originating from the decay of carbonaceous and nitrogenous compounds, as well as photosynthesis and natural reaeration by winds and currents as the oxygen producing processes. With a fixed-parameter set the model could accurately reproduce each single circadian DO cycle, but in the long run it failed to extend this fit and could not accommodate the large DO fluctuations induced by the seasonal variability. In order to enhance the model flexibility, a fuzzy pattern recognition algorithm was designed to classify the circadian DO patterns into four typical behaviours, related to the season, and estimate the corresponding parameters, with the overall model output being a fuzzy combination of these sets. The paper discusses several methods to patch the parameter sets and compares their performance in tracking long-term DO variations. A final assessment of the model validity is obtained by incorporating the whole DO dynamics (model, fuzzy pattern recognition and parameter combination) into the general lagoon model and producing a consistently correct series of DO daily distributions over a yearly cycle. Thus the paper contains both a practical and a methodological aspect. The practical one is the linking of all the lagoon dynamics to the dissolved oxygen kinetics in order to clarify to what extent macroalgae and macrophytes influence the oxygen balance. The methodological aspect consists of extending the validity of short-term models to long time-horizons through a patching technique supported by fuzzy pattern recognition.