Application of Bayesian Analysis Based on Neural Network and Deep Learning in Data Visualization

This study aims to explore the application of Bayesian analysis based on neural networks and deep learning in data visualization.The research background is that with the increasing amount and complexity of data,traditional data analysis methods have been unable to meet the needs.Research methods include building neural networks and deep learning models,optimizing and improving them through Bayesian analysis,and applying them to the visualization of large-scale data sets.The results show that the neural network combined with Bayesian analysis and deep learning method can effectively improve the accuracy and efficiency of data visualization,and enhance the intuitiveness and depth of data interpretation.The significance of the research is that it provides a new solution for data visualization in the big data environment and helps to further promote the development and application of data science.

Web-based spatiotemporal visualization of marine environment data

With long-term marine surveys and research,and especially with the development of new marine environment monitoring technologies,prodigious amounts of complex marine environmental data are generated,and continuously increase rapidly.Features of these data include massive volume,widespread distribution,multiple-sources,heterogeneous,multi-dimensional and dynamic in structure and time.The present study recommends an integrative visualization solution for these data,to enhance the visual display of data and data archives,and to develop a joint use of these data distributed among different organizations or communities.This study also analyses the web services technologies and defines the concept of the marine information gird,then focuses on the spatiotemporal visualization method and proposes a process-oriented spatiotemporal visualization method.We discuss how marine environmental data can be organized based on the spatiotemporal visualization method,and how organized data are represented for use with web services and stored in a reusable fashion.In addition,we provide an original visualization architecture that is integrative and based on the explored technologies.In the end,we propose a prototype system of marine environmental data of the South China Sea for visualizations of Argo floats,sea surface temperature fields,sea current fields,salinity,in-situ investigation data,and ocean stations.An integration visualization architecture is illustrated on the prototype system,which highlights the process-oriented temporal visualization method and demonstrates the benefit of the architecture and the methods described in this study.

Influence of environmental data of different sources on marine species habitat modeling:A case study for Ommastrephes bartramii in the Northwest Pacific Ocean

The quality of environmental data and its possible impact on the marine species habitat modelling are often overlooked while the sources for these data are increasing.This study selected sea surface temperature(SST)from two commonly used sources,the NOAA Ocean Watch and IRI/LDEO Climate Data Library,and then constructed habitat suitability index model to evaluate the influences of SST from the two sources on the outcomes of Ommastrephes bartramii habitat models for the months of July–October in the Northwest Pacific Ocean during 1996–2012.This study examined the differences in the amount of estimated unfavourable/favourable habitat area when the SST used for model building and inference were the same or different.Dynamics in suitable habitat area calculated from SST was insensitive to the two different SST products.In the fishing season of O.bartramii,the changes of magnitude and trend of monthly suitable habitat area in August and September were similar over time,whereas there were large differences for July and October.Importantly,there is a substantial lack of consistency in the O.bartramii habitat distribution based on SST of two sources.This study considered the sources of environmental data for habitat modelling and then inferred species habitat distribution whether by the same or different data source.

An Empirical Study on the Environmental Kuznets Curve for China's Carbon Emissions:Based on Provincial Panel Data

Based on the Environmental Kuznets Curve theory,the authors choose provincial panel data of China in 1990 2007 and adopt panel unit root and co-integration testing method to study whether there is Environmental Kuznets Curve for China's carbon emissions.The research results show that:carbon emissions per capita of the eastern region and the central region of China fit into Environmental Kuznets Curve,but that of the western region does not.On this basis,the authors carry out scenario analysis on the occurrence time of the inflection point of carbon emissions per capita of different regions,and describe a specific time path.

Environmental Data Acquisition, Elaboration and Integration： Preliminary Application to a Vulnerable Mountain Landscape and Village （Novalesa, NW Italy）

气候条件影响了山地社区的社会经济发展,特别是易发生高山斜坡破坏和泥石流等自然灾害的山区,气候因素将发挥重要的影响作用,因此在制定适当的可持续发展方案时应考虑到气候因素。同时,气候变化改变了生态系统服务(ES)功能,使得土壤肥力下降、水资源供应减少、草地面积减少、监管服务(如防止自然灾害)和文化服务发生潜在转变。本研究以意大利阿尔卑斯山区为研究区域进行初步讨论,该地区经历过极端降水和侵蚀,社区的发展十分依赖于对自然资源的直接利用。初步研究结果表明,经济因素影响了诺瓦莱萨社区(位于意大利西北部的皮埃蒙特地区)过去的人口变化趋势。然而,由气象气候因素引发的岩崩和泥石流事件的数量不断增加,可能会进一步影响社区人们的生计。因此,环境监测和数据分析对于辨识景观和气候变化的趋势并选择适当的规划方案是很重要的,这有助于将山地社区人口维持在全球人口的10%左右,这也是贫困地区未来经济发展的一个重要机遇。

Effect of FDI on China's environmental pollution: Evidence based on spatial panel data

It is clearly stated in the 19th people's congress that we should make the environmental protection as our national policy. Therefore, it is of great importance to study this issue. This article is going to consider 30 provinces of China as the cross-section, and utilize the data sample from 2006 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of FDI. By using these data, this article creates a comprehensive environmental pollution index with the help of entropy. The result indicates that the effect of FDI on environment has a non-linear and spatial spillover characteristic. Before reaching the critical value, FDI has a negative effect on environment; however, with the accumulation of FDI, it will create a significant positive effect on the environment.

Frame Work of Data Envelopment Analysis—A Model to Evaluate the Environmental Efficiency of China'S Industrial Sectors

Objective To evaluate the environmental and technical efficiencies of China＇s industrial sectors and provide appropriate advice for policy makers in the context of rapid economic growth and concurrent serious environmental damages caused by industrial pollutants. Methods A data of envelopment analysis （DEA） framework crediting both reduction of pollution outputs and expansion of good outputs was designed as a model to compute environmental efficiency of China＇s regional industrial systems. Results As shown by the geometric mean of environmental efficiency, if other inputs were made constant and good outputs were not to be improved, the air pollution outputs would have the potential to be decreased by about 60% in the whole China. Conclusion Both environmental and technical efficiencies have the potential to be greatly improved in China, which may provide some advice for policy-makers.

Employment effect of China's environmental regulation: Evidence based on spatial panel data

This article considers 30 provinces of China as the cross-section subjects, and utilizes the data sample from 2009 to 2015 of these cross-sections to formulate a Spatial Panel Data Durbin Model to analyze the effect of environmental regulation on employment. The result indicates that environmental regulation has negative effect on employment with the consideration of spatial spillover effect, and this adverse effect is not significant mathematically. With the enhance of environmental regulation, the negative impact on employment will decrease accordingly, even may eventually promote job growth, which means there may be a non-linear relationship between them. Specifically, the direct effect of environmental regulation on employment indicates that it is beneficial for job growth whereas the indirect effect illustrate that it is detrimental for employment.

环境规制、数据要素配置水平与产业结构调整

文章基于数字经济、绿色经济发展深刻影响产业结构转型升级进程这一背景,首先在理论分析的基础上构建了数据要素配置水平综合评价指标体系;然后采用Dagum基尼系数对数据要素配置水平的空间差异及主要来源进行分解测算;最后,基于2012—2019年省级面板数据探讨了环境规制的结构调整红利及数据要素有效配置的渠道效应。研究结果显示,我国数据要素配置水平总体空间差异明显,且区域间差异为主要来源,区域内差异次之。环境规制对产业结构升级存在先促进后抑制的“倒U”型影响,数据要素配置也有显著促进作用。动态边际效应结果显示,在研究期内环境规制所带来的产业结构“调整红利”正在逐渐弱化,数据要素优化配置可充当环境规制促进产业结构升级的有效路径,且从子维度来看,数据传播共享的渠道效应最为显著。数据要素配置的网络外部性特征对环境规制和产业结构优化的调节作用在不同地区所呈现的阶段性特征不同。

基于红外成像技术的城乡局部环境监测与分析研究

结合红外探测成像技术在复杂环境监测中的独特优势,研制了基于连续变焦中波红外成像技术的城乡局部环境监测系统,对城乡局部地区燃煤情况开展实时监测,并完成数据处理分析,为研究城乡地区燃煤趋势和特点、实施监控管理提供有力技术和数据支撑。经过在某市城乡结合地区开展的实地监测试验验证,证明该系统运行稳定、成像清晰,可实现对燃煤地区全局和重点位置的全天候在线监测,数据处理准确有效,该系统具有良好的工程应用价值。

浅谈数据资产化对推进生态环境监测数据共享利用的影响

传统生态环境监测数据共享利用存在共享意愿不高、权益不对称、低效率和数据权益不清等问题。数据资产化为解决生态环境监测数据共享难题提供了新思路。本文首先梳理了生态环境监测领域数据共享存在数据孤岛、数据质量等问题及面临的挑战。其次,从推动资产收益、培育监测市场、服务政府管理决策、推进数据共享及技术变革等角度对生态环境监测数据资产化潜在影响进行了讨论。最后,对生态环境监测领域如何推进数据资产化、促进监测数据资源高效共享利用进行了策略分析和展望。

基于遗传算法的炮击振动环境谱编制方法

为了提高炮击振动环境谱编制精度,提出了基于遗传算法(genetic algorithm,简称GA)的炮击振动环境谱特征点确定方法。首先,介绍了现有标准的预估炮击振动谱的编制方法;其次,以炮舱结构模拟件为对象,开展了炮击振动试验并获取了实测谱,基于飞机飞行振动环境测量数据的归纳方法对实测谱进行了归纳处理;然后,以特征点构成的环境谱与实测数据归纳谱的能量最接近为目标建立目标函数,采用遗传算法对目标函数进行优化以确定炮击振动谱特征点坐标,在对数坐标下通过折线将特征点连接以实现炮击振动环境谱的编制;最后,将基于遗传算法得到的环境谱与基于标准得到的预估谱进行对比,分析验证了所提方法的有效性。结果表明,所采用的方法获得的炮击振动环境谱在均方根值(rootmean square,简称RMS)和谱形特征上都更接近实测数据归纳谱。

基于多传感数据融合的室内空间适老化环境监测系统设计

针对当前多传感数据融合算法性能不够理想导致室内空间适老化环境监测效果较差的问题,提出一种改进的多传感数据融合算法。提出一种变长数据融合算法(VLDFA)来消除冗余数据,对蜻蜓优化算法(DA)进行改进,结合改进DA和改进BP神经网络(BPNN),构建多传感数据融合模型。结果显示,该模型的精度超过98%。在温度误差与湿度误差监测比较中,所提出的模型的温度误差平均值为0.34℃,优于另外2种模型,表明该模型的多传感数据融合效果较为良好,能够很好地调整老年人居住环境。

Environmental Information Governance Reform in the Era of Big Data--From Information Disclosure to Public Service

The development of environmental information governance includes three phases: providing for oneself,information disclosure,and public service. And then China is in the transition and transformation of environmental information disclosure to the environmental information public service. The core of the transformation is public participation,in the whole procedure of environmental information supply decision making,production,and quality supervision and evaluation,etc. The target path of the environmental information governance reform includes five parts: improvement of public satisfaction,optimizing information disclosure,information quality control,integration of information resources,and multiple supply.

大数据视域下印染行业环保趋势预测与策略

印染行业作为全球制造领域的重要组成部分,其生产过程中大量使用水资源、化学染料和助剂,产生的废水和废气对生态系统和人类健康构成严重威胁。随着环保意识的增强和法规的严格执行,印染行业亟须寻求新的方法和技术来减少对环境的影响,实现可持续发展。印染行业通过利用大数据技术,收集和分析大规模数据,更准确地预测环保趋势,优化资源配置,提高废弃物管理效率,实施有效的污染预防措施,并确保政策合规,为行业的环境管理和政策制定提供科学依据和决策支持。

环境分权与企业生产率--来自“国控源环境数据直报”政策的经验证据

环境分权是中央政府和地方政府对于环境事权的分配,而“国控源环境数据直报”政策本质上是一次调整环境分权化水平的改革。将该政策视为一个准自然实验,构建双重差分模型,考察其对企业生产率的影响。研究发现,该政策在短期内会显著抑制国家重点监控企业的生产率提升,但随着时间的推移,这种抑制作用会逐渐消失。结合环境分权理论进一步阐释和验证该政策对企业生产率的潜在影响机制,发现该政策主要通过挤出企业研发投入、抑制企业寻租行为和激励企业自愿规制环境行为等机制抑制企业生产率。进一步分析表明,企业所有制、行业污染密集程度和地区市场化水平等特征会对环境分权与企业生产率之间的关系产生异质性影响。环境分权与微观企业行为之间因果关系的揭示,可以为政府健全“国控源环境数据直报”政策的长效机制提供决策参考。

大数据能力对科技型企业绩效的影响机制研究--环境不确定性调节效应

本文基于资源基础理论、动态能力理论等,利用河南省科技型企业216个样本数据,对大数据能力、环境动态性、环境复杂性和企业绩效的关系进行实证研究,研究结果显示:第一,企业大数据能力对企业绩效有显著的正向影响。第二,企业资源获取能力、企业洞察预测能力对企业绩效有正向影响,资源获取能力对企业绩效的影响最大;企业整合分析能力对企业绩效的影响没有显著的影响。第三,环境动态性和环境的复杂性对大数据能力与企业绩效的调节效应是显著。最后指出了本研究对管理实践的启示,并从政府和企业层面提出了对策建议。

大数据背景下造纸企业经营风险识别与管理优化研究

近年来,大数据技术的快速发展颠覆了造纸企业传统的风险控制模式,大数据技术在企业经营管理中实现降本增效的趋势越发明显。基于此,简述了造纸企业经营风险的种类与控制现状,探究了大数据时代给造纸企业经营风险控制带来的积极效应与消极影响,结合某些造纸企业经营实例进行经营风险的识别与分析,并基于大数据背景提出造纸企业经营风险识别与管理优化策略,以期建立科学、有效的经营风险预防与管控体系,提升造纸企业经营管理水平。

汽车制造业绿色供应链管理对环境绩效的影响研究

从绿色供应链管理和大数据分析能力视角探讨制度压力对企业环境绩效的影响机理,揭示绿色供应链管理和大数据分析能力在企业环境绩效形成过程的作用。研究结果表明:制度压力对绿色供应链管理实施与大数据分析能力有显著影响;绿色供应链管理与大数据分析能力对企业环境绩效提升有显著影响;大数据分析能力对企业绿色供应链管理实施有显著影响;在制度压力对环境绩效的影响中,大数据分析能力与绿色供应链管理存在部分中介效应。研究结果能够为汽车制造企业重视大数据分析能力建设和绿色供应链管理实践,提高环境绩效提供一定的参考价值。