Structural characteristics and influencing factors of spatial correlation network for regional high-quality development in China

On the basis of measuring the regional high-quality development in China from 2011 to 2020,this study uses gravity model to build spatial correlation network,and uses social network analysis method to analyze the structural characteristics and influencing factors of correlation network.The results are shown as follows.First,from 2011 to 2020,the level of regional high-quality development in China is rising gradually,and the discrete characteristics between regions are gradually obvious,showing a step-like distribution structure decreasing from east to west.Second,the network density of regional high-quality development is generally low and tends to decline,but it has strong stability and correlation strength.Third,the spatial correlation network has an obvious core-edge structure.Shanghai is always at the center of the network and plays a significant intermediary role,while Qinghai and Xinjiang are always at the edge of the network.Fourth,the regional high-quality development association network can be divided into four major sectors:main benefit,net benefit,net spillover,and broker,showing the spatial correlation characteristics of inter-plate contact and intra-plate agglomeration.Fifth,the level of economic development,the level of urbanization and geographical proximity have a significant impact on the formation of regional high-quality development correlation network.

Enhancing Social Capital Through Networking for Sustainable Tourism Development： An Application to Khon Kaen Province, Thailand

Social capital has been recognised as a factor affecting sustainable development in every discipline. A network or a partnership is identified as a ＂structural＂ form of social capital and a tool to empower participants in the networks. There is a belief that social networks can be initiated or created at every level of social capital, from micro to macro. However, the concept of community is the key component of social capital, creating both physical ties （geographical locality） and normative behaviours （sense of belonging）. Therefore, this study is intended to enhance social capital at the community or micro-level, in order to sustain tourism development in those areas, and networking is initiated to enhance social capital. Participatory Action Research （PAR） was applied to tourism development in Kon Kaen Province. Tools and techniques used during this study included： observations, preliminary meetings, community meetings, tourism audits, workshops, and network meetings. Eleven districts in Khon Kaen were actively involved in the planning process.

A systems perspective on national prioritisation of sustainable development goals:Insights from Australia

Achieving the Sustainable Development Goals(SDGs)requires effective national initiatives and resource allo-cation.Yet,the simultaneous attainment of all goals is hindered by constraints such as limited budgets and resources,varied national priorities,and the intricate nature of the goals.As we approach 2030 and beyond,an urgent need for an effective,data-driven prioritisation system exists to optimise what can be accomplished.A considerable knowledge gap persists in identifying the priority areas that demand concentrated attention and how their improvement would propel overall sustainability goals.To bridge this gap,our study presents a priori-tisation approach that identifies significant SDG indicators based on urgency and impact,utilising Benchmarking,Bivariate,and Network analysis.Furthermore,we introduce an innovative Impact Index(IMIN)to assess an indi-cator’s extensive effect on the SDG network.This system carries significant international relevance by establishing a robust framework to identify key,potent,and interconnected indicators.It supports decision-makers worldwide in comprehending their nation’s SDG performance and promotes efficient resource allocation.In the specific con-text of Australia,our analysis spotlights several impactful,yet underperforming SDG indicators.These include the protection of Freshwater,Terrestrial,and Mountain Key Biodiversity Areas(KBAs),the share of renewable energy and energy intensity level of primary energy,targeted research and development,gender equality in national parliaments,and carbon-efficient manufacturing,amongst others.

Development and application of a GIS-based artificial neural network system for water quality prediction: a case study at the Lake Champlain area

Artificial Neural Network(ANN)models have been extensively applied in the prediction of water resource variables,and Geographical Information System(GIS)includes powerful functions to visualize spatial data.In order to provide an efficient tool for environmental assessment and management that combines the advantages of these two modules,a GIS-based ANN water quality prediction system was developed in the present study.The ANN module and ArcGIS Engine module,along with a dynamic database,were imbedded in the system,which integrates water quality prediction via the ANN model and spatial presentation of the model results.The structure of the ANN model could be modified through the graphical user interface to optimize the model performance.The developed system was applied to a real case study for the prediction of the total phosphorus concentration in the Lake Champlain area.The prediction results were verified with the monitoring data,and the performance of the developed model was further evaluated through graphical techniques and quantitative statistical methods.Overall,the developed system provided satisfactory prediction results,and spatial distribution maps of the predicted results were obtained,which coincided with the monitored values.The developed GIS-based ANN water quality prediction system could serve as an efficient tool for engineers and decision makers.

APPLICATION OF ARTIFICIAL NEURAL NETWORK IN COMPLEX SYSTEMS OF REGIONAL SUSTAINABLE DEVELOPMENT

Meeting the challenge of sustainable development requires substantial advances in understanding the interaction of natural and human systems. The dynamics of regional sustainable development could be addressed in the context of complex system thinking. Three features of complex systems are that they are uncertain, non-linear and self-organizing. Modeling regional development requires a consideration of these features. This paper discusses the feasibility of using the artificial neural networt(ANN) to establish an adjustment prediction model for the complex systems of sustainable development (CSSD). Shanghai Municipality was selected as the research area to set up the model, from which reliable prediction data were produced in order to help regional development planning. A new approach, which could help to manage regional sustainable development, is then explored.

APPLICATION OF NEURAL NETWORK WITH MULTI-HIERARCHIC STRUCTURE TO EVALUATE SUSTAINABLE DEVELOPMENT OF THE COAL MINES

The neural network with multi hierarchic structure is provided in this paper to evaluate sustainable development of the coal mines based on analyzing its effect factors. The whole evaluating system is composed of 5 neural networks.The feasibility of this method has been proved by case study. This study will provide a scientfic and theoretic foundation for evaluating the sustainable development of coal mines.

Prioritizing sustainable development goals and linking them to ecosystem services:A global expert’s knowledge evaluation

The implementation of strategies to achieve the Sustainable Development Goals(SDGs)is frequently hindered by potential trade-offs between priorities for either environmental protection or human well-being.However,ecosystem services(ES)-based solutions can offer possible co-benefits for SDGs implementation that are often overlooked or underexploited.In this study,we cover this gap and investigate how experts from different countries value the SDGs and relate them with ES.A total of 66 countries participated to the survey,and answers were grouped into three macro-regions:Asia;Europe,North America,and Oceania(ENO);Latin America,Caribbean and Africa(LA).Results show that the most prioritized SDGs in the three macro-regions are usually those related to essential material needs and environmental conditions,such as SDG2(Zero Hunger),SDG1(No Poverty),and SDG6(Clean Water).At a global scale,the number of prioritized synergies between SDGs and ES largely exceeded trade-offs.The highest amount of synergies was observed for SDG1(No Poverty),mainly with SDG2,SDG3(Good Health),SDG5(Gender Equality),and SDG8(Economic Growth).Other major synergies among SDGs include SDG14-15(Life below water-Life on land),SDG5-10(Gender Equity-Reduced Inequality),and SDG1-2(No poverty-Zero Hunger).At a global scale,SDG15,SDG13,SDG14,and SDG6 were closely related to ES like climate regulation,freshwater,food,water purification,biodiversity,and education.SDG11(Sustainable Cities)and SDG3 were also relevant in Asia and in LA,respectively.Overall,this study shows the potential to couple future policies that can implement SDGs’strategies while adopting ES-based solutions in different regions of the world.

Prediction and Analysis of Air Quality Based on FCM and BP Neural Network

In the paper,we solve the problems of air quality prediction and evaluation. Firstly,the original data of air quality monitoring are classified by fuzzy C means clustering algorithm（ FCM）; then the BP neural network model to predict the level of air quality is built through the simulation training of data. Experiments show that the model has good generalization ability and strong stability,and the prediction accuracy is higher,which has certain application value.

Network Management of Food Additives Quality Analysis and Inspection

In this paper, on the basis of the implementation of the national chemical industry standard analytical test methods and analysis of test items, a food additive quality analysis and inspection of network management applications are developed using the development technology of Visual Basic language and computer system operating environment, to achieve a network management software for users on food additives of quality analytical testing. The software sets up an information sharing network platform for enterprise and quality management departments, which is a major innovation in the food additive quality analysis on test management methods and tools.

Sustainable Development Plan Based on Mathematic Model Analysis

Sustainable development has been a global issue, which focuses on balancing human needs with the earth＇ s health. In this paper, we construct a model to distinguish the sustainability of a country. To evaluate the sustainability of a country, we select eight metrics based on four aspects： Society, Economics, Ecology and Politics. We use BP neural network to obtain the sustainability ranking and use Grey Relational Analysis to calculate the sustainability scores of 187countries. By combining the ranking and the score, we develop a measure to define whether a country is sustainable or not. The critical point is Maldives, which ranks No. 103 and scores 63.65. As one of least developed countries, Uganda ranks No.164 and scores 48.79, according to our measure. Based on Uganda＇ s society, population, natural resources, etc., we draft a 20-year （2013-2033） sustainable development plan that integrates the social, economic, ecological and political components. The overall goal of the plan is to transform Uganda into a sustainable country and make noticeable progress in the ranking. Furthermore, to analyze changes＇ influence on our plan, we take climate change as an example. The weights of Environment and Health will be modified by climate change, causing a reduction in the growth rate of sustainability score.

A Study on the Sustainable Development of Tourism under the Perspective of lnternet Travel Consumers

With the rapid development of China＇s tourism market and the gradual improvement of people＇s pace of life, tourism has become an important way to relax people, so the proportion of tourism consumption in people＇s daily consumption gradually increased. In the context of the continuous development of Interact technology, consumer network characteristics become more and more obvious, followed by the emergence of a new consumer groups, that is, travel network consumers. Tourism network consumers as a new consumer group develop rapidly. The rapid development of the Internet has led to the great changes in the tourism industry. However, because of the tourism developers＇ only immediate interests, wanton development of tourism base, and the weak public awareness of tourism, the environment caused serious damage. This paper elaborates the concrete manifestation of the sustainable development of tourism, analyzes the adverse effects of the tourism industry on the ecological environment in sustainable development, and puts forward effective measures to promote the coordinated development of tourism and environmental protection.

Blind Image Quality Assessment by Pairwise Ranking Image Series

Image quality assessment(IQA)is constantly innovating,but there are still three types of stickers that have not been resolved:the“content sticker”-limitation of training set,the“annotation sticker”-subjective instability in opinion scores and the“distortion sticker”-disordered distortion settings.In this paper,a No-Reference Image Quality Assessment(NR IQA)approach is proposed to deal with the problems.For“content sticker”,we introduce the idea of pairwise comparison and generate a largescale ranking set to pre-train the network;For“annotation sticker”,the absolute noise-containing subjective scores are transformed into ranking comparison results,and we design an indirect unsupervised regression based on EigenValue Decomposition(EVD);For“distortion sticker”,we propose a perception-based distortion classification method,which makes the distortion types clear and refined.Experiments have proved that our NR IQA approach Experiments show that the algorithm performs well and has good generalization ability.Furthermore,the proposed perception based distortion classification method would be able to provide insights on how the visual related studies may be developed and to broaden our understanding of human visual system.

智慧物流与企业可持续发展——基于经济绩效与环境绩效的双重验证

在“双碳”战略目标和可持续发展背景下,智慧物流为促进企业可持续发展提供了新契机。利用2009—2021年我国地级及以上城市数据,测度城市层面智慧物流水平,并将其与A股制造业上市公司数据进行匹配,考察了智慧物流对企业经济绩效和环境绩效的影响。结果表明,智慧物流对企业经济绩效和企业环境绩效具有显著的正向影响,这意味着智慧物流可以促进企业可持续发展。机制检验表明,智慧物流通过发挥成本效应、市场整合效应以及学习效应三种机制促进企业可持续发展。异质性分析表明:智慧物流的可持续发展效应主要存在于交通条件便利地区和外部媒体关注度高的企业;对于市场激励型环境规制地区,智慧物流仅发挥了经济效应。拓展研究发现,智慧物流对企业可持续发展的影响具有网络效应,现代物流创新发展试点政策的激励作用尚未实现经济与环境“和谐共生”。研究结论为我国政府优化智慧物流政策和“双碳”愿景下制造业企业实现可持续发展提供了路径选择。

社工机构介入儿童友好型社区营造的行动逻辑与可持续发展策略——以安徽省X项目为例

儿童友好型社区营造需要多主体协同参与,包括由民政部门、基层社区、社区居民、高校等主体组成的人类行动者以及社区文化、公共空间、课程体系等非人类行动者,社工机构如何激活这一行动者网络依然有待讨论。本文以安徽省X项目为例,借鉴行动者网络理论的框架,从转译的不同阶段分析社工机构的行动逻辑:在问题呈现阶段确立共同行动目标与强制通行点;在利益赋予阶段协调各类行动者的关键利益;在征召阶段推动异质行动者的融合加入;在异议动员阶段构建互利共赢的利益共同体。为了保障儿童友好型社区营造的可持续性,社工机构可采取的策略包括:通过调研评估挖掘社区特色的内源力、通过跨界融合吸纳异质行动者的加入、通过平台搭建畅通主体间的沟通渠道、通过充权赋能保障规划运营的自主化。

中国省域旅游竞争力与旅游网络关注度空间错位研究

正确把握中国省域旅游竞争力与旅游网络关注度的错位关系,对推动区域旅游高质量发展大有裨益。基于新发展理念构建旅游竞争力评价指标体系,采用重力模型、空间错位指数综合考察2011—2020年中国省域旅游竞争力与旅游网络关注度的空间错位特征及影响因素。结果表明:①研究期内中国省域旅游竞争力与旅游网络关注度均呈增长趋势且具有明显的空间分异性,旅游竞争力重心呈集聚分布态势,旅游网络关注度重心则随时间波动变化,大致位于旅游竞争力重心的西南方向;②中国省域旅游竞争力与旅游网络关注度空间错位格局由东至西呈现出正向错位向负向错位逐渐过渡的分布特征,正向高错位区由东部沿海省域向中部省域延伸,负向高错位区主要分布在西部特色旅游地与热门网红城市;③旅游资源禀赋、经济社会发展、政府政策导向、网络环境等多种因素综合作用促成旅游竞争力与旅游网络关注度的空间错位格局。

“双碳”目标下黄河流域绿色技术创新效率评价及影响因素

基于“双碳”目标视角,采用超效率动态网络SBM模型测算黄河流域82市(盟)2011—2021年绿色技术创新的综合效率、科技研发效率及成果转化效率,并利用面板Tobit回归模型检验外部环境因素对三种效率的影响。结果表明:将CO_(2)排放量纳入指标体系后,中下游地区绿色技术创新综合效率得以提升,上游地区效率反而下降;黄河流域绿色技术创新综合效率呈波动上升趋势,科技研发效率起引擎作用;黄河流域绿色技术创新综合效率区域差异明显,成果转化效率差异是综合效率差异的主要来源;经济发展水平、产业结构高级化、人力资本禀赋、对外开放水平、政府支持力度和环境规制强度对三种效率的影响具有区域异质性。建议黄河流域提高绿色技术创新能力,完善创新成果转化平台,推动能源和产业结构升级。

制造业关联网络承压能力研究:基于投入产出表的特征分析与压力测试

数字经济快速发展对制造业关联网络带来诸多不确定性影响,制造业关联网络承压能力研究尤为重要。为应对这一形势,基于2017年、2018年和2020年投入产出表,借助产业集群三角形化方法识别并构建制造业关联网络,结合最大权树法分析制造业关联网络特征,并测试不同程度冲击对制造业关联网络产生的压力。研究发现:①化学产品是制造业关联网络的核心产业,但其核心地位呈下降趋势;②总体而言,制造业对整个关联网络的后向关联效应较强,非制造业的前向关联效应较强;③随着压力源头产业直接关联产业数量的增加,制造业关联网络所承受的压力呈下降趋势;随着压力源头产业与其它产业关联程度的下降,制造业关联网络承受的压力呈下降趋势。研究结论可为制造企业应对承压状态、促进经济高质量发展提供理论依据与实践参考。

中国民营经济高质量发展空间关联网络结构特征及影响因素分析

了解民营经济高质量发展的空间关联网络结构状态及其影响因素,对促进民营经济实现高质量发展具有重要作用。以2014年至2021年我国31个省(自治区、直辖市)民营经济的省际面板数据为样本,基于修正后的引力模型测算民营经济高质量发展空间关联关系,在此基础上运用社会网络分析法(SNA)和二次指派程序(QAP)探究其空间关联网络结构整体、个体、块模特征及其影响因素。结果表明:我国民营经济高质量发展的空间关联网络结构特征相对稳定,并具有一定等级性;省际民营经济高质量发展的空间关联网络可以分为四个板块;城市距离对民营经济高质量发展的空间关联强度产生显著负向作用,科技投入水平差异、贸易经济水平差异和经济发展水平差异对其产生显著正向影响。研究结果可为推动民营经济高质量发展及引导省际民营经济形成高质量发展的关联网络结构提供参考。

协同推进南水北调后续工程和长江经济带高质量发展

推动长江经济带高质量发展,是以习近平同志为核心的党中央作出的重大决策,是关系党和国家事业发展全局的重大战略。南水北调东、中、西三条线均以长江为水源,是跨流域跨区域配置水资源的骨干工程,是国家水网的主骨架和大动脉,在保障国家经济安全、粮食安全、生态安全等方面具有基础性、战略性作用。两者联系紧密,互促共生。文章通过对长江经济带高质量发展内涵的分析,以及在国家水安全保障、长江经济带高质量发展对南水北调高质量发展的具体要求梳理的基础上,对共同推进南水北调和长江经济带高质量发展提出了初步的认识和思考。

基于云计算的软件工程方法在通信网络中的应用与效益

文章探讨了云计算与软件工程方法的结合,以及这种结合在通信网络中的应用和效益。首先,概述了云计算的基本概念和软件工程方法,分析了两者的结合点。其次,深入探讨了基于云计算的软件工程方法如何满足通信网络的软件需求并解决存在的问题,并评估了这种方法带来的效益,包括提高工作效率、降低运营成本,以及提高网络的可靠性和安全性等。最后,总结了软件工程方法的未来发展趋势,并对未来通信网络的发展趋势和预期效益进行了预测。