An Effective Prediction Method for Supporting Decision Making in Real Estate Area Selection

Real estate has been a dominant industry in many countries. One problem for real estate companies is determining the most valuable area before starting a new project. Previous studies on this issue mainly focused on market needs and economic prospects, ignoring the impact of natural disasters. We observe that natural disasters are important for real estate area selection because they will introduce considerable losses to real estate enterprises. Following this observation, we first develop a self-defined new indicator named Average Loss Ratio to predict the losses caused by natural disasters in an area. Then, we adopt the existing ARIMA model to predict the Average Loss Ratio of an area. After that, we propose to integrate the TOPSIS model and the Grey Prediction Model to rank the recommendation levels for candidate areas, thereby assisting real estate companies in their decision-making process. We conduct experiments on real datasets to validate our proposal, and the results suggest the effectiveness of the proposed method.

Empirical evidence on the ownership and liquidity of real estate tokens

To better understand the potential and limitations of the tokenization of real asset mar-kets,empirical studies need to examine this radically new organization of financial mar-kets.In our study,we examine the financial and economic consequences of tokenizing 58 residential rental properties in the US,particularly those in Detroit.Tokenization aims at fragmented ownership.We found that the residential properties examined have 254 owners on average.Investors with a greater than USD 5,000 investment in real estate tokens,diversify their real estate ownership across properties within and across the cities.Property ownership changes about once yearly,with more changes for proper-ties on decentralized exchanges.We report that real estate token prices move accord-ing to the house price index;hence,investing in real estate tokens provides economic exposure to residential house prices.

Research on the intelligent supervision and operation platform of railway real estate

Railway real estate is the fundamental element of railway transportation production and operation.Effective management and rational utilization of railway real estate is essential for railway asset operation.Based on the investigation of the requirements of railway real estate management and operation,combined with Beidou positioning,GIS(Geographic Information System),multi-source data fusion and other cutting-edge technologies,this paper puts forward the multi-dimensional dynamic statistical method of real estate information,the identification method of railway land occupation and the comprehensive evaluation method of real estate development and utilization potential,and build the railway real estate supervision and operation platform,design the function of the platform,so as to provide intelligent solutions for the railway real estate operation.

Architecting the Metaverse: Blockchain and the Financial and Legal Regulatory Challenges of Virtual Real Estate

There has been disagreement over the value of purchasing space in the metaverse, but many businesses including Nike, The Wendy’s Company, and McDonald’s have jumped in headfirst. While the metaverse land rush has been called an “illusion” given underdeveloped infrastructure, including inadequate software and servers, and the potential opportunities for economic and legal abuse, the “real estate of the future” shows no signs of slowing. While the current virtual space of the metaverse is worth $6.30 billion, that is expected to grow to $84.09 billion by the end of 2028. But the long-term legal and regulatory considerations of capitalizing on the investment, as well as the manner in which blockchain technology can secure users’ data and digital assets, has yet to be properly investigated. With the metaverse still in a conceptual phase, building a new 3D social environment capable of digital transactions will represent most of the initial investment in time in human capital. Digital twin technologies, already well-established in industry, will be ported to support the need to architect and furnish the new digital world. The return on and viability of investing in the “real estate of the future” raises questions fundamental to the success or failure of the enterprise. As such this paper proposes a novel framing of the issue and looks at the intersection where finance, technology, and law are converging to prevent another Dot-com bubble of the late 1990s in metaverse-based virtual real estate transactions. Furthermore, the paper will argue that these domains are technologically feasible, but the main challenges for commercial users remain in the legal and regulatory arenas. As has been the case with the emergence of online commerce, a legal assessment of the metaverse indicates that courts will look to traditional and established legal principles when addressing issues until the enactment of federal and/or state statutes and accompanying regulations. Lastly, whereas traditional regulation of real estate would involve property law, the current legal framing of ownership of metaverse assets is governed by contract law.

Prioritizing real estate enterprises based on credit risk assessment:an integrated multi‑criteria group decision support framework

Credit risk assessment involves conducting a fair review and evaluation of an assessed subject’s solvency and creditworthiness.In the context of real estate enterprises,credit risk assessment provides a basis for banks and other financial institutions to choose suitable investment objects.Additionally,it encourages real estate enterprises to abide by market norms and provide reliable information for the standardized management of the real estate industry.However,Chinese real estate companies are hesitant to disclose their actual operating data due to privacy concerns,making subjective evalu-ation approaches inevitable,occupying important roles in accomplishing Chinese real estate enterprise credit risk assessment tasks.To improve the normative and reliability of credit risk assessment for Chinese real estate enterprises,this study proposes an integrated multi-criteria group decision-making approach.First,a credit risk assessment index for Chinese real estate enterprises is established.Then,the proposed framework combines proportional hesitant fuzzy linguistic term sets and preference ranking organization method for enrichment evaluation II methods.This approach is suitable for processing large amounts of data with high uncertainty,which is often the case in credit risk assessment tasks of Chinese real estate enterprises involving massive subjec-tive evaluation information.Finally,the proposed model is validated through a case study accompanied by sensitivity and comparative analyses to verify its rationality and feasibility.This study contributes to the research on credit assessment for Chinese real estate enterprises and provides a revised paradigm for real estate enterprise credit risk assessment.

Assessment of Compliance to Building Energy Efficiency Strategies in the Development of Housing Estates in FCC, Abuja Nigeria

Compliance to local energy efficiency strategies can significantly reduce energy consumption in buildings and promote sustainability. However, Nigeria Building Energy Efficiency Code (BEEC) seems to be just paper work without enforcement or compliance. Assessment of Compliance to Green Building Energy Efficiency Strategies in the Development of Housing Estates in FCC, Abuja Nigeria was carried out. The compliance of estate buildings to BEEC in the study area was assessed;and the aspects of the building energy efficiency strategies with more compliance were determined. Data were mainly from primary sources such as questionnaire survey, interview with key informants and observation. The study population included all estate developers and building construction professionals. Data were gathered from one hundred and fifty (150) building professionals through questionnaire administration. Data collected were analysed using Z score and ANOVA and presented in tables. Results show that only 18% of respondents agreed that building complied with BEEC, and the Z score for positive affirmation is below average score. There is a significant difference in the integration of different energy efficient management strategies in the estates’ construction at 95% confidence level. The integration of measures such as window to wall ratio and window shading’ were significantly higher than other BEEC strategies such as roof insulation and minimal air condition unit (≤EER/COP of 2.8). Thus, the development of estates in FCC Abuja did not achieve energy efficiency.

A Concept about Guide on Hazards for the Real Estate Business-An Example from Bulgaria

The paper is a part of wider investigation related to the application of basic sciences to the sustainable development of society.It deals with the presentation of knowledge to the real estate(fast growing business)about the local natural and man-made hazards in the near vicinity of any structure(inhabitant,recreation area,land,etc.)and their influence to the social safety and human comfort of life.The structure,necessary information and knowledge base for visible or hidden hazards about a guide for the real estate business is included.An example of application the knowledge about seismic hazard and related phenomena simplified to be more available to the non-specialists(such as real estate agents and companies)targeted to Sofia(the largest urban center and capital of Bulgaria)can attract and improve the learning abilities of the real estate for the society’s sake.

Examining the Impact Factors and Strategies to Mitigate Economic Fluctuation in the Real Estate Sector

With the continuous growth of the economy and the rapid pace of urbanization,the real estate sector has assumed an increasingly substantial role within the national economy.Ensuring the stable and sustainable development of the real estate sector to maximize its societal and economic contributions has become a pressing issue.China,presently engaged in an extensive urbanization drive,places real estate development and sales as pivotal components in the broader real estate industry,significantly impacting the overall functionality of the real estate market.Real estate,being a comprehensive system encompassing land,housing,infrastructure,and other key elements,exerts a profound influence on people’s basic needs such as shelter,sustenance,and daily living.Its evolution directly shapes the trajectory of the national economy and social stability.Therefore,to foster the consistent and robust growth of China’s real estate economy,it is necessary to implement effective measures that entail a systematic and thorough analysis of the factors responsible for the fluctuations in China’s real estate economy.

A Review of Domestic and Foreign Research on Real Estate Financial Management

With the tightening of house purchase policies in recent years, the introduction of financial and land restriction policies, as well as the impact of the COVID-19 pandemic, real estate bombshells are common. Real estate is in the critical stage of transformation and upgrading, and industrial development is facing dire challenges and pressure for survival. As an important part of enterprise management, financial management is directly related to the success or failure of enterprise development. Facing the financial risks emerging in the financial management of the real estate industry at this stage, this review begins from financial management personnel training, investment calculation management, budget management, and asset management in the effort of optimizing the real estate financial management operating mechanism under the new situation and ensuring the healthy and stable development of real estate enterprises, while maintaining core competitiveness.

Does China's digital economy contribute to low-carbon transition?

The digital economy,as a new emerging economic form,has become an important power for realizing Chinese-style modernization and promoting green development in China.This paper measures the digital economy and low-carbon transition index based on the data of 30 provinces in China from 2013 to 2020 and analyzes the mechanism and path of the digital economy affecting low-carbon transition using the fixed effect panel data model and the threshold effect model.It is found that,(1)The digital economy and low-carbon transition in China are various in different regions,with characteristics of being unbalanced and insufficient.(2)The digital economy significantly promotes low-carbon transition,with the greatest influence in the Central region,followed by the Eastern region and the Western region.Under different dimensions,the development of informatization and digital transactions promote low-carbon transition,but the development of the internet plays an inhibiting role.(3)The higher the degree of urbanization and environmental regulation,the greater the influence of the digital economy on low-carbon transition.

Effect of ZrC Modified Graphite on Structure and Properties of Low-carbon Al_(2)O_(3)-C Refractories

To address the issues of reduced performance and shortened lifespan during the low-carbonizating process of Al_(2)O_(3)-C refractories,nano-crystalline ZrC modified graphite was prepared using Zr powder and flake graphite as raw materials,with NaCl and NaF mixed salt serving as the medium.The flake graphite was gradually replaced by ZrC modified graphite in the preparation of Al_(2)O_(3)-C refractories,and its impact on the material’s structure and properties was investigated.The results indicate that,compared to samples with only flake graphite,the introduction of 1 mass%to 5 mass%nano-crystalline ZrC modified graphite can significantly enhance the mechanical performance of low-carbon Al_(2)O_(3)-C refractories.When 5 mass%ZrC modified graphite is added,the mechanical properties of the samples are optimal,with the cold modulus of rupture and elastic modulus reaching 22.5 MPa and 65.0 GPa,respectively.

Performance Evaluation of Low-Carbon and Clean Transformation of China’s Coal Economy

In China,the oversupply of coal occurred in 2009,and from that year onwards,China’s coal economy began a low-carbon and clean transformation.Evaluating transformation performance is the research goal of this paper.The data collection for this paper includes data on deep processing of Chinese coal products from 2009 to 2020,as well as data on asset structure evolution and financial performance of 34 listed companies in the Chinese coal mining.Entropy value method is used to calculate the entropy value of low-carbon transformation,and the regression analysis is used to study the performance of cleaner transformation,the conclusion is as follows:(1)From 2009 to 2020,in China’s total energy consumption,coal consumption accounted for 71.6%in 2009 and 56.8%in 2020,the goals set by the state have been achieved.(2)The national goal of reducing the proportion of coal consumption and reducing carbon emissions has forced the transformation of deep processing of coal products.The transformation of coal enterprises towards low-carbon and clean production has achieved remarkable results.(3)From 2009 to 2020,the non coal industry income of 34 listed companies in China’s coal mining industry increased by 8.21%annually.At the same time,the asset structure was adjusted,and nearly 80%of the asset structure evolution showed an orderly development trend.(4)The regression analysis results show that the entropy value of coal deep processing products and the entropy value of asset structure adjustment are significantly related to transformation performance.The paper proposes to summarize the successful experience of China’s coal energy economic transformation,lay a foundation for achieving the carbon peak and carbon neutral goals in the future,further increase the intensity of coal deep processing,increase the proportion of clean energy in total energy consumption,and strive to control asset operation towards the goal of increasing the proportion of non coal industry income.

A Mechanism for Digital Finance to Drive Green and Low-Carbon Development

Given the global focus on green and low-carbon development and the increasing prominence of digital finance,it is particularly important to explore how to leverage digital finance to achieve these environmental goals.This study,through mechanism analysis,deeply examines how China’s digital finance promotes green and low-carbon development and elucidates the positive interaction between digital finance and the green industry.The study found that digital finance,through more flexible and efficient financial functions,alters the cost structure of carbon emissions,and reduces the risks and costs of green investments,thereby creating a cooperative green mechanism benefiting all parties,and guiding social groups toward a green and low-carbon transformation.Additionally,the rapid development of digital finance has strengthened the implementation of environmental protection policies,effectively promoted the expansion of the environmental protection industry,and established the green ethos as a mainstream concept in financial development.This study aims to provide reference perspectives and suggestions,assist policymakers in promoting the green and lowcarbon development of digital finance,and offer insights into the integrated development of digital finance and the green environmental protection industry.

基于AI-ESTATE的远程故障诊断系统

基于某电子设备的自动测试系统,参照IEEE的AI-ESTATE标准建立了一个远程故障诊断系统;在该远程故障诊断系统中,封装了不同的故障诊断模型和人工智能算法;诊断测试信息用XML语言描述,诊断推理机用DCOM组件实现,从而使诊断知识与诊断推理机分离,便于诊断知识的共享和诊断推理机的移植;为了优化测试序列,采用了最大信息熵故障诊断策略;另外还详细介绍了诊断推理机服务的定义和DCOM组件的具体实现方法;该诊断系统具有跨平台和面向网络服务的特点。

基于AI-ESTATE的开放式故障诊断系统体系结构研究

论文分析了开放式故障诊断系统构建的必要性,提出了构建基于AI-ESTATE的开放式故障诊断系统体系结构;"4+1"多视图体系结构模型从不同的视角描述系统,针对开放式故障诊断系统的需求分析了其组织视图、功能视图、信息视图和过程视图,并建立了各视图的结构图,从而全面描述了基于AI-ESTATE开放式故障诊断系统的基本组成、功能、测试与诊断信息流和动态运行模式,体现了诊断系统的模块化、可移植、互操作,为系统的具体开发和应用提供了方法;该方法已用于相关系统的开发,结果表明该体系结构能够实现诊断信息的共享和诊断模型的可移植性。

基于AI-ESTATE的二叉树诊断信息模型研究

采用综合诊断开放式体系结构实现信息的互换和重用,解决了装备诊断维护领域存在的诊断效率低和诊断资源费用高的问题;为了实现诊断知识的互换,AI-ESTATE对广义测试环境下的诊断知识进行了标准化描述,从而保证诊断知识和数据的可移植、可重用及互操作;然而AI-ESTATE描述的诊断模型还有待增加,二叉树是一种传统的应用较广的诊断方法,如何进行二叉树诊断信息模型的建立则具有重要的工程意义;论文首先分析了综合诊断和AI-ESTATE的对诊断信息的要求;其次研究二叉树诊断模型的关键要素以及各个要素之间的约束关系;然后建立了基于XML Schema的二叉树诊断信息模型标准化描述;最后运用导弹在位诊断模型验证了该信息模型的有效性。

面向远程诊断的AI-ESTATE智能诊断系统研究动态

通过封装服务、规范标准服务,AI—EATATE为诊断系统的客户端和应用对象的扩展、测试与诊断的分离提供了条件,使其更适合远程控制的诊断系统的构建;分析了武器装备远程故障诊断对知识重用与共享、软件互操作的需求,提出了面向远程诊断的AI-ESTTAE智能诊断系统构建的方法;研究了AI-ESTATE智能诊断系统的基本结构和框架,讨论了AI-ESTATE在发展过程中其服务的变化对开放、远程智能诊断系统构建的影响;最新的AI-ESTATE标准规范的服务更加强了对诊断过程的控制和效果评估,论文采用状态图的方式分析了最新的AI-ESTTAE服务在远程故障诊断过程的作用,为符合AI-ESTATE标准的远程故障诊断系统的开发提供了方法。

基于Schematron的AI-ESTATE约束的标准化描述

针对ATS中AI-ESTATE诊断信息描述的一致性问题,提出了基于Schematron的AI-ESTATE约束的标准化描述方法。首先介绍了开放式ATS中诊断信息描述的要求,其次分析了目前Express语言约束的XML表示方法,然后研究了Schematron的约束表示原理和AI-ESTATE实体约束的特征,最后完成了AI-ESTATE约束的Schematron描述。实例验证了该方法的有效性。

面向服务的AI-ESTATE故障诊断系统建模

测试和诊断的融合可以提高武器系统的维护效率,但是随着武器装备的升级改造就带来了原有的诊断知识难共享、诊断推理软件难以互操作、难重用,诊断功能难扩展的问题;AI-ESTATE标准规范了诊断知识和数据的标准化描述和诊断推理机的服务接口,为知识互换和软件可移植提供了条件;论文研究了面向服务的AI-ESTATE开放式故障诊断系统的体系结构和信息传递模式,分析了推理机模型管理服务和互操作服务;然后运用静态诊断模型服务关系图和UML时序图分析了AI-ESTATE服务在诊断模型编辑、索引等功能实现中的交换流程,运用动态诊断模型的UML时序图分析了AI-ESTATE互操作服务在故障诊断系统运行中推理机与其它组件的动态交互过程,为开放式AI-ESTATE智能诊断系统的开发奠定了基础。

基于AI-ESTATE贝叶斯诊断的软件架构设计

为了提高水中兵器智能化故障诊断水平,实现诊断知识的可互换性和可移植性,设计了一种基于AI-ESTATE贝叶斯故障诊断的软件架构。简要分析了全测试环境人工智能交换与服务(AI-ESTATE)标准及其体系结构,并结合最新的贝叶斯网络技术,提出了相关实体的诊断模型标准化信息模型。最后在AI-ESTATE的架构概念和诊断系统的层次框架结构的基础上,设计了一种基于AI-ESTATE贝叶斯故障诊断技术的软件架构,同时给出了其实验验证的软件流程图。该软件架构的设计能够为电子装备故障诊断系统的软件开发提供一种新的解决方案。