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.

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.

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.

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.

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。

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STEP的AI—ESTATE数据类型转换方法

针对ATML标准中诊断信息描述一致性问题，提出了基于STEP的AI—ESTATE数据类型转换方法。首先介绍了ATML中诊断信息的描述标准，其次分析了AI—ESTATE信息描述的转换方法，然后应用STEP28针对CEM存在的数据类型进行了EXPRESS-XML匹配结构和功能结构一致性研究，最后建立了CEM典型数据类型的XML标准化描述。

An Intelligent Recommendation System for Real Estate Commodity

Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms,whereas consumers often rely on websites to search and compare prices when purchasing real property. In addition to being time consuming, this search processrenders it difficult for agents and consumers to understand the status changes ofobjects. In this study, Python is used to write web crawler and image recognitionprograms to capture object information from the web pages of real estate agents;perform data screening, arranging, and cleaning;compare the text of real estateobject information;as well as integrate and use the convolutional neural networkof a deep learning algorithm to implement image recognition. In this study, dataare acquired from two business-to-consumer real estate agency networks, i.e., theSinyi real estate agent and the Yungching real estate agent, and one consumer-toconsumer real estate agency platform, i.e., the, FiveNineOne real estate agent. Theresults indicate that text mining can reveal the similarities and differences betweenthe objects, list the number of days that the object has been available for sale onthe website, and provide the price fluctuations and fluctuation times during thesales period. In addition, 213,325 object amplification images are used as a database for training using deep learning algorithms, and the maximum image recognition accuracy achieved is 95%. The dynamic recommendation system for realestate objects constructed by combining text mining and image recognition systems enables developers in the real estate industry to understand the differencesbetween their commodities and other businesses in approximately 2 min, as wellas rapidly determine developable objects via comparison results provided by thesystem. Meanwhile, consumers require less time in searching and comparingprices after they have understood the commodity dynamic information, therebyallowing them to use the most efficient approach to purchase real estate objectsof their interest.

Enhancing the Efficiency of the Management of Real Estate Companies through Organizational Structures

The article represents research on ways to make the management of real estate companies more efficient, starting from their structural organization. The organizational structure of the enterprise is a basic component of the general structure of the company and reflects the “anatomy of the enterprise” and the way of its conception, detailing, and implementation directly influence the activities required to achieve the objectives of the enterprise. On closer examination of a series of organizational charts of real estate management companies, the author observed a tendency to use organizational structures that are inefficient. The main objectives of this article are to bring into the practice of real estate management a model of beneficial organizational structure, both for the real estate management companies and for the construction companies that, besides the building activity, also deal with the management of their own real estate, and to emphasize the particular importance of the organizational structure of the company. The appreciation of the organizational structure represents the process of knowledge, understanding, and explanation of the existing situation through a detailed analysis of the factors that influence its condition through: the enterprise development strategy;the type and complexity of services;the size of the enterprise;the quality of human resources;the changes that take place in the external environment of the company, and last but not least, the legal framework and the statutes of the enterprise.

The Applicability of the Maximum Global Utility Method in the Activity of the Real Estate Consulting Service

The real estate sector is vital for ensuring human needs for living and activity. This fact conditioned the formation of a legal, normative and methodological framework specific to real estate, but also the investment attractiveness of the field. Thus, the real estate consultant often solves technical, economic, legal, organizational problems, but the biggest responsibility rests with investment consulting. The applied methodologies, focused on evaluating the efficiency of investments, are not sufficient to propose to the investor a reasoned conclusion regarding the investment priority. In this article, the authors propose a useful tool for real estate consultants in order to reason the decision regarding the investment of funds in commercial real estate for the purpose of renting it out—the Maximum Global Utility (MGU) method. It is proposed to include in the analysis and the way of calculating the indicator “importance level of the real estate” which reflects the criterion of the best use. This indicator ensures the flexibility of the decision depending on the quality characteristics of the real estate.

Trends in the incidence of cryptorchidism and hypospadias of registry-based data in Korea： a comparison between industrialized areas of petrochemical estates and a non-industrialized area

This study aimed to represent the recent trends in the nationwide incidence of cryptorchidism and hypospadias in Korea, and to determine whether there is evidence of spatial heterogeneity in the incidence. The incidence was calculated as the number of newly diagnosed patients （males） during the first 4 years after a live birth in a population, nationally and regionally （a non-industrialized area （Chuncheon） and petrochemical estates （Yeocheon and Ulsan））, between 2000 and 2005. The data （numerator） for new patients were acquired from the National Health Insurance Review Agency, and the data （denominator） for the resident registration population were from the National Statistical Office. Between 2000 and 2005, the national incidence of cryptorchidism and hypospadias had an increased tendency from 5.01 to 17.43 per 10 000 persons and from 1.40 to 3.28 per 10 000 persons, respectively. The incidence of cryptorchidism was significantly higher in Yeocheon （throughout the study period） and in Ulsan （2001, 2002, 2004 and 2005） than the national incidence, whereas the incidence in Chuncheon was significantly lower in 2001 and 2002. It was difficult to compare the rates of hypospadias yearly and regionally because of the small number of cases. In conclusion, the incidence of cryptorchidism has recently increased in Korea. The petrochemical estates, Yeocheon and Ulsan, had a significantly higher incidence of cyptorchidism than the national incidence, which suggests that further study is needed to obtain a more precise estimation of the trends in the incidence of the anomalies and to confirm the association between petrochemicals and the anomalies.

Real estate appraisal system based on GIS and BP neural network

For the inefficiency and inaccuracy of appraisal method of traditional estate appraisal theory, the real estate appraisal system based on GIS and BP neural network was established. The structure of the system was designed which includes appraisal model, trade case, GIS database and query analysis module. With the help of the L-M algorithm in MATLAB software, BP neural network was improved and the trade cases were trained, then the BP neural network which has already been trained was tested. At the same time, the BP neural and GIS were put together to construct the hedonic price estimate model. The C# and ArcGIS9.3 were used to achieve the system in VS2008. City basic geographic data and real estate related information were used as the basic data in practice. The results show that the functions of querying, adding and editing the spatial data and attribute data are achieved and also the efficiency and accuracy of real estate are improved, so that the new method of real estate is provided by the system.

Design of the Blockchain Smart Contract: A Use Case for Real Estate

Blockchain is a fast-disruptive technology becoming a key instrument in share economy. In recent years, Blockchain has received considerable attention from many researchers and government institutions. This paper aims to present the Blockchain and smart contract for a specific domain which is real estate. A detailed design of smart contract is presented and then a use case for renting residential and business buildings is examined.

Real Estate Management via a Decentralized Blockchain Platform

Blockchain technology is one of the key technological breakthroughs of the last decade.It has the ability to revolutionize numerous aspects of society,including financial systems,healthcare,e-government and many others.One such area that is able to reap the benefits of blockchain technology is the real estate industry.Like many other industries,real estate faces major administrative problems such as high transaction fees,a lack of transparency,fraud and the effects of a middleman including undue influence and commissions.Blockchain enables supporting technologies to overcome the obstacles inherent within the real estate investment market.These technologies include smart contracts,immutable record management and time-stamped storage.We utilize these key properties of blockchain technology in our work by proposing a system that has the ability to record real estate transactions in a private blockchain,using smart contracts.The immutability of the blockchain ledger and transactions can provide a safe space for the real estate business.Blockchain technology can also assist the authentication process by hastening background checks.Personal digital keys are provided to parties that are involved in a contract,thus minimizing the risk of fraud.We also discuss the rationale behind the advantages of using a blockchain in this manner,and how we selected the consensus mechanism for our proposed system.