用MRL分析检验出租房屋数据

Rohit Rastogi
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引用次数: 0

摘要

在今天的情况下,我们都被技术所包围。随着世界向技术的快速转变,技术也显示出它的效率和力量,我们必须认识到它的力量。现在世界正在向数字化转变。因此,考虑电子商务以充分利用系统的优势也是很重要的。住房部门是一个重要的领域,必须得到技术领域的支持,以克服许多挑战。因此,有必要带来一个系统,可以指导租户和客户的工作更容易。为了将这个想法带入现实世界,作者的团队提出了一个出租房屋门户系统的想法。这个门户网站是一个web应用程序,它作为一个电子平台来搜索公寓、公寓、物业等,并提供基于科学分析的数据。在这个系统中,业主提供公寓的详细信息,并使用ML(机器学习)技术,计算公寓的价格,客户可以根据自己的需求查看公寓的可用性,并为双方提供利益。由于单位的细节可以在现场找到,所以没有必要向业主解释房子的特点。客户还可以在更短的时间内以非常合理的价格找到想要的房子。因此,租房系统是在网上找房子的一个很好的步骤。本文运用统计技术,根据所提供的特征,提出了预测房屋租金价格的新思路,成为搜索合理价格房产的最佳平台之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Examining Rental House Data With MRL Analysis
In today's scenario, we all are surrounded with technologies. As the world is shifting towards technology with great pace, and technology is also showing its efficiency and strength, we must appreciate its power. Now the world is shifting towards digitalization. So, it's also important to think that ideas should lie towards e-business to get full advantage of the system. The housing sector is one of the important fields which must get the support of the technological domains to overcome many challenges. So, there is a requirement to bring a system that can direct the work of renter and customer easier. To bring this idea into the real world, the author's team has come up with the idea of a rental house portal system. This portal is a web application which acts as an e-platform to search flats, apartments, property, etc., with scientific analysis-based data. In this system, the owner provides the details of flats with its features and using ML (machine learning) technology, the price of flat is calculated and the customer can check the availability of flat according to his/her requirement and to provide benefits to both parties. As the details of the flat are available on site, there is no need to explain the features of the house to the owner. Customers also have the benefits of searching for the desired house in less time and at a very reasonable price. Therefore, the rental house system is a very nice step towards the finding of flats online. The present manuscript has new thoughts of prediction of house rent price according to the features provided using statistical techniques and has come as one of the best platforms to search the property at a reasonable price.
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来源期刊
CiteScore
1.10
自引率
0.00%
发文量
20
期刊介绍: The mission of the International Journal of Cyber Behavior, Psychology and Learning (IJCBPL) is to identify learners’ online behavior based on the theories in human psychology, define online education phenomena as explained by the social and cognitive learning theories and principles, and interpret the complexity of cyber learning. IJCBPL offers a multi-disciplinary approach that incorporates the findings from brain research, biology, psychology, human cognition, developmental theory, sociology, motivation theory, and social behavior. This journal welcomes both quantitative and qualitative studies using experimental design, as well as ethnographic methods to understand the dynamics of cyber learning. Impacting multiple areas of research and practices, including secondary and higher education, professional training, Web-based design and development, media learning, adolescent education, school and community, and social communication, IJCBPL targets school teachers, counselors, researchers, and online designers.
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