Abstract:
The research is aimed at developing a prototype of a decision support
information system for managers of a company operating in the real estate
rental industry. The system provides tools for data analysis, the use of
mathematical models and expert knowledge to solve complex problems. The
work analyzes the practical aspects of the design and use of decision support
systems and formulates the requirements for the functionality of the system
being developed. The Python programming language was used for
implementation. The prototype includes machine learning models, expert
systems, user interface and reports. Linear regression, data clustering
density-based spatial clustering of applications with noise (DBSCAN) and
backpropagation methods were implemented to train the classifying
perceptron. The developed tool represents a significant contribution to the
field of decision support, providing unique analysis and forecasting
capabilities in the dynamic real estate rental environment. This prototype is
an innovative solution that promotes effective management and strategic
decision making in complex real estate business scenarios.
