Development of a module for environmental monitoring of the living condition of landscaping facilities using neural networks

Abstract

At the moment, one of the shortcomings in the management of territories where landscaping objects grow is the lack of up-to-date and reliable data, their real assessment. The reason for this lies in poor-quality accounting or in the absence of software tools for accounting for landscaping objects. In modern conditions, the availability of software tools that solve such problems most often using neural network methodologies are finding new successful applications in the practice of management and decision-making. Not only in the financial and trade spheres, but also in the field of ecology. The development of systems based on neural networks and machine learning is a necessary means of improving the efficiency of all business processes and the timeliness of management decisions. Improving the efficiency of management activities through the introduction of neural networks is becoming one of the main directions of improving the company's activities. The problem of improving the efficiency of monitoring of landscaping facilities is solved by developing and implementing a software module using forecasting methods. Such a module will make it possible to predict the vital state of landscaping facilities and promptly identify problems of facilities and make timely management decisions in the form of proposed recommendations for their elimination based on the knowledge base of experts.