KEYWORDS: Neural networks, Databases, Data modeling, Neurons, Machine learning, Data processing, Data mining, Information technology, Document management, Control systems
Currently, computer technologies are actively used in the field of management and organizational decisions. In particular,
automated computer systems based on statistical processing of information are used to monitor the time management of
employees. The purpose of this study is to develop methods for monitoring the time management of employees of the
organization using data mining technologies. The paper examines the capabilities of WorkForce Management (WFM)
systems. Within the framework of modern information technologies, methods of planning the need for labor resources are
considered. The design of a computer application for forecasting orders, including a module containing neural networks,
is described. The analysis and selection of machine learning methods (polynomial regression and multilayer perceptron)
are carried out. The structure of two training data sets is developed and examples of their filling are given. The advantages
and disadvantages of using the selected machine learning methods to predict the number of tasks and employees required
to perform the work are analyzed.
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