
Decision tree as a tool for implementing a scenario approach for multi-level predictive models
Author(s) -
Альфира Менлигуловна Кумратова,
Elmira Popova,
Vitaly V. Aleshchenko,
A.A. Bykov,
A K Bashieva
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/839/3/032050
Subject(s) - computer science , tourism , decision tree , operations research , decision support system , task (project management) , process (computing) , decision analysis , data mining , economics , engineering , mathematics , statistics , management , operating system , political science , law
The paper presents a decision-making method for a quantitative income estimation depending on the intensity of the future tourist flow, as a complex indicator reflecting the level of the tourist market in a region or in a separate object (a hotel complex, sanatorium, tourist base, etc.). The authors proposed to use a three-level economic and mathematical model as a practical implementation of the hotel complex room stock management process. Each its level corresponds to a specific task. At the first level it is a pre-forecast study, substantiation and selection of forecasting models. At the second it is a forecast model and the quantitative value of the predicted indicator. At the third level it is a model tohelp a decision maker (DM) with decision making, i.e., a decision tree is applied as a tool. Thus, the authors present a complete system of models and methods of decision support. The results of pre-forecast analysis, development of predictive models, building, adaptation and implementation of top-level economic and mathematical models will help decision makers to make effective management decisions. There by the maneuver material resources, choose sales technologies and search for economic solutions, including in tourism recreational production activities.