Simulation in Intelligent Management of Pedestrian Flows at Heritage Sites

2016 ◽  
Author(s):  
Vitaly Bolshakov ◽  
Galina Merkuryeva
Keyword(s):  
Heritage Sites ◽  
Intelligent Management

Intelligent management systems in operations: a review

1998 ◽  
Vol 49 (7) ◽  
pp. 682-699 ◽  
Author(s):  
N C Proudlove ◽  
S Vaderá ◽  
K A H Kobbacy
Keyword(s):  
Management Systems ◽  
Intelligent Management

The Reconstruction Project of Illumination Devices at the Krasnoselskaya Station of the Moscow Metro

2019 ◽  
pp. 59-66
Author(s):  
Ksenia I. Nechaeva
Keyword(s):  
Cultural Heritage ◽  
Historical Analysis ◽  
Metro Station ◽  
Heritage Sites ◽  
Passenger Transportation ◽  
Fluorescent Lamps ◽  
Current State ◽  
Heritage Site ◽  
Lighting Environment ◽  
Incandescent Lamps

The current state of the Moscow Metro station of the first priority that became operational in 1935 does not allow it to be called a cultural heritage site. This is due to the fact that lighting modernisation carried out by the Moscow Metro was based on fluorescent lamps. Such lamps are more energy efficient compared to incandescent lamps, which were used in original lighting devices specified in the Station Lighting Project developed by architects and designers. However, they significantly changed the station appearance, transforming the originally designed station with entire well visible architectural tectonics?1 from the standpoint of lighting into a simple, flat, unremarkable, and little loaded station of the Moscow Metro./br> This paper describes a method of lighting reconstruction at Krasnoselskaya station by means of original lighting devices that meet modern standards and requirements for cultural heritage sites. The historical analysis on the development of the station lighting environment was conducted during its operation in order to understand what kind of station was conceived by its architects, what changes occurred with its lighting over time, and how it influenced the station appearance and safety of passenger transportation.

Review of classification studies for machine learning in the development of intelligent management decision support systems

2020 ◽  
Vol 89 ◽  
pp. 20-29
Author(s):  
Sh. K. Kadiev ◽  
◽  
R. Sh. Khabibulin ◽  
P. P. Godlevskiy ◽  
V. L. Semikov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Support ◽  
Mathematical Models ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Decision ◽  
Classification Methods ◽  
Advantages And Disadvantages ◽  
Intelligent Management ◽  
Management Decision Support

Introduction. An overview of research in the field of classification as a method of machine learning is given. Articles containing mathematical models and algorithms for classification were selected. The use of classification in intelligent management decision support systems in various subject areas is also relevant. Goal and objectives. The purpose of the study is to analyze papers on the classification as a machine learning method. To achieve the objective, it is necessary to solve the following tasks: 1) to identify the most used classification methods in machine learning; 2) to highlight the advantages and disadvantages of each of the selected methods; 3) to analyze the possibility of using classification methods in intelligent systems to support management decisions to solve issues of forecasting, prevention and elimination of emergencies. Methods. To obtain the results, general scientific and special methods of scientific knowledge were used - analysis, synthesis, generalization, as well as the classification method. Results and discussion thereof. According to the results of the analysis, studies with a mathematical formulation and the availability of software developments were identified. The issues of classification in the implementation of machine learning in the development of intelligent decision support systems are considered. Conclusion. The analysis revealed that enough algorithms were used to perform the classification while sorting the acquired knowledge within the subject area. The implementation of an accurate classification is one of the fundamental problems in the development of management decision support systems, including for fire and emergency prevention and response. Timely and effective decision by officials of operational shifts for the disaster management is also relevant. Key words: decision support, analysis, classification, machine learning, algorithm, mathematical models.

Food, Museums, and Cultural Heritage Sites

2019 ◽  
Vol 49 (3) ◽  
pp. 372-381
Author(s):  
Tanfer Emin Tunc
Keyword(s):  
Cultural Heritage ◽  
Heritage Sites

Does historical nostalgia predict tourists' delight and their destination loyalty intention for the world cultural heritage site of Mahabalipuram, India?

2020 ◽  
Author(s):  
Anil Verma ◽  
G. Rajendran
Keyword(s):  
Cultural Heritage ◽  
Structural Equation ◽  
Destination Loyalty ◽  
Heritage Sites ◽  
Heritage Site ◽  
Loyalty Intention ◽  
Tourism Studies ◽  
The World ◽  
World Cultural Heritage ◽  
The Impact

Delighting consumers has been one of the most important goals for marketing stakeholders but the effect of historical nostalgia on tourists delight at the world cultural heritage sites has rarely been examined. This study examines the impact of historical nostalgia on the heritage tourists' delight, their satisfaction and destination loyalty intention. The survey for the study was conducted at the world cultural heritage site of Mahabalipuram, India. The hypotheses were tested through the structural equation modelling technique. The results indicated positive and significant effect of historical nostalgia on tourists' delight, satisfaction and destination loyalty intention. The study makes contribution to the tourism studies by examining the role of historical nostalgia in delighting the tourists at the cultural heritage sites and instructs the managers to evoke such experiences to keep the heritage tourists delighted and thereby enhance their loyalty.

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