scholarly journals Computational approach to synthesis of the multiversion structure of distributed information decision-making support system

2021 ◽  
Vol 2094 (3) ◽  
pp. 032068
Author(s):  
I V Kovalev ◽  
N A Testoyedov ◽  
A A Voroshilova ◽  
D I Kovalev ◽  
D V Borovinskii
Keyword(s):  
Decision Making ◽  
Distributed System ◽  
Support System ◽  
Formal Model ◽  
Technical Condition ◽  
Computational Approach ◽  
Local Information ◽  
Distributed Information ◽  
Complex Control System ◽  
Decision Making Support

Abstract The computational approach to synthesis of the multiversion structure of distributed information decision-making support system is presented. A formal model of the local information system is given. This system is intended to ensure the functioning of a complex control system based on the multiversion approach and consisting of a set of multiversion objects. The problem of distribution of objects by local information subsystems has been solved. For a set of valid queries in a distributed system, the answers for the decision maker are formed sequentially without repeating queries. To take into account certain requirements regarding the structure of a distributed system, it is necessary to formulate these requirements in formalized constraints and introduce them into the mathematical description of the problem. Note that the effectiveness of the targeted use of the system depends both on the results of synthesis (structure and parameters of the system) and on the correct organization of the subsystem for monitoring its technical condition during operation.

scholarly journals Renovation Management Method in Neglected Buildings

2021 ◽  
Vol 13 (2) ◽  
pp. 929
Author(s):  
Beata Nowogońska ◽  
Magdalena Mielczarek
Keyword(s):  
Decision Making ◽  
Technical Condition ◽  
Irreversible Processes ◽  
Management Method ◽  
The Stability ◽  
Motivating Factor ◽  
Decision Making Support

Renovation works to buildings are often not carried out or there are shifts in time, which causes degradation of the building. The article presents an analysis of the consequences of abandoning renovation works. The aim of this article is to present a method of preliminarily planning renovations of a MRUB (Managing Renovation in Un-renovated Buildings). This method of decision-making support is based on the consequences in the case of the omission of renovations. The omission of renovations may lead to a threat to the stability of the building’s structure, threaten the lives of its users, and further damage the building by damaging further elements, or even cause a building disaster. Often, as a result of the abandonment of renovation, usually caused by the lack of the owner, improper manager, or irresponsible owners, these objects are degraded. The consequences of the failure of renovating buildings lead to irreversible processes of destruction. As a result of the research, it was found that it was not only a bad technical condition that was a prerequisite for carrying out the renovation. The consequences of the absence of renovation works, in addition to the technical condition, should be a motivating factor. The problem of the abandonment of renovations is presented using the example of the palace in Drwalewice.

scholarly journals Real-Time AI-Based Informational Decision-Making Support System Utilizing Dynamic Text Sources

2021 ◽  
Vol 11 (13) ◽  
pp. 6237
Author(s):  
Azharul Islam ◽  
KyungHi Chang
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Random Forest ◽  
Support System ◽  
Classification Accuracy ◽  
Short Term Memory ◽  
Learning Algorithm ◽  
Unstructured Data ◽  
Stochastic Gradient Descent ◽  
Decision Making Support

Unstructured data from the internet constitute large sources of information, which need to be formatted in a user-friendly way. This research develops a model that classifies unstructured data from data mining into labeled data, and builds an informational and decision-making support system (DMSS). We often have assortments of information collected by mining data from various sources, where the key challenge is to extract valuable information. We observe substantial classification accuracy enhancement for our datasets with both machine learning and deep learning algorithms. The highest classification accuracy (99% in training, 96% in testing) was achieved from a Covid corpus which is processed by using a long short-term memory (LSTM). Furthermore, we conducted tests on large datasets relevant to the Disaster corpus, with an LSTM classification accuracy of 98%. In addition, random forest (RF), a machine learning algorithm, provides a reasonable 84% accuracy. This research’s main objective is to increase the application’s robustness by integrating intelligence into the developed DMSS, which provides insight into the user’s intent, despite dealing with a noisy dataset. Our designed model selects the random forest and stochastic gradient descent (SGD) algorithms’ F1 score, where the RF method outperforms by improving accuracy by 2% (to 83% from 81%) compared with a conventional method.

A Distributed Scenario-Based Decision Support System for Robust Decision-Making in Complex Situations

2013 ◽  
pp. 213-231
Author(s):  
Tina Comes ◽  
Niek Wijngaards ◽  
Michael Hiete ◽  
Claudine Conrado ◽  
Frank Schultmann
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Emergency Management ◽  
Distributed System ◽  
Support System ◽  
Irrelevant Information ◽  
Informed Decision Making ◽  
Processing Information ◽  
Flexible Adaptation

Decision-making in emergency management is a challenging task as the consequences of decisions are considerable, the threatened systems are complex and information is often uncertain. This paper presents a distributed system facilitating better-informed decision-making in strategic emergency management. The construction of scenarios provides a rationale for collecting, organising, and processing information. The set of scenarios captures the uncertainty of the situation and its developments. The relevance of scenarios is ensured by gearing the scenario construction to assessing alternatives, thus avoiding time-consuming processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to both the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios. The theoretical framework is demonstrated in a distributed decision support system by orchestrating experts into workflows tailored to each specific decision.

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