A proactive decision support method based on deep reinforcement learning and state partition

2018 ◽  
Vol 143 ◽  
pp. 248-258 ◽  
Author(s):  
Yongheng Wang ◽  
Shaofeng Geng ◽  
Hui Gao
Keyword(s):  
Reinforcement Learning ◽  
Decision Support ◽  
Decision Support Method

Decision Support System Based on Fuzzy Logic for Assessment of Expected Corporate Income Performance

2021 ◽  
pp. 2150009
Author(s):  
Arthur Yosef ◽  
Eli Shnaider ◽  
Rimona Palas ◽  
Amos Baranes
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Operating Income ◽  
Explanatory Variables ◽  
Section Model ◽  
Evaluation Mechanism ◽  
One Year ◽  
High Degree ◽  
Decision Support Method ◽  
Very High

This study presents a decision-support method to estimate the next year performance of corporate Operating Income Margin (OIM). It is based on a unique combination of cross-section model and the rules-based evaluation mechanism. The estimate is done in terms of broad categories, and not precise numerical values. The model is constructed as follows: its dependent variable (OIM) is one year ahead vs. the corresponding explanatory variables. This structure of the model allows us to view explanatory variables as reflecting financial potential of corporations. The evaluation component consists of a set of rules designed to identify the companies whose “potential” clearly points to an opportunity to invest. For the method presented here to succeed, it is necessary to utilize a highly reliable modeling method, even if it is “Fuzzy”. We apply Soft Regression (SR), which is a Soft Computing modeling tool based on Fuzzy Logic, and utilize all available proxy variables by creating intervals of values. Advantages of utilizing SR, and the intervals’-based modeling are extensively discussed. Modeling results for five consecutive years are consistent and stable, thus indicating high degree of reliability. Testing indicates very high success rate for the stock market related domain, the lowest being 87.9%.

scholarly journals A decision support method for evaluating database designs

2012 ◽  
Vol 9 (1) ◽  
pp. 81-106 ◽  
Author(s):  
Erki Eessaar ◽  
Marek Soobik
Keyword(s):  
Decision Support ◽  
Data Model ◽  
Processing System ◽  
Transaction Processing ◽  
Database Management System ◽  
Pairwise Comparisons ◽  
Analytic Hierarchy ◽  
Hierarchy Process ◽  
Decision Support Method

It is possible to produce different database designs based on the same set of requirements to a database. In this paper, we present a decision support method for comparing different database designs and for selecting one of them as the best design. Each data model is an abstract language that can be used to create many different databases. The proposed method is flexible in the sense that it can be used in case of different data models, criteria, and designs. The method is based on the Analytic Hierarchy Process and uses pairwise comparisons. We also present a case study about comparing four designs of SQL databases in case of PostgreSQL? database management system. The results depend on the context where the designs will be used. Hence, we evaluate the designs in case of two different contexts - management of measurements data and an online transaction processing system.

scholarly journals Intelligent decision support method in a typical situation

2021 ◽  
Vol 11 (1) ◽  
pp. 126-136
Author(s):  
V.V. Antonov ◽  
◽  
K.A. Konev
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Base ◽  
Business Process ◽  
Support System ◽  
System Integration ◽  
General Structure ◽  
Typical Situation ◽  
Ontological Model ◽  
Decision Support Method

The article discusses a decision support method using a knowledge base. The relevance of the study of issues related to decision-making in typical situations is shown. In order to increase the effectiveness of management activities, the is-sues of system integration of the regulatory framework, ontological model and knowledge base of the intelligent sub-system of decision support within the framework of the business process are considered. In support of the proposed method, a model has been formed for replenishing the knowledge base both at the structural and analytical levels, which demonstrates the connection between the most important elements of the system: the ontological model, the knowledge base and the normative subsystem. An example of using the proposed scheme is shown. To demonstrate the model of functioning of the decision support system, an algorithm for replenishing the knowledge base is proposed and described. As a conceptual basis for the formal description of the model, operations for working with knowledge are described in the set-theoretic aspect. The principles of adaptation of the ontological model as an information object for linking with the knowledge base are considered. The conceptual diagram of the general structure of the ontological model for making decisions within the framework of the business process as a set of interrelated concepts is proposed and demonstrated. An information model of a specialized database has been developed and presented, serving as a technical basis for building a knowledge base of a decision support system in a typical situation, its main structural el-ements, the principles of their interrelation and an approach to ensuring the consistency of its internal structure are de-scribed.

Toward a Decision Support System for Regulation in an Urban Transport Network

2018 ◽  
Vol 9 (2) ◽  
pp. 1-17
Author(s):  
Khadidja Yachba ◽  
Zakaria Bendaoud ◽  
Karim Bouamrane
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Urban Transport ◽  
Transport Network ◽  
Formal Modeling ◽  
Proposed Model ◽  
Available Information ◽  
Decision Support Method ◽  
Multicriteria Decision Support

In this article, a solution to the problem of perturbation in the urban transport network has been proposed. This solution is based on the multicriteria decision support method, which is an efficient way of identifying appropriate solutions to different perturbations situations. The proposed model should provide synthesis, evaluation and updating of available information in order to facilitate the task of the network monitoring operator. To achieve this objective, the authors propose formal modeling of the perturbation concept through an effective and above all significant decision support system exploiting the diversity of the criteria as well as the decision maker's subjectivity. This modeling makes it possible to capitalize the knowledge available within a checkpoint and to monitor the process. The authors show how, from the information available on the network, the modeling of the process represented by a perturbation makes it possible to enrich the possibilities of evaluation of the state of the network.

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