scholarly journals About Rule-Based Systems: Single Database Queries for Decision Making

2020 ◽  
Vol 12 (12) ◽  
pp. 212
Author(s):  
Piotr Artiemjew ◽  
Lada Rudikova ◽  
Oleg Myslivets
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Integrated Circuits ◽  
Future Internet ◽  
Rule Based ◽  
Industry Standard ◽  
Decision Making Processes ◽  
Computational Intelligence Methods ◽  
Minimal Description ◽  
Rule Based Systems

One of the developmental directions of Future Internet technologies is the implementation of artificial intelligence systems for manipulating data and the surrounding world in a more complex way. Rule-based systems, very accessible for people’s decision-making, play an important role in the family of computational intelligence methods. The use of decision-making rules along with decision trees are one of the simplest forms of presenting complex decision-making processes. Decision support systems, according to the cross-industry standard process for data mining (CRISP-DM) framework, require final embedding of the learned model in a given computer infrastructure, integrated circuits, etc. In this work, we deal with the topic concerning placing the learned rule-based model of decision support in the database environment-exactly in the SQL database tables. Our main goal is to place the previously trained model in the database and apply it by means of single queries. In our work we assume that the decision-making rules applied are mutually consistent and additionally the Minimal Description Length (MDL) rule is introduced. We propose a universal solution for any IF THEN rule induction algorithm.

scholarly journals State-of-the-Art Prescriptive Criteria Weight Elicitation

2012 ◽  
Vol 2012 ◽  
pp. 1-24 ◽  
Author(s):  
Mona Riabacke ◽  
Mats Danielson ◽  
Love Ekenberg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Theory ◽  
Decision Analysis ◽  
Analytical Methods ◽  
State Of The Art ◽  
Criteria Weights ◽  
Decision Making Processes ◽  
Method Of Assessment ◽  
Descriptive Theories

Comparatively few of the vast amounts of decision analytical methods suggested have been widely spread in actual practice. Some approaches have nevertheless been more successful in this respect than others. Quantitative decision making has moved from the study of decision theory founded on a single criterion towards decision support for more realistic decision-making situations with multiple, often conflicting, criteria. Furthermore, the identified gap between normative and descriptive theories seems to suggest a shift to more prescriptive approaches. However, when decision analysis applications are used to aid prescriptive decision-making processes, additional demands are put on these applications to adapt to the users and the context. In particular, the issue of weight elicitation is crucial. There are several techniques for deriving criteria weights from preference statements. This is a cognitively demanding task, subject to different biases, and the elicited values can be heavily dependent on the method of assessment. There have been a number of methods suggested for assessing criteria weights, but these methods have properties which impact their applicability in practice. This paper provides a survey of state-of-the-art weight elicitation methods in a prescriptive setting.

A Study of Organizational Narrative Simulation for Decision Support

2013 ◽  
pp. 179-192
Author(s):  
C. L. Yeung ◽  
C. F. Cheung ◽  
W. M. Wang ◽  
E. Tsui
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Pilot Study ◽  
Reference Site ◽  
Lessons Learned ◽  
Implementation Processes ◽  
Organizational Narrative ◽  
Decision Making Processes ◽  
New Challenges ◽  
Narrative Simulation

This paper presents an overview of current decision making approaches. For some approaches abstract information is provided, whereas others require a large amount of labor and time resources to facilitate decision making. However, few address the issues of assisting participants in learning how to make decisions and provide prompt responses to the situations. Harnessing lessons learned from making inappropriate decisions is expensive. To redress this problem, this paper presents a pilot study of the investigation of the psychological behaviors of humans to improve decision making processes with the use of organizational narrative simulation (ONS). By using the ONS method, possible and plausible narrative-based environments can be simulated. Participants can take actions based on their decisions; they can also observe the changes and the consequences. The decisions for handling new challenges generated purposely are validated in a trial that allows prompt responses to the situations. The ONS method is implemented in a selected reference site. The implementation processes, findings, and benefits are presented.

Overview of Decision Support Systems Applied to Construction

2016 ◽  
pp. 77-94
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Markov Decision Processes ◽  
Support Systems ◽  
Decision Processes ◽  
Rule Based ◽  
Markov Decision ◽  
Knowledge Intensive ◽  
The Cost ◽  
Rule Based Systems

The domain of construction is a very knowledge-intensive domain with so many factors involved. This implies undertaking any action requires an understanding of the different factors and how best to combine them to achieve a favourable and optimal outcome. Thus decision-making has been extensively used in the domain of construction. The aim of this chapter is to undertake a review of various decision support systems and to provide insights into their applications in the domain of construction. Specifically, the principle of cost index, sub-work chaining diagram method, linear regression and cost over-runs in time-overrun context (CCOTOV) model and Markov decision processes (MDP), ontology and rule-based systems have been reviewed. Based on the review the Markov decision processes (MDP), ontology and rule-based systems were chosen as the more suitable for the cost control case considered in this study.

Decision Support Systems and Decision-Making Processes

2010 ◽  
pp. 135-143 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Problem ◽  
Upper Management ◽  
Structured Problems ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Computer Based

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.

Managerial Decision Support in the Post-COVID-19 Era

2021 ◽  
pp. 225-241
Author(s):  
Jan Kalina
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Management Practices ◽  
Support Systems ◽  
Management Decision ◽  
Managerial Decision ◽  
Massive Datasets ◽  
New Development ◽  
Decision Making Processes

The COVID-19 pandemic accelerated trends to digitalization and automation, which allow us to acquire massive datasets useful for managerial decision making. The expected increase of available data (including big data) will represent a potential for an increasing deployment of management decision support systems for more general and more complex tasks. Sophisticated decision support systems have been proposed already in the pre-pandemic times either to assist managers in specific decision-making processes or to perform the decision making fully automatically. Decision support systems are presented in this chapter as perspective artificial intelligence tools contributing to a deep transform of everyday management practices. Attention is paid here to their new development in the quickly transforming post-COVID-19 era and to their role under the post-pandemic conditions. As an original contribution, this chapter presents a vision of information-based management, which far exceed the rather limited pre-pandemic visions of evidence-based management focused primarily on critical thinking.

A Study of Organizational Narrative Simulation for Decision Support

2011 ◽  
Vol 2 (3) ◽  
pp. 26-41
Author(s):  
C. L. Yeung ◽  
C. F. Cheung ◽  
W. M. Wang ◽  
E. Tsui
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Pilot Study ◽  
Reference Site ◽  
Lessons Learned ◽  
Implementation Processes ◽  
Organizational Narrative ◽  
Decision Making Processes ◽  
New Challenges ◽  
Narrative Simulation

This paper presents an overview of current decision making approaches. For some approaches abstract information is provided, whereas others require a large amount of labor and time resources to facilitate decision making. However, few address the issues of assisting participants in learning how to make decisions and provide prompt responses to the situations. Harnessing lessons learned from making inappropriate decisions is expensive. To redress this problem, this paper presents a pilot study of the investigation of the psychological behaviors of humans to improve decision making processes with the use of organizational narrative simulation (ONS). By using the ONS method, possible and plausible narrative-based environments can be simulated. Participants can take actions based on their decisions; they can also observe the changes and the consequences. The decisions for handling new challenges generated purposely are validated in a trial that allows prompt responses to the situations. The ONS method is implemented in a selected reference site. The implementation processes, findings, and benefits are presented.

How Groupware Systems Can Change How an Organisation Makes Decisions

2011 ◽  
pp. 426-433
Author(s):  
Frédéric Adam ◽  
Jean-Charles Pomerol ◽  
Patrick Brézillon
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Study Protocol ◽  
Support Systems ◽  
Decision Making Processes ◽  
The Impact

In this article, a newspaper company which has implemented a computerised editorial system is studied in an attempt to understand the impact that groupware systems can have on the decision making processes of an organisation. First, the case study protocol is presented, and the findings of the case are described in detail. Conclusions are then presented which pertain both to this case and to the implementation of decision support systems that have a groupware dimension.

Decision Support Systems and Decision-Making Processes

2010 ◽  
pp. 218-224 ◽  
Author(s):  
Udo Richard Averweg
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Problem ◽  
Upper Management ◽  
Structured Problems ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Computer Based

Decision support systems (DSS) deal with semi-structured problems. Such problems arise when managers in organisations are faced with decisions where some but not all aspects of a task or procedure are known. To solve these problems and use the results for decision-making requires judgement of the manager using the system. Typically such systems include models, data manipulation tools, and the ability to handle uncertainty and risk. These systems involve information and decision technology (Forgionne, 2003). Many organisations are turning to DSS to improve decision-making (Turban, McLean, & Wetherbe, 2004). This is a result of the conventional information systems (IS) not being sufficient to support an organisation’s critical response activities—especially those requiring fast and/or complex decision-making. In general, DSS are a broad category of IS (Power, 2003). A DSS is defined as “an interactive, flexible, and adaptable computer-based information system, specially developed for supporting the solution of a non-structured management problem for improved decision-making. It utilises data, it provides easy user interface, and it allows for the decision maker’s own insights” (Turban, 1995). There is a growing trend to provide managers with IS that can assist them in their most important task—making decisions. All levels of management can benefit from the use of DSS capabilities. The highest level of support is usually for middle and upper management (Sprague & Watson, 1996). The question of how a DSS supports decision-making processes will be described in this article. This article is organised as follows: The background to decisionmaking is introduced. The main focus (of this article) describes the development of the DSS field. Some future trends for the DSS field are then suggested. Thereafter a conclusion is given.

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