scholarly journals Intelligent Decision Support System of Emergency Language Based on Fog Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Li Wang
Keyword(s):  
Decision Making ◽  
Fog Computing ◽  
Economic Loss ◽  
Ecological Environment ◽  
Intelligent Decision Support System ◽  
Evaluation Scores ◽  
Intelligent Decision ◽  
Direct Economic Loss ◽  
Index Value ◽  
Intelligent Decision Support

In recent years, various emergencies have frequently occurred worldwide, which has forced relevant service departments to pay more attention to decision-making and emergency management. Since emergency events are characterized by complex environments, unstable events, and time constraints, events usually involve multiple factors and promptly correct errors in the decision-making process. In fact, in many cases, emergency decision-making needs to select an optimal one from multiple alternatives for execution. The fog algorithm decision-making method can solve the problem of optimal solution selection, and it has been widely used in many fields. This article evaluates the emergencies that have occurred in the past 10 years. The evaluation indicators include direct economic loss, indirect reputation loss, ecological environment indicators, and healthy living indicators. The first two are cost-based indicators. The index value of direct economic loss and indirect reputation loss is as small as possible, while the index value of ecological environment index and healthy living index is the larger the better. Among the many selected emergencies, only the index evaluation scores of fires are reliable ( P < 0.01 ), and the evaluation scores of other emergencies belonging to natural disasters are a bit wrong ( P > 0.05 ). The reason for this may be that the direct economic losses caused by natural disasters are not well counted, and the families involved and the environment are too wide. Therefore, the emergency language intelligent decision support system based on fog computing has a good development prospect.

Improving Intelligent Decision Making in Urban Planning

2021 ◽  
Vol 8 (3) ◽  
pp. 40-58
Author(s):  
Abderrazak Khediri ◽  
Mohamed Ridda Laouar ◽  
Sean B. Eom
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Urban Planning ◽  
Agglomerative Clustering ◽  
New Techniques ◽  
Intelligent Decision Support System ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Urban Issues ◽  
Intelligent Decision Support

Generally, decision making in urban planning has progressively become difficult due to the uncertain, convoluted, and multi-criteria nature of urban issues. Even though there has been a growing interest to this domain, traditional decision support systems are no longer able to effectively support the decision process. This paper aims to elaborate an intelligent decision support system (IDSS) that provides relevant assistance to urban planners in urban projects. This research addresses the use of new techniques that contribute to intelligent decision making: machine learning classifiers, naïve Bayes classifier, and agglomerative clustering. Finally, a prototype is being developed to concretize the proposition.

Expert knowledge elicitation for decision-making in home energy retrofits

2014 ◽  
Vol 32 (5) ◽  
pp. 377-395 ◽  
Author(s):  
Daniel Yaw Addai Duah ◽  
Kevin Ford ◽  
Matt Syal
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Expert Knowledge ◽  
Knowledge Elicitation ◽  
Content Type ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
Intelligent Decision Support

Purpose – The purpose of this paper is to develop a knowledge elicitation strategy to elicit and compile home energy retrofit knowledge that can be incorporated into the development of an intelligent decision support system to help increase the uptake of home energy retrofits. Major problems accounting for low adoption rates despite well-established benefits are: lack of information or information in unsuitable and usable format for decision making by homeowners. Despite the important role of expert knowledge in developing such systems, its elicitation has been fraught with challenges. Design/methodology/approach – Using extensive literature review and a Delphi-dominated data collection technique, the relevant knowledge of 19 industry experts, selected based on previously developed determinants of expert knowledge and suitable for decision making was elicited and compiled. Boolean logic was used to model and represent such knowledge for use as an intelligent decision support system. Findings – A combination of comprehensive knowledge elicitor training, Delphi technique, semi-structured interview, and job shadowing is a good elicitation strategy. It encourages experts to describe their knowledge in a natural way, relate to specific problems, and reduces bias. Relevant and consensus-based expert knowledge can be incorporated into the development of an intelligent decision support system. Research limitations/implications – The consensus-based and relevant expert knowledge can assist homeowners with decision making and industry practitioners and academia with corroboration and enhancement of existing knowledge. The strategy contributes to solving the knowledge elicitation challenge. Originality/value – No previous study regarding a knowledge elicitation strategy for developing an intelligent decision support system for the energy retrofit industry exists.

Thermal Power Plant Bidding Strategies IDSS Analysis and Design

2013 ◽  
Vol 717 ◽  
pp. 899-903
Author(s):  
Hong Fei Sun ◽  
Wei Hou ◽  
Yan Yan Wang ◽  
Rui Ling Lu
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Power Plant ◽  
Decision Support System ◽  
Support System ◽  
Bidding Strategies ◽  
Intelligent Decision Support System ◽  
Analysis And Design ◽  
Intelligent Decision ◽  
Intelligent Decision Support

The bidding decision-making of power plant was a complicated system engineering which had high complexity and real-time, so power plant must rely on the support of information technology to complete the bidding. Therefore, how to use all kinds of advanced information technologies had become one of topics which broad power enterprises must face. This paper established a kind of intelligent decision support system (IDSS) which was based on multi-agent intelligent decision support system and combined with the data warehouse, data mining and on-line analysis processing. Compared with the former information management, IDSS had so many advantages in auxiliary support for decision-making. If it was applied to power plant bidding strategies or other semi-structural and unstructured problems in power market, it would provide good auxiliary support for them.

Application of Intelligent Decision Support System in Enterprise Management

2013 ◽  
Vol 709 ◽  
pp. 740-743
Author(s):  
Yong Jie Tan
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Social Economy ◽  
Living Environment ◽  
Enterprise Management ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
Intelligent Decision Support

Decision-making in the process of business operations is a more complex management task and is a core part of enterprise management. With the continuous development of the social economy, the living environment of enterprises is increasingly complex and the competition among enterprises becomes increasingly fierce. Intelligent Decision Support System is a new information technology that can provide information and solutions for enterprise management, help managers quickly process information, reduce their burden of work, and enhance managers efficiency and quality of decision-making.

scholarly journals Situational planning and operational adjustment of the route of the Autonomous robotic underwater vehicle

2019 ◽  
Vol 3 (122) ◽  
pp. 3-11
Author(s):  
Oleksandr Illich Mikhalov ◽  
Oleksandr Afrykanovych Stenin ◽  
Viktor Petrovych Pasko ◽  
Oleksandr Serhiiovych Stenin ◽  
Yurii Opanasovych Tymoshyn
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Optimal Strategies ◽  
Underwater Robot ◽  
Mathematical Apparatus ◽  
Intelligent Decision Support System ◽  
Cargo Delivery ◽  
Intelligent Decision ◽  
Semi Markov Processes ◽  
Intelligent Decision Support

Currently, missions (tasks) for the underwater robot formed using imperative programming methods (both text and graphic), describing in detail the sequence of robot actions that need performed to achieve the desired goal. At the same time, only the operator of the underwater robot, which makes up the mission, for example, the delivery of cargo to the target point, has an idea of the goal itself. Such technology is effective if the robot's mission carried out within a priori scenario. In other cases, it can either not be executed at all, or it can be executed with large violations and a threat to the safety of the device.When assessing the effectiveness of an underwater robot, the degree of its information autonomy, i.e. the ability to act independently in an unknown or insufficiently defined environment, is of fundamental importance. Therefore, the "intellectualization" of the Autonomous control system of the underwater robot is extremely important for the mission in unforeseen circumstances. For this propose to use intelligent decision support system. Two ways to implement optimal decision-making strategies based on the mathematical apparatus of the theory of Markov and semi-Markov processes using the Bellman optimality principle propose. The considered ways of implementation of optimal strategies of decision - making process relate to the strategy for a short finite time of cargo delivery, which is the most common in practice, and for a long interval of cargo delivery relative to the entire task. In addition, the article discusses ways to find optimal strategies when the time of making single decisions is fixed or when the time of translation is implement randomly.Hence, the situational approach to decision-making in the planning of the route ARPA is very relevant and allows not only to assess the possible situation on the route, but also to determine the control solutions for the operational adjustment of the route using the intelligent decision support system (ISPR). The development of models of the routing process based on the representation of the situational model in the form of nodes of the graph, the transitions of which correspond to the control solutions.The paper proposes two ways to implement optimal strategies of decision - making based on the mathematical apparatus of the theory of Markov and semi-Markov processes using the Bellman principle of optimality.

Study on Expert Decicion System for Spraying of Trellis Crop

2013 ◽  
Vol 584 ◽  
pp. 225-230
Author(s):  
Yong Hai Yu ◽  
Rui Hong Zhang ◽  
Bin Cheng ◽  
Hai Liang Ren
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Climatic Conditions ◽  
Target System ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
C4.5 Algorithm ◽  
Decision Making System ◽  
Set Up ◽  
Intelligent Decision Support

Bases on accurate spraying of the trellis crop, the expert decision-making technology was used to provide the decision support. The intelligent decision support system was combined with accurate spraying technology of pesticides. According to the differences of relevant factor of accurate spraying, the expert decision-making system of job parameters of trellis spraying machine was researched and set up. And systematic target, system expansion and system architecture were analyzed. Through C4.5 algorithm, the expert decision-making system was to decide if the trellis crop was sprayed under different climatic conditions, and the decision tree of spraying was constructed. It provided intelligent decision support to accurate spraying.

Sign in / Sign up

Export Citation Format

Share Document