Integration of Analytical Tools to Obtain Reliable Production Forecasts for Quick Decision-Making

2017 ◽  
Author(s):  
Gisela F. Villarroel ◽  
Dante E. Crosta ◽  
Cecilia Romero
Keyword(s):  
Decision Making ◽  
Analytical Tools

Spatially Enabled Pipeline Route Optimization Model

2004 ◽  
Author(s):  
S. Raza Wasi ◽  
J. Darren Bender
Keyword(s):  
Decision Making ◽  
Optimization Problem ◽  
Environmental Design ◽  
Route Optimization ◽  
Design Criteria ◽  
Least Cost Path ◽  
Ahp Model ◽  
Spatial Decision Making ◽  
Pipeline Route ◽  
Analytical Tools

An interesting, potentially useful, and fully replicable application of a spatially enabled decision model is presented for pipeline route optimization. This paper models the pipeline route optimization problem as a function of engineering and environmental design criteria. The engineering requirements mostly deal with capital, operational and maintenance costs, whereas environmental considerations ensure preservation of nature, natural resources and social integration. Typically, pipelines are routed in straight lines, to the extent possible, to minimize the capital construction costs. In contrast, longer pipelines and relatively higher costs may occur when environmental and social considerations are part of the design criteria. Similarly, much longer pipelines are less attractive in terms of capital costs and the environmental hazard associated with longer construction area. The pipeline route optimization problem is potentially a complex decision that is most often undertaken in an unstructured, qualitative fashion based on human experience and judgement. However, quantitative methods such as spatial analytical techniques, particularly the least-cost path algorithms, have greatly facilitated automation of the pipeline routing process. In the past several interesting studies have been conducted using quantitative spatial analytical tools for finding the best pipeline route or using non-spatial decision making tools to evaluate several alternates derived through conventional route reconnaissance methods. Most of these studies (that the authors are familiar with) have concentrated on integrating multiple sources of spatial data and performing quantitative least-cost path analysis or have attempted to make use of non-spatial decision making tools to select the best route. In this paper, the authors present a new framework that incorporates quantitative spatial analytical tools with an Analytical Hierarchical Process (AHP) model to provide a loosely integrated but efficient spatial Decision Support System (DSS). Specifically, the goal is to introduce a fully replicable spatial DSS that processes both quantitative and qualitative information, balances between lowest-cost and lowest-impact routes. The model presented in this paper is implemented in a four step process: first, integration of multiple source data that provide basis for engineering and environmental design criteria; second, creation of several alternate routes; third, building a comprehensive decision matrix using spatial analysis techniques; and fourth, testing the alternative and opinions of the stakeholder groups on imperatives of AHP model to simplify the route optimization decision. The final output of the model is then used to carry out sensitivity analysis, quantify the risk, generate “several what and if scenarios” and test stability of the route optimization decision.

scholarly journals Cooperative Decision Support Systems

2011 ◽  
pp. 109-115 ◽  
Author(s):  
Pascale Zaraté
Keyword(s):  
Decision Making ◽  
Search Space ◽  
Optimal Decision ◽  
Decision Making Process ◽  
Collaborative Decision Making ◽  
Distributed Reasoning ◽  
Cooperative Decision Making ◽  
Optimal Decision Making ◽  
Analytical Tools ◽  
Collaborative Decision

The subject of our research aims to support in the most suitable way the collaborative decision-making process. Several scientific approaches deal with collaborative decision-making: decision analysis (Carlsson & Turban, 2002; Doyle & Thomason, 1999; Keeney & Raiffa, 1976) developing different analytical tools for optimal decision-making; in management sciences the observation of decision-making styles activity (Nuut, 2005; Fong, Wyer, & Robert 2003); decision-making as a group work (Esser, 1998; Matta & Corby, 1997); studies concerning different types of decisions focalised on number of actors: individual (Keeney & Raiffa, 1976), group (Shim, Warkentin, Courtney, Power, Sharda, & Carlsson, 2002), cooperative (Zaraté, 2005), and collaborative (Karacapilidis & Papadias, 2001). For the collaborative decision-making field, the situation is clear. In most of research studies, the concept of collaborative decision-making is used as a synonym for cooperative decision-making. Hence, the collaborative decision-making process is considered to be distributed and asynchronous (Chim, Anumba, & Carillo, 2004; Cil, Alpturk, & Yazgan, 2005). However, we can stand out several works, having different research approaches, considering collaborative decision-making process as multi-actor decision-making process, where actors have different goals. Considering (Panzarasa, Jennings, & Norman, 2002) the collaborative decision-making process is seen as “a group of logically decentralised agents that cooperate to achieve objectives that are typically beyond the capacities of an individual agent. In short, the collaborative decision-making has generally been viewed and modelled as a kind of distributed reasoning and search, whereby a collection of agents collaboratively go throughout the search space of the problem in order to find a solution.” The main interrogation of this article is to study the best way to support collaborative decision-making process.

scholarly journals TRANSFORMATION OF THE DECISION SUPPORT SYSTEM MODEL FOR STANDARD SITUATIONS USING INTELLECTUAL AND ANALYTICAL METHODS

2021 ◽  
Vol 21 (3) ◽  
pp. 14-25
Author(s):  
V.V. Antonov ◽  
◽  
K.A. Konev ◽  
G.G. Kulikov ◽  
◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Decision Makers ◽  
Information Support ◽  
Accurate Identification ◽  
Interaction Structure ◽  
Typical Situation ◽  
Analytical Tools

The article discusses the issues of improving the efficiency of decision support activities on a relatively large amount of information. The research relevance is associated with the increasing complexity of control objects, which leads to a decrease in the efficiency of decision-making based on the personal experience of decision-makers, up to complete impossibility. The purpose of the ar-ticle is to analyze the problems faced by decision-makers and the creation of methods to improve the effectiveness of decision-making in typical situations. The article examines the main compo-nents of the intelligent subsystem of the decision support system, which require the use of analytical tools, and also forms the methods interaction structure necessary for the effective formation of sce-narios of information support for decision making. To achieve the goals, a decision support method based on an intelligent component was used, which is aimed at creating an effective infrastructure to sup-port decision-making; methods of identification and categorization, designed to implement the most accurate and correct comparison of the characteristics (state) of the observed situation and the characteristics of a typical situation stored in the knowledge base; correlation methods aimed at finding dependencies between the characteristics of situations and scenarios to solve problems associated with these situa-tions; a method for constructing subject qualimetry, used to form a predictive model to assess the degree of compliance of the selected scenario for solving the current situation. As a result, it was de-termined that an important aspect of decision-making in typical situations is the most accurate identification of the state of the situation, the choice of the best scenario for implementing the solu-tion for this situation and the analysis of the consequences of the selected set of measures. To solve these problems, a method for identifying a situation, a method for finding solution scenarios and a qualimetric method for predicting the effectiveness of the selected scenario have been formed. The article concludes that decision-making activities based on the accumulated experience can be im-proved by using the proposed methods and implementing a decision support system with an intelli-gent component.

ARTIFICIAL INTELLIGENCE AND "PREDICTED JUSTICE": FOREIGN EXPERIENCE

Lex Russica ◽  
2019 ◽  
pp. 79-87
Author(s):  
P. N. Biryukov
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Relevant Information ◽  
Final Decision ◽  
Legal Information ◽  
The Right ◽  
Task Interpretation ◽  
Short Time ◽  
Analytical Tools

The paper deals with the problems of application of artificial intelligence (AI) in the field of justice. Present day environment facilitates the use of AI in law. Technology has entered the market. As a result, "predicted justice" has become possible. Once an overview of the possible future process is obtained, it is easier for the professional to complete the task-interpretation and final decision-making (negotiations, litigation). It will take a lot of work to bring AI up to this standard. Legal information should be structured to make it not only readable, but also effective for decision-making. "Predicted justice" can help both the parties to the case and the judges in structuring information, and students and teachers seeking relevant information. The development of information technology has led to increased opportunities for "predicted justice" programs. They take advantage of new digital tools. The focus is on two advantages of the programs: a) improving the quality of services provided; b) simultaneously monitoring the operational costs of the justice system. "Predicted justice" provides algorithms for analyzing a huge number of situations in a short time, allowing you to predict the outcome of a dispute or at least assess the chances of success. It helps: choose the right way of defense, the most suitable arguments, estimate the expected amount of compensation, etc. Thus, it is not about justice itself, but only about analytical tools that would make it possible to predict future decisions in disputes similar to those that have been analyzed.

scholarly journals Study on competitive intelligence in Israel: 2016 update

2016 ◽  
Vol 6 (2) ◽  
Author(s):  
Avner Barnea
Keyword(s):  
Decision Making ◽  
Response Rate ◽  
Quality Attributes ◽  
The State ◽  
Competitive Intelligence ◽  
Global Markets ◽  
Decision Making Process ◽  
Minimal Effect ◽  
Analytical Tools ◽  
Annual Turnover

This paper investigates the state of competitive intelligence among Israeli firmsin 2014. The methodology used was self completion questionnaires, which were responded to in May and June of 2016. A response rate of 26% was achieved with 39 questionnaires returned of the 69 questionnaires that were sent out to 65 local firms, most of them with an annual turnover of greater than 100 million USD. The results indicated that there were insignificant changes in the use of competitive intelligence in Israel in the last 10 years, since a survey conducted in 2006. Initially it looked as if the use of competitive intelligence was expanding, but the actual findings shows that the contribution of competitive intelligence to the decision making process was not progressing as it was expected to and there were difficulties in making competitiveintelligence an integral part of the decision-making process and having it reach an influential position. The results indicated that the recent global downturn evidently had only a minimal effect on the competitive intelligence scheme and in 75% of the firms there were actually almost no changes in the competitive intelligence programs. Clearly, competitive intelligence was primarily a tool used by the larger organizations and most of the firms that responded (60%),were among those who competed in the global markets. I have also attempted to look into the quality attributes of competitive intelligence performance, and it seemed that the low use of analytical tools was an indicator that we cannot ignore. Only 33% of the competitive intelligence professionals were using these tools regularly as part of their analysis work and in presentingtheir findings.

Web 2.0 Mash-Up System for Real Time Data Visualisation and Analysis Using OSS

2015 ◽  
pp. 208-231 ◽  
Author(s):  
Wajid Khan ◽  
Fiaz Hussain ◽  
Edmond C. Prakash
Keyword(s):  
Decision Making ◽  
Vital Role ◽  
Decision Makers ◽  
Resource Utilisation ◽  
Data Visualisation ◽  
Time Data ◽  
Real Time Data ◽  
Analytical Tools ◽  
Transactional Data ◽  
Day By Day

The arrival of E-commerce systems has contributed a lot to the economy and also played a vital role in collecting a huge amount of transactional data in the form of online orders and web enquiries, with such a huge volume of data it is getting difficult day by day to analyse business and consumer behaviour. There is a greater need for business analytical tools to help decision makers understand data properly - and understanding data will lead to amazing things such as hidden trends, effective resource utilisation, decision making ability and understanding business and its core values.

Business intelligence in academic libraries in Jordan: Opportunities and challenges

IFLA Journal ◽  
2020 ◽  
pp. 034003522093188 ◽  
Author(s):  
Faten Hamad ◽  
Razan Al-Aamr ◽  
Sinaria Abdel Jabbar ◽  
Hussam Fakhuri
Keyword(s):  
Decision Making ◽  
Business Intelligence ◽  
Academic Libraries ◽  
Academic Library ◽  
Decision Makers ◽  
Successful Implementation ◽  
Advanced Level ◽  
Department Staff ◽  
Library Users ◽  
Analytical Tools

Data plays a major role in helping to understand clearly the changing needs of academic library users, and in helping libraries to innovate their services and procedures accordingly. Data needs to be transformed into information for decision-making and strategic planning. Business intelligence offers powerful analytical tools, such as visualization and data-mining tools, which lead to informed decisions and hence transform the user’s experience, bringing it to a more advanced level. This research investigates the concept of business intelligence from the perceptions of information department staff at academic libraries in Jordan. The opportunities and challenges associated with it are also discussed and explored. As indicated by the results, information department staff agree that business intelligence improves decision-making, helping decision-makers to make the most accurate and timely decisions for the library. The results also indicate that an appropriate infrastructure is important for the successful implementation of business intelligence in academic libraries in Jordan.

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