Applying Fuzzy Data Mining to Tourism Area

2011 ◽  
pp. 563-584 ◽  
Author(s):  
R. A. Carrasco ◽  
F. Araque ◽  
A. Salguero ◽  
M. A. Vila
Keyword(s):  
Data Mining ◽  
Data Warehouse ◽  
Selection Process ◽  
Fuzzy Data ◽  
Competitive Sport ◽  
Location Selection ◽  
Number Of Factors ◽  
Complex Decision Making ◽  
Complex Decision

Soaring is a recreational activity and a competitive sport where individuals fly un-powered aircrafts known as gliders. The soaring location selection process depends on a number of factors, resulting in a complex decision-making task. In this chapter, we propose the use of an extension of the FSQL language for fuzzy queries as one of the techniques of data mining that can be used to solve the problem of offering a better place for soaring given the environmental conditions and customer characteristics. The FSQL language is an extension of the SQL language that permits us to write flexible conditions in our queries to a fuzzy or traditional database. After doing a process of clustering and characterization of a large customer database in a data warehouse, we are able of classify the next clients in a cluster and offer an answer according to it.

Combining Induction Methods with the Multimethod Approach

2011 ◽  
pp. 184-189
Author(s):  
Mitja Lenic ◽  
Peter Kokol ◽  
Petra Povalej ◽  
Milan Zorman
Keyword(s):  
Data Mining ◽  
Important Class ◽  
Missed Opportunities ◽  
Disk Storage ◽  
Large Databases ◽  
Complex Decision Making ◽  
Multimethod Approach ◽  
Complex Decision ◽  
Multi Method Approach ◽  
Method Approach

The aggressive rate of growth of disk storage and, thus, the ability to store enormous quantities of data have far outpaced our ability to process and utilize that. This challenge has produced a phenomenon called data tombs—data is deposited to merely rest in peace, never to be accessed again. But the growing appreciation that data tombs represent missed opportunities in cases supporting scientific discovering, business exploitation, or complex decision making has awakened the growing commercial interest in knowledge discovery and data-mining techniques. That, in order, has stimulated new interest in the automatic knowledge induction from cases stored in large databases—a very important class of techniques in the data-mining field. With the variety of environments, it is almost impossible to develop a single-induction method that would fit all possible requirements. Thereafter, we constructed a new so-called multi-method approach, trying out some original solutions.

INVESTIGATING CONFLICTS IN COTS DECISION-MAKING

2003 ◽  
Vol 13 (05) ◽  
pp. 473-493 ◽  
Author(s):  
CARINA ALVES ◽  
ANTHONY FINKELSTEIN
Keyword(s):  
Decision Making ◽  
Selection Process ◽  
Decision Making Process ◽  
Customer Requirements ◽  
Mail Server ◽  
Different Types ◽  
Complex Decision Making ◽  
Complex Decision

The development of COTS-based systems largely depends on the success of the selection process. This activity encompasses the evaluation of COTS packages against customer requirements, so that it is necessary to perform a complex decision-making process to select the most suitable package. We argue that analysing the matching between features and requirements is a core task of COTS decision-making. In particular, it is very likely that mismatches occur, as COTS are designed to meet very general requirements rather than specific needs. In this paper, we investigate the different types of conflicts that can arise from these mismatches. We propose a goal driven framework to deal with such conflicts. We demonstrate the approach with the mail server case study.

Fuzzy Optimization Model for Decision-Making in Supply Chain Management

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 312
Author(s):  
Jui-Fang Chang ◽  
Chao-Jung Lai ◽  
Chia-Nan Wang ◽  
Ming-Hsien Hsueh ◽  
Van Thanh Nguyen
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Optimization ◽  
Multicriteria Decision Making ◽  
Garment Industry ◽  
Fuzzy Environment ◽  
Selection Processes ◽  
Complex Decision Making ◽  
Complex Decision

Choosing a supplier is a complex decision-making process that can reduce the total cost of production inputs and increase profits without increasing the price or sacrificing product quality. However, supplier selection processes usually involve multiple quantitative and qualitative criteria which increase the complexity of the problem and may decrease the accuracy and effectiveness of the process. Such complex decision-making problems can be supported by using multicriteria decision-making (MCDM) models. While there have been multiple MCDM models to support supplier selection processes in different industries and sectors, only a few are developed to support the supplier selection processes in the garment industry, especially under uncertain decision-making environment. This paper presents an integrated mathematical model under a fuzzy environment and applies it to the supplier selection process in the garment industry. In this research, the authors utilize the Buckley extension based fuzzy Analytical Hierarchical Process (FAHP) method in combination with linear normalization based fuzzy Grey Relational Analysis (F-GRA) method to develop a MCDM approach to the supplier selection process under a fuzzy environment. As a result, supplier 08 (SA08) is the optimal supplier. The contribution of this work is to propose an MCDM model for ranking potential suppliers in the garment industry under a fuzzy environment. The proposed approach can also be applied to support complex decision-making processes under a fuzzy environment in different industries.

scholarly journals A Delphi Study Investigating Clinicians’ Views on Access to, Delivery of, and Adaptations of MBCT in the UK Clinical Settings

Mindfulness ◽  
2021 ◽  
Author(s):  
Kate Williams ◽  
Samantha Hartley ◽  
Peter Taylor
Keyword(s):  
Delphi Study ◽  
Good Practice ◽  
Evidence Base ◽  
Clinical Settings ◽  
Training Support ◽  
Decision Making Processes ◽  
Complex Decision Making ◽  
Complex Decision ◽  
The Uk ◽  
Clinical Populations

Abstract Objectives Mindfulness-based cognitive therapy (MBCT) is a well-evidenced relapse-prevention intervention for depression with a growing evidence-base for use in other clinical populations. The UK initiatives have outlined plans for increasing access to MBCT in clinical settings, although evidence suggests that access remains limited. Given the increased popularity and access to MBCT, there may be deviations from the evidence-base and potential risks of harm. We aimed to understand what clinicians believe should be best clinical practice regarding access to, delivery of, and adaptations to MBCT. Methods We employed a two-stage Delphi methodology. First, to develop statements around best practices, we consulted five mindfulness-based experts and reviewed the literature. Second, a total of 59 statements were taken forward into three survey rating rounds. Results Twenty-nine clinicians completed round one, with 25 subsequently completing both rounds two and three. Forty-four statements reached consensus; 15 statements did not. Clinicians agreed with statements regarding sufficient preparation for accessing MBCT, adherence to the evidence-base and good practice guidelines, consideration of risks, sufficient access to training, support, and resources within services, and carefully considered adaptations. The consensus was not reached on statements which reflected a lack of evidence-base for specific clinical populations or the complex decision-making processes involved in delivering and making adaptations to MBCT. Conclusions Our findings highlight the delicate balance of maintaining a client-centred and transparent approach whilst adhering to the evidence-base in clinical decisions around access to, delivery of, and adaptations in MBCT and have important wide-reaching implications.

Sign in / Sign up

Export Citation Format

Share Document