scholarly journals Clustering analysis and decision-making by “rank of links”

2002 ◽  
Vol 8 (4-5) ◽  
pp. 475-492 ◽  
Author(s):  
O. Verulava ◽  
R. Khurodze
Keyword(s):  
Decision Making ◽  
Cluster Analysis ◽  
Clustering Analysis ◽  
Decision Making Process ◽  
Distance Matrices

In this paper, formalism for cluster analysis, based on the “Rank of Links”-theory, is suggested. It tackles resemble measures, cross-distance matrices, “rank of links”-metric and some other cluster characteristics. Using these notions, an algorithm of clustering has been designed. Its application to estimation and prognosis of decision-making process shows nice workability and reliability.

scholarly journals Could clustering of comorbidities be useful for better defining the internal medicine patients’ complexity?

2018 ◽  
Vol 12 (2) ◽  
pp. 137 ◽  
Author(s):  
Flavio Tangianu ◽  
Paola Gnerre ◽  
Fabrizio Colombo ◽  
Roberto Frediani ◽  
Giuliano Pinna ◽  
...  
Keyword(s):  
Internal Medicine ◽  
Decision Making ◽  
Cluster Analysis ◽  
Adverse Events ◽  
Decision Making Process ◽  
High Similarity ◽  
High Prevalence ◽  
Clinical Problems ◽  
Index Disease ◽  
Improve Health

Internal medicine patients are mostly elderly with multiple comorbidities, usually chronic. The high prevalence of comorbidity and multimorbidity has a significant impact on both positive responses to treatment and the occurrence of adverse events. Clustering is the process of nosography grouping into meaningful associations with some index disease, so that the objects within a cluster have high similarity in comparison with one another. In the decision-making process it is imperative that, in addition to understanding the immediate clinical problems, we are able to explicit all the contextual factors that have to be taken into account for the best outcome of care. Cluster analysis could be leveraged in developing better interventions targeted to improve health outcomes in subgroups of patients.

A Product Feature Prioritization-Based Segmentation Model of Consumer Market for Health Drinks

2019 ◽  
Vol 10 (2) ◽  
pp. 70-83
Author(s):  
Chandan Parsad ◽  
Chandra Prakash Chandra ◽  
Shekhar Suman
Keyword(s):  
Decision Making ◽  
Cluster Analysis ◽  
Country Of Origin ◽  
The Internet ◽  
Decision Making Process ◽  
Relative Importance ◽  
Consumer Decision Making ◽  
Consumer Market ◽  
Consumer Decision

This study sets out to identify the various factors of a health drink product that affects the consumer decision-making process. It aims to determine the relative importance connected to multiple aspects of health drink beverages, such as brand, nutrition content, taste, muscle building, brain boosting, price, ingredients, and country of origin. The paper also aims to identify consumer segments by the relative importance consumers give to various attributes of health drinks. Through examining the literature, the researchers identified various attributes of health drinks, which they analyzed empirically using a choice-based conjoint survey conducted with the help of the internet-based software 1000minds. Cluster analysis was also done to identify different consumer segments. The study identified two consumer segments: brand conscious and value conscious. As the name indicates, the brand-conscious segment gives more importance to a trusted brand, followed by nutrition content and price.

scholarly journals Applying cluster analysis to ranking the vulnerabilities of railway influence territory

2019 ◽  
Vol 265 ◽  
pp. 02018
Author(s):  
Viktor Katin ◽  
Vladimir Kosygin ◽  
Midkhat Akhtiamov ◽  
Andrey Lutsenko
Keyword(s):  
Decision Making ◽  
Cluster Analysis ◽  
Single Point ◽  
Rail Transport ◽  
Accurate Information ◽  
Decision Making Process ◽  
Cultural Significance ◽  
Ecological Economic ◽  
Vulnerability Ranking

The article considers the proprietary method of ranking the territory of the railway influence, based on the use of vulnerability matrices and application of cluster analysis, which allows optimizing the decision-making process for responding to emergencies associated with rail transport. The "point" ranking of vulnerabilities in the zone of railway influence was used for more accurate information on the events with applying the identity matrices of vulnerabilities. The partition cell is taken as a single "point". The method is based on the ranking of ecological, economic, environmental, bioresource and cultural significance of the territory by means of defining identical matrices of vulnerabilities that describe each point of the event. The partition cells were grouped into three clusters: moderately vulnerable territory, highly vulnerable territory and extremely vulnerable territory. The result of using the method was the compiling of vulnerability ranking maps.

scholarly journals Analysis of natural-production conditions for timber harvesting in European North of Russia

2019 ◽  
Vol 65 (2) ◽  
pp. 81-91
Author(s):  
Ilya Shegelman ◽  
Pavel Budnik ◽  
Vyacheslav Baklagin ◽  
Oleg Galaktionov ◽  
Ivan Khyunninen ◽  
...  
Keyword(s):  
Decision Making ◽  
Cluster Analysis ◽  
Forest Management ◽  
Timber Harvesting ◽  
Decision Making Process ◽  
Small Enterprises ◽  
Natural Production ◽  
European North ◽  
Different Levels ◽  
Production Conditions

Abstract Natural-production conditions determine operational efficiency of logging machines. This influence needs to be taken into account at different levels of forest management. It is necessary to allocate areas with similar natural-production conditions for effective forest management. It allows simplifying the decision making process for selecting logging technology and machines. The purpose of this study was to establish areas with similar natural and production conditions in the European North of Russia (ENR). In addition, for small enterprises, we recommend logging technologies and logging machines that can be used in established areas. We determined the indicators of the natural-production conditions of ENR regions and compared them. Cluster analysis was used to compare the indicators. We found that ENR can be divided into three main zones A, B, C and two subzones B1 and B2 with similar natural-production conditions. In the zones A, B and the subzones B1 and B2, small logging enterprises should use a harvester and a forwarder. In the zone C, the enterprises can use a logging system including a harvester and a forwarder or a logging system including a feller buncher, a skidder and a processor. The logging system should be based on the light class of logging machines for the zone A, the medium class or the heavy class for the zones B, C and the subzones B1, B2, the heavy class of machines for the zone C.

scholarly journals The Application Of K-Means Algorithm For LQ45 Index on Indonesia Stock Exchange

2016 ◽  
Vol 7 (2) ◽  
pp. 151
Author(s):  
A. Raharto Condrobimo ◽  
Albert V. Dian Sano ◽  
Hendro Nindito
Keyword(s):  
Decision Making ◽  
Cluster Analysis ◽  
Stock Exchange ◽  
Decision Making Process ◽  
Exchange Cluster ◽  
Stock Investment ◽  
Speed Up

The objective of this study is to apply cluster analysis or also known as clustering on stocks data listed in LQ45 index at Indonesia Stock Exchange. The problem is that traders need a tool to speed up decision-making process in buying, selling and holding their stocks.The method used in this cluster analysis is k-means algorithm. The data used in this study were taken from Indonesia Stock Exchange. Cluster analysis in this study took data’s characteristics such as stocks volume and value. Results of cluster analysis were presented in the form of grouping of clusters’ members visually. Therefore, this cluster analysis in this study could be used to identify more quickly and efficiently about the members of each cluster of LQ45 index. The results of such identification can be used by beginner-level investors who have started interest in stock investment to help make decision on stocks trading.

AAC Decision-Making and Mobile Technology: Points to Ponder

2014 ◽  
Vol 23 (2) ◽  
pp. 104-111 ◽  
Author(s):  
Mary Ann Abbott ◽  
Debby McBride
Keyword(s):  
Decision Making ◽  
Mobile Technology ◽  
Communication System ◽  
Augmentative And Alternative Communication ◽  
Evaluation Process ◽  
Decision Making Process ◽  
Alternative Communication ◽  
Ipod Touch ◽  
Feature Match

The purpose of this article is to outline a decision-making process and highlight which portions of the augmentative and alternative communication (AAC) evaluation process deserve special attention when deciding which features are required for a communication system in order to provide optimal benefit for the user. The clinician then will be able to use a feature-match approach as part of the decision-making process to determine whether mobile technology or a dedicated device is the best choice for communication. The term mobile technology will be used to describe off-the-shelf, commercially available, tablet-style devices like an iPhone®, iPod Touch®, iPad®, and Android® or Windows® tablet.

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