scholarly journals Decision trees in environmental justice research — a case study on the floods of 2001 and 2010 in Hungary

2019 ◽  
Vol 11 (1) ◽  
pp. 1025-1034 ◽  
Author(s):  
Gyula Nagy ◽  
György Vida ◽  
Lajos Boros ◽  
Danijela Ćirić
Keyword(s):  
Decision Making ◽  
Decision Tree ◽  
Environmental Justice ◽  
Social Groups ◽  
Principal Component ◽  
Decision Making Processes ◽  
Main Factors ◽  
Decision Tree Method ◽  
Tree Method

Abstract Environmental justice is a normative framework for the analysis of environmental impacts on the wellbeing of individuals and social groups. According to the framework, the deprived social groups and ethnic minorities are often more exposed to environmental risks and hazards due to their disadvantaged situation, and due to the lack of representation and political power. To manage the impacts of injustices and to include the citizen in the decision-making processes, proper information is needed on local attitudes and decision-making processes. Therefore, this study sought to (i) identify the main factors shaping the attitudes towards environmental injustices and (ii) to analyse the attitudes and perception of the various social groups and (iii) to identify the main factors which are shaping the attitudes and actions of those who were affected by the floods of 2001 and 2010 through the use of decision tree method. The data for the predictive model was acquired from a questionnaire survey conducted in two disadvantaged and flood-hit Hungarian regions. Based on the survey data, a principal component analysis (PCA) was conducted, which resulted in three principal components; fear, social change, and change in the built environment. The study focused only on the elements of the “fear principal component”, due to the decision tree tool homogenous groups identified in relation to this component. Our analysis showed that ethnicity has a determinative role in the emergence and the level of fear from floods; the Roma respondents expressed a significantly higher level of fear than others.

scholarly journals Common Metamodel of Questionnaire Model and Decision Tree Model

2018 ◽  
Vol 10 (3) ◽  
pp. 106
Author(s):  
Mirza Suljic ◽  
Edin Osmanbegovic ◽  
Željko Dobrović
Keyword(s):  
Decision Making ◽  
Decision Tree ◽  
Decision Trees ◽  
Decision Tree Model ◽  
Tree Model ◽  
Meta Model ◽  
The Subject ◽  
Decision Tree Method ◽  
Questionnaire Method ◽  
Tree Method

The subject of this paper is metamodeling and its application in the field of scientific research. The main goal is to explore the possibilities of integration of two methods: questionnaires and decision trees. The questionnaire method was established as one of the methods for data collecting, while the decision tree method represents an alternative way of presenting and analyzing decision making situations. These two methods are not completely independent, but on the contrary, there is a strong natural bond between them. Therefore, the result reveals a common meta-model that over common concepts and with the use of metamodeling connects the methods: questionnaires and decision trees. The obtained results can be used to create a CASE tool or create repository that can be suitable for exchange between different systems. The proposed meta-model is not necessarily the final product. It could be further developed by adding more entities that will keep some other data.

scholarly journals Classification of Parkinsonian Syndromes from FDG-PET Brain Data Using Decision Trees with SSM/PCA Features

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
D. Mudali ◽  
L. K. Teune ◽  
R. J. Renken ◽  
K. L. Leenders ◽  
J. B. T. M. Roerdink
Keyword(s):  
Decision Tree ◽  
Decision Trees ◽  
Fdg Pet ◽  
Imaging Techniques ◽  
Principal Component ◽  
Training Data ◽  
Brain Diseases ◽  
Parkinsonian Syndromes ◽  
Decision Tree Method ◽  
Tree Method

Medical imaging techniques like fluorodeoxyglucose positron emission tomography (FDG-PET) have been used to aid in the differential diagnosis of neurodegenerative brain diseases. In this study, the objective is to classify FDG-PET brain scans of subjects with Parkinsonian syndromes (Parkinson’s disease, multiple system atrophy, and progressive supranuclear palsy) compared to healthy controls. The scaled subprofile model/principal component analysis (SSM/PCA) method was applied to FDG-PET brain image data to obtain covariance patterns and corresponding subject scores. The latter were used as features for supervised classification by the C4.5 decision tree method. Leave-one-out cross validation was applied to determine classifier performance. We carried out a comparison with other types of classifiers. The big advantage of decision tree classification is that the results are easy to understand by humans. A visual representation of decision trees strongly supports the interpretation process, which is very important in the context of medical diagnosis. Further improvements are suggested based on enlarging the number of the training data, enhancing the decision tree method by bagging, and adding additional features based on (f)MRI data.

scholarly journals C4.5 Classification Data Mining for Inventory Control

2018 ◽  
Vol 7 (2.3) ◽  
pp. 68 ◽  
Author(s):  
Robbi Rahim ◽  
Ilka Zufria ◽  
Nuning Kurniasih ◽  
Muhammad Yasin Simargolang ◽  
Abdurrozzaq Hasibuan ◽  
...  
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Tree ◽  
Large Data ◽  
Production Costs ◽  
Traffic Data ◽  
Tree Form ◽  
Minimal Error ◽  
Decision Tree Method ◽  
Tree Method

Data Mining is a process of exploring against large data to find patterns in decision making. One of the techniques in decision-making is classification. Classification is a technique in data mining by applying decision tree method to form data, algorithm C4.5 is algorithm that can be used to classify data in tree form. The system has been built that shows the results of good performance and minimal error in view of the system that is able to distinguish the anomaly traffic with normal traffic. Data mining inventory system applications can facilitate the control of inventory in the company to reduce production costs. 

scholarly journals Using Decision Trees for Identification of Most Relevant Indicators for Effective ICT Utilization

2013 ◽  
Vol 13 (1) ◽  
pp. 83-94 ◽  
Author(s):  
Silvana Tomic Rotim ◽  
Jasminka Dobsa ◽  
Zdravko Krakar
Keyword(s):  
Decision Tree ◽  
Decision Trees ◽  
World Economic Forum ◽  
Effective Utilization ◽  
The World ◽  
World Economic ◽  
Main Factors ◽  
Decision Tree Method ◽  
Tree Method

Abstract This paper offers a brief overview of the research of ICT utilization and benefits of its usage. The results of several important studies conducted worldwide are presented. One of them is a study by the World Economic Forum that we use as the basis of our research. This study covers 134 countries, NRI (Network Readiness Index) is used as a parameter to distinguish the readiness of different countries to adopt ICT. NRI consists of 68 indicators that are organized into three groups. Each group describes one of the three main factors crucial for effective utilization of ICT: Environment, Readiness and Usage. The observed countries are divided into four groups (leaders, followers, league III and league IV) and classification by a decision tree is conducted. The decision tree method is applied to each of the three main factors and the results are presented by means of F1 measure.

scholarly journals Method of decision tree applied in adopting the decision for promoting a company

10.26458/1535 ◽  
2015 ◽  
Vol 15 (3) ◽  
pp. 47
Author(s):  
Cezarina Adina TOFAN
Keyword(s):  
Decision Making ◽  
Decision Tree ◽  
Decision Making Process ◽  
Competition Intensity ◽  
Financial Decisions ◽  
Complex Information ◽  
Decision Tree Method ◽  
A Company ◽  
Informational System ◽  
Tree Method

 The decision can be defined as the way chosen from several possible to achieve an objective. An important role in the functioning of the decisional-informational system is held by the decision-making methods. Decision trees are proving to be very useful tools for taking financial decisions or regarding the numbers, where a large amount of complex information must be considered. They provide an effective structure in which alternative decisions and the implications of their choice can be assessed, and help to form a correct and balanced vision of the risks and rewards that may result from a certain choice. For these reasons, the content of this communication will review a series of decision-making criteria. Also, it will analyse the benefits of using the decision tree method in the decision-making process by providing a numerical example. On this basis, it can be concluded that the procedure may prove useful in making decisions for companies operating on markets where competition intensity is differentiated.  

scholarly journals The application of outsourcing decision-making methods in a logistics context in South Africa

2015 ◽  
Vol 9 (1) ◽  
Author(s):  
Naomi Bloem ◽  
Wilna L. Bean
Keyword(s):  
Decision Making ◽  
South African ◽  
Decision Problem ◽  
Cost Model ◽  
Logistics Outsourcing ◽  
Secondary Distribution ◽  
Decision Tree Method ◽  
Outsourcing Decision ◽  
Tree Method

Background: Companies have often relinquished the control of important business functions to outside suppliers for the sake of short-term savings and because of the lack of use of proper decision-making methods within the business.Objectives: This article identified three methods of decision-making and applied it to a logistics outsourcing problem. The logistics outsourcing problem consisted of a make-or-buy decision as well as a supplier selection process. The purpose of the study was to determine the most suitable method in the case of logistics outsourcing.Method: The decision-making methods were applied to a South African case study within the fast moving consumer goods (FMCG) industry. The logistics functions considered in the case study included secondary distribution and warehousing of finished goods. Each method considered the same evaluation criteria and the results were analysed and compared.Results: Each method produced different results to the logistics outsourcing problem. The method developed by Platts, Probert and Canez (2000) suggested that the logistics functions be insourced. The decision tree method suggested outsourcing both functions, with a unit rate cost model. The results from the linear programming (LP) method indicated that the secondary distribution function should be insourced and the warehousing function outsourced, with a fixed and variable cost model pending further analysis of the demand trends.Conclusion: The study provides empirical evidence that proven outsourcing decision-making methods, such as the method developed by Platts et al. (2000), the LP method and the decision tree method traditionally applied to a manufacturing outsourcing decision problem, can be adapted and applied to a logistics outsourcing decision problem of a South African FMCG company.

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