scholarly journals Building decision trees based on production knowledge as support in decision-making process

2020 ◽  
Vol 26 (2) ◽  
pp. 36-40
Author(s):  
Marcin Matuszny
Keyword(s):  
Decision Making ◽  
Decision Tree ◽  
Decision Trees ◽  
Real Data ◽  
Knowledge Bases ◽  
Decision Making Process ◽  
Construction Of Knowledge ◽  
Production Processes ◽  
Technical Preparation ◽  
Production Knowledge

AbstractThe article presents sources of production knowledge and thoroughly describes its identification which on the construction of decision trees, and on the construction of knowledge bases for production processes. The problems that arise during the technical preparation of production are briefly characterized and the advanced algorithm with which decision trees can be built is described in detail. A decision tree was built based on real data from the manufacturing company. Decision trees are presented as a method of knowledge representation.

Decision Trees

2011 ◽  
pp. 203-208
Author(s):  
John Wang ◽  
Dajin Wang
Keyword(s):  
Decision Making ◽  
Decision Tree ◽  
Decision Theory ◽  
Decision Trees ◽  
Decision Making Process ◽  
Decision Tree Learning ◽  
Learning Methods ◽  
Business Functions

Decision trees are part of the decision theory and are excellent tools in the decision-making process. Majority of decision tree learning methods were developed within the last 30 years by scholars like Quinlan, Mitchell, and Breiman, just to name a few (Ozgulbas & Koyuncugil, 2006). There are a number of methods and sophisticated software used to graphically present decision trees. Decision trees have a great number of benefits and are widely used in many business functions as well as different industries. However there are also disagreements and various concerns as to how useful decision trees really are. As technology evolves so do decision trees. Therefore not only do many controversies arise but also solutions and new proposals to these arguments.

Implementation of Decision Tree for Maintenance Policy Decision Making - A Case Study in Semiconductor Industry

2012 ◽  
Vol 591-593 ◽  
pp. 704-707 ◽  
Author(s):  
Siew Hong Ding ◽  
Teing Tien Goh ◽  
Pei Sze Tan ◽  
Siew Ching Wee ◽  
Shahrul Kamaruddin
Keyword(s):  
Decision Making ◽  
Decision Tree ◽  
Failure Mechanism ◽  
Semiconductor Industry ◽  
Policy Decision ◽  
Decision Making Process ◽  
Maintenance Policy ◽  
Machine Performance ◽  
Policy Decision Making

Suitable maintenance policy implemented in particular machine able to improve the machine performance as well as the product quality. However, selecting a suitable maintenance policy is a vital and hard work because it has to be decided from analysis of various criteria including failure mechanism and resources limitation. Thus, decision tree is suggested in this paper to provide assistance for maintenance crew in conducting a systematic and efficient decision making process in determining the suitable maintenance policy. In the end of the paper, a case study in semiconductor industry is conducted to illustrate the practicability of developed decision tree.

Utilizing Fuzzy Decision Trees in Decision Making

2011 ◽  
pp. 2024-2030
Author(s):  
Malcolm J. Beynonm
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Tree ◽  
Decision Trees ◽  
Time Series Data ◽  
Series Data ◽  
Fuzzy Decision ◽  
Fuzzy Environment ◽  
Complex Decision Making ◽  
Fuzzy Decision Trees

The seminal work of Zadeh (1965), namely fuzzy set theory (FST), has developed into a methodology fundamental to analysis that incorporates vagueness and ambiguity. With respect to the area of data mining, it endeavours to find potentially meaningful patterns from data (Hu & Tzeng, 2003). This includes the construction of if-then decision rule systems, which attempt a level of inherent interpretability to the antecedents and consequents identified for object classification (See Breiman, 2001). Within a fuzzy environment this is extended to allow a linguistic facet to the possible interpretation, examples including mining time series data (Chiang, Chow, & Wang, 2000) and multi-objective optimisation (Ishibuchi & Yamamoto, 2004). One approach to if-then rule construction has been through the use of decision trees (Quinlan, 1986), where the path down a branch of a decision tree (through a series of nodes), is associated with a single if-then rule. A key characteristic of the traditional decision tree analysis is that the antecedents described in the nodes are crisp, where this restriction is mitigated when operating in a fuzzy environment (Crockett, Bandar, Mclean, & O’Shea, 2006). This chapter investigates the use of fuzzy decision trees as an effective tool for data mining. Pertinent to data mining and decision making, Mitra, Konwar and Pal (2002) succinctly describe a most important feature of decision trees, crisp and fuzzy, which is their capability to break down a complex decision-making process into a collection of simpler decisions and thereby, providing an easily interpretable solution.

Simulation of consumers decision-making process using agent-based model approach

2019 ◽  
Vol 10 (06) ◽  
pp. 1950037
Author(s):  
Daniel Soto Forero ◽  
Yony F. Ceballos ◽  
German Sànchez Torres
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Real Data ◽  
World Market ◽  
Decision Making Process ◽  
Agent Based ◽  
Dynamic Social Network ◽  
Proposed Model ◽  
The World ◽  
Model Approach

This paper describes a model to simulate the decision-making process of consumers that adopts technology within a dynamic social network. The proposed model use theories and tools from the psychology of consumer behavior, social networks and complex dynamical systems like the Consumat framework and fuzzy logic. The model has been adjusted using real data, tested with the automobile market and it can recreate trends like those described in the world market.

scholarly journals Assessment of maturity of reverse logistics as a strategy to sustainable solid waste management

2020 ◽  
Vol 38 (1_suppl) ◽  
pp. 65-76 ◽  
Author(s):  
Claudia C Peña-Montoya ◽  
Marina Bouzon ◽  
Patricia Torres-Lozada ◽  
Carlos Julio Vidal-Holguin
Keyword(s):  
Decision Making ◽  
Waste Management ◽  
Solid Waste ◽  
Reverse Logistics ◽  
Solid Waste Management ◽  
Decision Making Process ◽  
Maturity Model ◽  
Maturity Models ◽  
Production Processes ◽  
Holistic Vision

Small- and medium-sized enterprises primarily focus on their operations and rarely pay attention to issues related to sustainable solid waste management that originate from their production processes. A suitable strategy to support sustainable solid waste management is reverse logistics. Through the use of maturity models, it is possible to determine the grade to which small- and medium-sized enterprises are prepared to perform this strategy. This study proposes an adapted maturity model to measure maturity levels of reverse logistics aspects at small- and medium-sized enterprises in regions from Colombia in order to contribute to sustainable solid waste management. The maturity model was applied to seven small- and medium-sized enterprises in the plastics sector in the central and southern regions of Colombia by adapting a maturity model that was previously correlated to suggested drivers and barriers in this sector. Results show that maturity levels range from naïve to immature owing to the incipient development of reverse logistics in Colombia. Therefore, it is necessary to establish a holistic vision of the organisation to improve the reverse logistics decision-making process to achieve sustainable solid waste management.

scholarly journals A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Jose M. Gonzalez-Cava ◽  
José Antonio Reboso ◽  
José Luis Casteleiro-Roca ◽  
José Luis Calvo-Rolle ◽  
Juan Albino Méndez Pérez
Keyword(s):  
Decision Making ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Real Data ◽  
Clinical Variable ◽  
Decision Making Process ◽  
Drug Supply ◽  
Inference System ◽  
Surgical Interventions ◽  
Physiological Signal

One of the main challenges in medicine is to guarantee an appropriate drug supply according to the real needs of patients. Closed-loop strategies have been widely used to develop automatic solutions based on feedback variables. However, when the variable of interest cannot be directly measured or there is a lack of knowledge behind the process, it turns into a difficult issue to solve. In this research, a novel algorithm to approach this problem is presented. The main objective of this study is to provide a new general algorithm capable of determining the influence of a certain clinical variable in the decision making process for drug supply and then defining an automatic system able to guide the process considering this information. Thus, this new technique will provide a way to validate a given physiological signal as a feedback variable for drug titration. In addition, the result of the algorithm in terms of fuzzy rules and membership functions will define a fuzzy-based decision system for the drug delivery process. The method proposed is based on a Fuzzy Inference System whose structure is obtained through a decision tree algorithm. A four-step methodology is then developed: data collection, preprocessing, Fuzzy Inference System generation, and the validation of results. To test this methodology, the analgesia control scenario was analysed. Specifically, the viability of the Analgesia Nociception Index (ANI) as a guiding variable for the analgesic process during surgical interventions was studied. Real data was obtained from fifteen patients undergoing cholecystectomy surgery.

The Structuring Of The Strategic-Decision-Making Process

2011 ◽  
pp. 213-240
Author(s):  
Tamio Shimizu ◽  
Marley Monteiro de Carvalho ◽  
Fernando Jose Barbin
Keyword(s):  
Decision Making ◽  
Sensitivity Analysis ◽  
Decision Trees ◽  
Strategic Decision ◽  
Decision Models ◽  
Decision Problems ◽  
Strategic Decision Making ◽  
Decision Making Process ◽  
Decision Matrix

The basic types of decision models presented in the previous chapter (rational, descriptive, political, and ambiguous models) relies on quantitative values (money, time, or probabilities) that are most suitable for structured and semi-structured decision problems. These basic models can be used as starting models to guide the structuring process of strategic decision problems. First, a systematic procedure for structuring the strategic decision making process is presented, using decision matrix and decision trees. The need for the sensitivity analysis is introduced, and will be illustrated with more detail in the next chapter. Some problems that must be considered in this structuring process are illustrated in form of hidden traps and paradoxes. The first step in the decision-making process is to formulate the problem. It is possible that an inadequate formulation of the problem leads to a result that reduces efficiency and efficacy, since an incorrect formulation can define a wrong problem.

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 Making Decisions in Monitoring by Using Decision-Making Method, Knowledge Bases and New it Solutions

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jefto Džino ◽  
Branko Latinović ◽  
Zoran Ž. Avramović
Keyword(s):  
Decision Making ◽  
Semantic Web ◽  
Open Source ◽  
Knowledge Bases ◽  
Decision Makers ◽  
Decision Making Process ◽  
Specific Knowledge ◽  
Decision Making Processes

In this paper we deal with decision-making processes in monitoring with the use of new technological solutions. This is an area where decision-makers in monitoring face a large number of different challenges and need appropriate specific knowledge. We give an example of a method for making complex decisions. Here we propose the application of the semantic web and knowledge bases that can provide decision-makers with a quick access to the necessary knowledge in the decision-making process. To update some of the knowledge we will use the Protégé editor, an open source platform. Our goal is not to update all the necessary knowledge needed by those who make decisions in monitoring, but only to propose a new concept to their faster fullfilment and more efficient use.

scholarly journals A CBR-AHP Hybrid Method to Support the Decision-Making Process in the Selection of Environmental Management Actions

2019 ◽  
Author(s):  
Fernando Ramos-Quintana ◽  
Efraín Tovar-Sánchez ◽  
Hugo Saldarriaga-Noreña ◽  
Héctor Sotelo-Nava ◽  
Juan-Paulo Sánchez-Hernández ◽  
...  
Keyword(s):  
Environmental Management ◽  
Decision Making ◽  
Real Data ◽  
Environmental Management System ◽  
Decision Making Process ◽  
Case Based Reasoning ◽  
Adaptation Mechanism ◽  
Sustainable Performance ◽  
Management Actions ◽  
State Quality

This paper proposes a Case-Based Reasoning (CBR) system to contribute to reinforce the sustainable performance of an environmental management system. The CBR system aims to support the decision-making process to select environmental management actions aimed at reducing risky trends of the environmental state of a region. The CBR system takes advantage of a set of situation-solution pairs called cases, which are stored in a memory and then retrieved as candidates to solve new problems. Situations in this work are represented by a set of risky trends of the following key environmental variables: CO2 emissions, Air-Quality, Loss of Vegetation Cover, Water Availability, and Solid Waste, whose combination damage the environmental state quality of a region. Meanwhile, solutions are represented by a set of environmental management actions. Similar situations to a given current situation are retrieved from the memory of cases and then their solutions are combined, through an adaptation mechanism, until the solution of the current problem is obtained. We used risky trends derived from real data related to the environmental states of a Mexican region to test the proposed CBR system. The results obtained provided insights into the potential of CBR systems to support the decision-making process to select environmental management actions aimed at reducing risky trends of current environmental states.

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