A method for threshold selection in load extrapolation based on multiple criteria decision-making technology

2017 ◽  
Vol 08 (03) ◽  
pp. 1750019
Author(s):  
Jixin Wang ◽  
Qingsong Liu ◽  
Xinting Zhai
Keyword(s):  
Decision Making ◽  
Comprehensive Evaluation ◽  
Multiple Criteria Decision Making ◽  
Entropy Method ◽  
Multiple Criteria ◽  
Threshold Selection ◽  
Selection Methods ◽  
Additional Method ◽  
Random Simulation ◽  
Peak Over Threshold

In order to establish an accurate peak over threshold (POT) model for reasonable load extrapolation, a new threshold selection method based on multiple criteria decision making (MCDM) technology is proposed. The fitting test criterion is taken into consideration in the method. For each candidate threshold, the fitting values of several fitting test criteria are integrated into a comprehensive evaluation value through entropy method and MCDM technology. The threshold corresponding to the minimum comprehensive evaluation value is assumed as the optimal threshold. A random simulation study is carried out to evaluate the performance of the method and to compare them with other literature methods. Genuine load data are applied the proposed method. Both the results shown that the proposed method could be seen as an additional method that complements existing threshold selection methods.

scholarly journals Optimization of a Multiple Injection System in a Marine Diesel Engine through a Multiple-Criteria Decision-Making Approach

2020 ◽  
Vol 8 (11) ◽  
pp. 946 ◽  
Author(s):  
Maria Isabel Lamas ◽  
Laura Castro-Santos ◽  
Carlos G. Rodriguez
Keyword(s):  
Decision Making ◽  
Standard Deviation ◽  
Diesel Engine ◽  
Multiple Criteria Decision Making ◽  
Entropy Method ◽  
Multiple Criteria ◽  
Injection System ◽  
Marine Diesel Engine ◽  
Weighting Method ◽  
Marine Diesel

In this work, a numerical model was developed to analyze the performance and emissions of a marine diesel engine, the Wärtsilä 6L 46. This model was validated using experimental measurements and was employed to analyze several pre-injection parameters such as pre-injection rate, duration, and starting instant. The modification of these parameters may lead to opposite effects on consumption and/or emissions of nitrogen oxides (NOx), carbon monoxide (CO), and hydrocarbons (HC). According to this, the main goal of the present work is to employ a multiple-criteria decision-making (MCDM) approach to characterize the most appropriate injection pattern. Since determining the criteria weights significantly influences the overall result of a MCDM problem, a subjective weighting method was compared with four objective weighting methods: entropy, CRITIC (CRiteria Importance Through Intercriteria Correlation), variance, and standard deviation. The results showed the importance of subjectivism over objectivism in MCDM analyses. The CRITIC, variance, and standard deviation methods assigned more importance to NOx emissions and provided similar results. Nevertheless, the entropy method assigned more importance to consumption and provided a different injection pattern.

Developing MCDM Approach Based on GRA and TOPSIS

2010 ◽  
Vol 34-35 ◽  
pp. 1931-1935 ◽  
Author(s):  
Qi Bing Wang ◽  
An Hua Peng
Keyword(s):  
Decision Making ◽  
Comprehensive Evaluation ◽  
Multiple Criteria Decision Making ◽  
Fuzzy Comprehensive Evaluation ◽  
Multiple Criteria ◽  
Shape Similarity ◽  
Ideal Solution ◽  
Relational Analysis ◽  
Order Preference ◽  
Grey Relational

Multiple criteria decision making(MCDM) is widely used in selection from a set of available alternatives with multiple criteria, approaches to which includes fuzzy comprehensive evaluation(FCE), grey relational analysis(GRA), and technique for order preference by similarity to ideal solution(TOPSIS), and so on. First analyzes the limitations of various methods: only considering the overall effect of attribute indicators in the method of FCE, only considering the shape similarity of data curve between comparative scheme and ideal solution in GRA and only considering position approximation in TOPSIS. Second proposes a new method of comprehensive evaluation which takes into account both shape similarity and position approximation. The validity of this method has been further proved by an example of suppliers selection.

Multiple Criteria Decision Making (MCDM) Process in Selecting Location for Floating Storage and Regasification Unit (FSRU): A Case Study of Bali Island Project

2009 ◽  
Author(s):  
Ketut Buda Artana
Keyword(s):  
Decision Making ◽  
Multiple Criteria Decision Making ◽  
Entropy Method ◽  
Multiple Criteria ◽  
Total Probability ◽  
Decision Matrix ◽  
Qualitative And Quantitative ◽  
Probability Assignment ◽  
Qualitative Attribute

This paper presents a case study in selecting the best location for a Floating Storage and Regasification Unit (FSRU) in Bali. FSRU is an alternative to replace a conventional shore LNG terminal. The selection involves several criteria/attributes that can be grouped into two general attributes, namely qualitative and quantitative attribute. Multiple Criteria Decision Making (MCDM) approach is utilized to solve the selection problem, considering the capability of this method in solving multi-criteria problem with mutual conflict. Qualitative criteria is evaluated using AHP method to calculate weight of each criteria, and decision matrix algorithm is then utilized to convert preference of stakeholders into, consecutively, probability assignment, total probability assignment and preference degree. Quantitative criteria are also converted into preference degree and after combining with the preference degree of qualitative attribute, entropy method is then used to rank the alternatives. Selected location would be the alternative having the highest entropy. Four alternatives are under consideration; Benoa, Celukan Bawang, Pemaron and Gilimanuk. This research found that Celukan Bawang is the best location for the FSRU.

scholarly journals A New Grey Approach for Using SWARA and PIPRECIA Methods in a Group Decision-Making Environment

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1554
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Muzafer Saračević ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Multiple Criteria Decision Making ◽  
Grey System Theory ◽  
Multiple Criteria ◽  
Decision Making Process ◽  
Grey System ◽  
Criteria Weights

The environment in which the decision-making process takes place is often characterized by uncertainty and vagueness and, because of that, sometimes it is very hard to express the criteria weights with crisp numbers. Therefore, the application of the Grey System Theory, i.e., grey numbers, in this case, is very convenient when it comes to determination of the criteria weights with partially known information. Besides, the criteria weights have a significant role in the multiple criteria decision-making process. Many ordinary multiple criteria decision-making methods are adapted for using grey numbers, and this is the case in this article as well. A new grey extension of the certain multiple criteria decision-making methods for the determination of the criteria weights is proposed. Therefore, the article aims to propose a new extension of the Step-wise Weight Assessment Ratio Analysis (SWARA) and PIvot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods adapted for group decision-making. In the proposed approach, attitudes of decision-makers are transformed into grey group attitudes, which allows taking advantage of the benefit that grey numbers provide over crisp numbers. The main advantage of the proposed approach in relation to the use of crisp numbers is the ability to conduct different analyses, i.e., considering different scenarios, such as pessimistic, optimistic, and so on. By varying the value of the whitening coefficient, different weights of the criteria can be obtained, and it should be emphasized that this approach gives the same weights as in the case of crisp numbers when the whitening coefficient has a value of 0.5. In addition, in this approach, the grey number was formed based on the median value of collected responses because it better maintains the deviation from the normal distribution of the collected responses. The application of the proposed approach was considered through two numerical illustrations, based on which appropriate conclusions were drawn.

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