Research on Recommendation System Selection Based on Fuzzy VIKOR with Multiple Distances

2014 ◽  
Vol 598 ◽  
pp. 481-485 ◽  
Author(s):  
Bao Wen Sun ◽  
Ming Li ◽  
Wei Zhang
Keyword(s):  
Hausdorff Distance ◽  
Euclidean Distance ◽  
Recommendation System ◽  
Hamming Distance ◽  
Evaluation Criteria ◽  
Calculation Methods ◽  
Distance Calculation ◽  
Fuzzy Vikor ◽  
Mcdm Method ◽  
System Selection

Nowadays, there are several different kinds of methodology in selecting recommendation systems (CRS), and every method has its own evaluation criteria to pick up the best one. In this paper, a new MCDM method for recommendation system selection based on fuzzy VIKOR with multiple distances is introduced. It selects the best system by calculating values using three different distance calculation methods, which are Hamming distance, Euclidean distance and Hausdorff distance, and voting via Condorcet method. It minimizes the effect of distance and offers a more objective result than other methods and helps enterprises to select the most suitable recommendation system.

Evidence Theory of One-Dimensional Compression KNN Classification Method

2010 ◽  
Vol 143-144 ◽  
pp. 1337-1341
Author(s):  
Wei Feng Yan ◽  
Gen Xiu Wu ◽  
Can Ze Li ◽  
Li Zhou
Keyword(s):  
Euclidean Distance ◽  
Evidence Theory ◽  
Numerical Data ◽  
Calculation Methods ◽  
Data Set ◽  
One Dimensional ◽  
Actual Distance ◽  
Distance Calculation ◽  
New Methods ◽  
Knn Classification

As only using Euclidean distance KNN algorithm has its limits, many researchers use other distance calculation methods as the replacement it to improve the accuracy of Data Classification. While combining the DS evidence theory with a series of KNN algorithm which discussed in this paper, we found that every algorithm has their merits. All of them ignore the analysis of the data set, through deeply analysis we found that the actual distance is determined by the larger value when two attribute values are in great difference. Therefore, what we do next is to compress the large-dimensional numerical data values. By this way, the accuracy of KNN, VSMKNN, KERKNN algorithm are obviously improved after experiment and then these new methods are called CDSKNN, CDSVSMKNN, CDSKERKNN.

AN OVERVIEW OF DISTANCE AND SIMILARITY MEASURES OF INTUITIONISTIC FUZZY SETS

2008 ◽  
Vol 16 (04) ◽  
pp. 529-555 ◽  
Author(s):  
Z. S. XU ◽  
J. CHEN
Keyword(s):  
Fuzzy Sets ◽  
Hausdorff Distance ◽  
Euclidean Distance ◽  
Hamming Distance ◽  
Similarity Measures ◽  
Intuitionistic Fuzzy Sets ◽  
Comprehensive Overview ◽  
Intuitionistic Fuzzy ◽  
Distance Model ◽  
Short Time

The Intuitionistic Fuzzy Sets (IFSs), originated by Atanassov [1], is a useful tool to deal with vagueness and ambiguity. In the short time since their first appearance, many different distance and similarity measures of IFSs have been proposed, but they are scattered through the literature. In this paper, we give a comprehensive overview of distance and similarity measures of IFSs. Based on the weighted Hamming distance, the weighted Euclidean distance, and the weighted Hausdorff distance, respectively, we define some continuous distance and similarity measures for IFSs. We also utilize geometric distance model to define some continuous distance and similarity measures for IFSs, which are the various combinations and generalizations of the weighted Hamming distance, the weighted Euclidean distance and the weighted Hausdorff distance. Then we extend these distance and similarity measures for Interval-Valued Intuitionistic Fuzzy Sets (IVIFSs).

Efficient Hausdorff Distance Calculation Algorithm Based on Z-Order and Octree

2018 ◽  
Vol 30 (10) ◽  
pp. 1794
Author(s):  
Dejun Zhang ◽  
Fazhi He ◽  
Long Tian ◽  
Zhuyang Xie ◽  
Lu Zou
Keyword(s):  
Hausdorff Distance ◽  
Calculation Algorithm ◽  
Distance Calculation

ERP selection using picture fuzzy CODAS method

2021 ◽  
pp. 1-11
Author(s):  
Hacer Yumurtacı Aydoğmuş ◽  
Eren Kamber ◽  
Cengiz Kahraman
Keyword(s):  
Decision Analysis ◽  
Fuzzy Sets ◽  
Fuzzy Numbers ◽  
Ideal Solution ◽  
Application Area ◽  
Erp System ◽  
Mcdm Method ◽  
Negative Ideal Solution ◽  
Picture Fuzzy Sets ◽  
System Selection

The purpose of this study is to develop an extension of CODAS method using picture fuzzy sets. In this respect, a new methodology is introduced to figure out how picture fuzzy numbers can be applied to CODAS method. COmbinative Distance-based Assessment (CODAS) is a new MCDM method proposed by Ghorabaee et al. Picture fuzzy sets (PFSs) are a new extension of ordinary fuzzy sets for representing human’s judgments having possibility more than two answers such as yes, no, refusal and neutral. Compared with other studies, the proposed method integrates multi-criteria decision analysis with picture fuzzy uncertainty based on Euclidean and Taxicab distances and negative ideal solution. ERP system selection problem is handled as the application area of the developed method, picture fuzzy CODAS. Results indicate that the new proposed method finds meaningful rankings through picture fuzzy sets. Comparative analyzes show that the presented method gives successful and robust results for the solutions of MCDM problems under fuzziness.

scholarly journals Wind Turbine Fault Diagnosis by the Approach of SCADA Alarms Analysis

2021 ◽  
Vol 12 (1) ◽  
pp. 69
Author(s):  
Lu Wei ◽  
Zheng Qian ◽  
Yan Pei ◽  
Jingyue Wang
Keyword(s):  
Fault Diagnosis ◽  
Wind Turbine ◽  
Euclidean Distance ◽  
Wind Farm ◽  
Hamming Distance ◽  
Fault Identification ◽  
Farm Operators ◽  
One Year ◽  
The Right ◽  
Better Than

Wind farm operators are overwhelmed by a large amount of supervisory control and data acquisition (SCADA) alarms when faults occur. This paper presents an online root fault identification method for SCADA alarms to assist operators in wind turbine fault diagnosis. The proposed method is based on the similarity analysis between an unknown alarm vector and the feature vectors of known faults. The alarm vector is obtained from segmented alarm lists, which are filtered and simplified. The feature vector, which is a unique signature representing the occurrence of a fault, is extracted from the alarm lists belonging to the same fault. To mine the coupling correspondence between alarms and faults, we define the weights of the alarms in each fault. The similarities is measured by the weighted Euclidean distance and the weighted Hamming distance, respectively. One year of SCADA alarms and maintenance records are used to verify the proposed method. The results show that the performance of the weighted Hamming distance is better than that of the weighted Euclidean distance; 84.1% of alarm lists are labeled with the right root fault.

scholarly journals Review of Existing Energy Retrofit Decision Tools for Homeowners

2021 ◽  
Vol 13 (18) ◽  
pp. 10189
Author(s):  
Mohammed Seddiki ◽  
Amar Bennadji ◽  
Richard Laing ◽  
David Gray ◽  
Jamal M. Alabid
Keyword(s):  
Financial Support ◽  
Current Knowledge ◽  
Evaluation Criteria ◽  
Data Driven ◽  
Energy Calculation ◽  
Calculation Methods ◽  
Decision Tools ◽  
Energy Retrofit ◽  
The Impact

Energy retrofit tools are considered by many countries as one of the strongest incentives to encourage homeowners to invest in energy renovation. These tools help homeowners to get an initial overview of suitable retrofit measures. Although a large number of energy retrofit tools have been developed to inspire and educate homeowners, energy renovation by individual homeowners is still lagging and the impact of current tools is insufficient as awareness and information issues remain one of main obstacles that hinder the uptake of energy retrofitting schemes. This research extends the current knowledge by analysing the characteristics of 19 tools from 10 different countries. The selected tools were analysed in terms of energy calculation methods, features, generation and range of retrofit measures, evaluation criteria, and indications on financial support. The review indicates that: (1) most toolkits use empirical data-driven methods, pre-simulated databases, and normative calculation methods; (2) few tools generate long-term integrated renovation packages; (3) technological, social, and aesthetic aspects are rarely taken into consideration; (4) the generation of funding options varies between the existing tools; (5) most toolkits do not suggest specific retrofit solutions adapted to traditional buildings; and (6) preferences of homeowners in terms of evaluation criteria are often neglected.

Interval Rough Neutrosophic TOPSIS Strategy for Multi-Attribute Decision Making

2020 ◽  
pp. 98-118
Author(s):  
Rumi Roy ◽  
Surapati Pramanik ◽  
Tapan Kumar Roy
Keyword(s):  
Decision Making ◽  
Euclidean Distance ◽  
Hamming Distance ◽  
Ideal Solution ◽  
Numerical Example ◽  
New Strategy ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Ranking Order ◽  
Negative Ideal Solution

In this chapter, the authors present a new strategy for multi-attribute decision making in interval rough neutrosophic environment. They define Hamming distance and Euclidean distance between interval rough neutrosophic numbers. They also define interval rough neutrosophic relative positive ideal solution (IRNRPIS) and interval rough neutrosophic relative negative ideal solution (IRNRNIS). Then the ranking order of the alternatives is obtained by the technique for order preference by similarity to ideal solution (TOPSIS) strategy. Finally, a numerical example is provided to demonstrate the applicability and effectiveness of the proposed interval rough neutrosophic TOPSIS strategy.

Selecting an Advertising Agency: A Multi-Criteria Decision Making Approach

2008 ◽  
Vol 12 (4) ◽  
pp. 13-22 ◽  
Author(s):  
Mohd. Nishat Faisal ◽  
Bilal Mustafa Khan
Keyword(s):  
Decision Making ◽  
Evaluation Criteria ◽  
Multiple Criteria Decision Making ◽  
Analytic Network Process ◽  
Advertising Agency ◽  
Product Service ◽  
Proposed Model ◽  
Network Process ◽  
Product Personality ◽  
Mcdm Method

Indian economy is evolving day by day, and with an upswing spending power of its inhabitants advertising has been emerging as one of the most effective tools for the companies to reach out to their customers. Best advertisement agencies create value through giving the product personality, developing an understanding of product/service, creating an image or memorable picture of that product and above all trying to distinguish the product apart from its competitors. Today, advertising budgets of companies are rising and thus there are numerous agencies in the market vying for their shares. But there exists no method, which can take into account numerous criterions and their impact simultaneously under consideration while selecting a best advertisement agency. Selecting an advertisement agency is a multiple criteria decision-making (MCDM) problem that requires considering large number of complex factors as multiple evaluation criteria. A robust MCDM method should consider the interactions among criteria. Analytic network process (ANP) is a relatively new MCDM method which can deal with all kinds of interactions systematically. This paper proposes an ANP based methodology for the selection of advertisement agencies. ANP is capable of measuring the relative importance that captures all indirect interactions in a network required to be considered in an advertisement agency selection and also their interactions. Additionally, the proposed model is evaluated for a case company.

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