The Pairwise Comparison Model: The Multiplicative and the Additive Approach

2006 ◽  
pp. 70-80
Author(s):  
Antonio Jesús Herencia-Leva ◽  
M. Teresa Lamata ◽  
Cristino Pérez-Meléndez
Keyword(s):  
Pairwise Comparison ◽  
Comparison Model

On Moderate Fuzzy Analytic Hierarchy Process Pairwise Comparison Model With Subcriteria

2016 ◽  
Vol 2 (3) ◽  
pp. 54
Author(s):  
G. Marimuthu ◽  
G. Ramesh
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
Fuzzy Ahp ◽  
Pairwise Comparison ◽  
Decision Models ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analysis Method ◽  
Analytic Hierarchy ◽  
Comparison Model ◽  
Hierarchy Process

Decisions usually involve the getting the best solution, selecting the suitable experiments, most appropriate judgments, taking the quality results etc., using some techniques.  Every decision making can be considered as the choice from the set of alternatives based on a set of criteria.  The fuzzy analytic hierarchy process is a multi-criteria decision making and is dealing with decision making problems through pairwise comparisons mode [10].  The weight vectors from this comparison model are obtained by using extent analysis method.  This paper concern with an alternate method of finding the weight vectors from the original fuzzy AHP decision model (moderate fuzzy AHP model), that has the same rank as obtained in original fuzzy AHP and ideal fuzzy AHP decision models.

Predicting the NCAA basketball tournament using isotonic least squares pairwise comparison model

2018 ◽  
Vol 14 (4) ◽  
pp. 173-183 ◽  
Author(s):  
Ayala Neudorfer ◽  
Saharon Rosset
Keyword(s):  
Machine Learning ◽  
Least Squares ◽  
Linear Relationship ◽  
Logistic Models ◽  
Pairwise Comparison ◽  
Previous Knowledge ◽  
Suggested Model ◽  
College Basketball ◽  
Comparison Model ◽  
Better Than

Abstract Each year, millions of people fill out a bracket to predict the outcome of the popular NCAA men’s college basketball tournament, known as March Madness. In this paper we present a new methodology for team ranking and use it to predict the NCAA basketball tournament. We evaluate our model in Kaggle’s March Machine Learning Mania competition, in which contestants were required to predict the results of all possible games in the tournament. Our model combines two methods: the least squares pairwise comparison model and isotonic regression. We use existing team rankings (such as seeds, Sagarin and Pomeroy ratings) and look for a monotonic, non-linear relationship between the ranks’ differences and the probability to win a game. We use the isotonic property to get new rankings that are consistent with both the observed outcomes of past tournaments and previous knowledge about the order of the teams. In the 2016 and 2017 competitions, submissions based on our methodology consistently placed in the top 5% out of over 800 other submissions. Using simulations, we show that the suggested model is usually better than commonly used linear and logistic models that use the same variables.

Penilaian Kinerja Dosen Dengan Menggunakan Metode AHP Studi Kasus di STIE Ahmad Dahlan Jakarta

Liquidity ◽  
2018 ◽  
Vol 2 (1) ◽  
pp. 100-109
Author(s):  
Ellya Sestri
Keyword(s):  
Decision Making ◽  
Performance Appraisal ◽  
Technological Progress ◽  
Pairwise Comparison ◽  
Relative Importance ◽  
Faculty Performance ◽  
Business World ◽  
The Face ◽  
Hierarchy Process ◽  
Rule Out

An increasingly rapid technological progress in the era of globalization in the business world, so do not rule out the possibility that a decision-making is something that is very vital in determining the decisions to be taken in the face of competitive business world. Decision making can be influenced by several aspects, this can affect the speed of decision making by the decision maker in which decisions must be quick and accurate. Lecturer Performance Assessment Using the Analytical Hierarchy Process is a decision support system that aims to assess faculty performance according to certain criteria. This system of faculty performance appraisal criteria to map a hierarchy, where each hierarchy will be performed pairwise comparison, the pairwise comparisons between criteria, so to get a comparison of the relative importance of criteria with each other. The results of this comparison is then analyzed to obtain the priority of each criterion. Once completed and performed an assessment of alternative options to be compared and calculated to obtain the best alternatives according to established criteria.

DETERMINING THE DESALINATION UNIT COMPOSITION FOR COSTAL AREAS AND SMALL ISLANDS USE ANALYTIC HIERARCHY PROCESS

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Imam Setiadi ◽  
Dinda Rita K. Hartaja
Keyword(s):  
Analytic Hierarchy Process ◽  
Energy Demand ◽  
Pairwise Comparison ◽  
Small Islands ◽  
Ahp Method ◽  
Analytic Hierarchy ◽  
Comparison Research ◽  
Hierarchy Process ◽  
Selection Of

Selection of the appropriate composition desalination units can be done with a variety of method approaches, one of the method is the Analytic Hierarchy Process. In determining the desalination unit with AHP method to consider is setting a goal, an alternative criteria and pairwise comparison. Research for the determination of the exact composition of the desalination unit in order to achieve sustainable drinking water suppy in coastal areas and small islands has been conducted. The results of the study are as follows, the energy demand of 50.83%, operator costs of 26.64%, maintenance costs of 14.13% and chemical requirement 8.4%. For an alternative composition desalination unit of RO 10 m3 / day is the best alternative composition with value of 59.61%, the composition of the next alternative is RO 20 m3/ day of 30.40% and the last alternative of the desalination unit composition is RO 120 m3/ day of 09.99%.Key words : Desalination, Mukti Stage Flash Composition, AHP

Model and Method for Contributor’s Quality Assessment in Community Image Tagging Systems

2018 ◽  
pp. 45-51
Author(s):  
A. V. Ponomarev
Keyword(s):  
Large Scale ◽  
Wide Spectrum ◽  
Preference Relation ◽  
Pairwise Comparison ◽  
Ground Truth ◽  
Comparison Method ◽  
Characteristic Matrix ◽  
Image Tagging ◽  
Proposed Model

Introduction: Large-scale human-computer systems involving people of various skills and motivation into the information processing process are currently used in a wide spectrum of applications. An acute problem in such systems is assessing the expected quality of each contributor; for example, in order to penalize incompetent or inaccurate ones and to promote diligent ones.Purpose: To develop a method of assessing the expected contributor’s quality in community tagging systems. This method should only use generally unreliable and incomplete information provided by contributors (with ground truth tags unknown).Results:A mathematical model is proposed for community image tagging (including the model of a contributor), along with a method of assessing the expected contributor’s quality. The method is based on comparing tag sets provided by different contributors for the same images, being a modification of pairwise comparison method with preference relation replaced by a special domination characteristic. Expected contributors’ quality is evaluated as a positive eigenvector of a pairwise domination characteristic matrix. Community tagging simulation has confirmed that the proposed method allows you to adequately estimate the expected quality of community tagging system contributors (provided that the contributors' behavior fits the proposed model).Practical relevance: The obtained results can be used in the development of systems based on coordinated efforts of community (primarily, community tagging systems). 

scholarly journals Reclassification of Kidney Clear Cell Carcinoma Based on Immune Cell Gene-Related DNA CpG Pairs

Biomedicines ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 215
Author(s):  
Qizhan Luo ◽  
Thomas-Alexander Vögeli
Keyword(s):  
Cell Carcinoma ◽  
Immune Cell ◽  
Clear Cell ◽  
Clear Cell Carcinoma ◽  
Pairwise Comparison ◽  
Clinicopathological Features ◽  
Immune Checkpoints ◽  
Potential Mechanism ◽  
Tissue Samples

Background: A new method was developed based on the relative ranking of gene expression level, overcoming the flaw of the batch effect, and having reliable results in various studies. In the current study, we defined the two methylation sites as a pair. The methylation level in a specific sample was subject to pairwise comparison to calculate a score for each CpGs-pair. The score was defined as a CpGs-pair score. If the first immune-related CpG value was higher than the second one in a specific CpGs-pair, the output score of this immune-related CpGs-pair was 1; otherwise, the output score was 0. This study aimed to construct a new classification of Kidney Clear Cell Carcinoma (KIRC) based on DNA CpGs (methylation sites) pairs. Methods: In this study, the biomarkers of 28 kinds of immune infiltration cells and corresponding methylation sites were acquired. The methylation data were compared between KIRC and normal tissue samples, and differentially methylated sites (DMSs) were obtained. Then, DNA CpGs-pairs were obtained according to the pairs of DMSs. In total, 441 DNA CpGs-pairs were utilized to construct a classification using unsupervised clustering analysis. We also analyzed the potential mechanism and therapy of different subtypes, and validated them in a testing set. Results: The classification of KIRC contained three subgroups. The clinicopathological features were different across three subgroups. The distribution of immune cells, immune checkpoints and immune-related mechanisms were significantly different across the three clusters. The mutation and copy number variation (CNV) were also different. The clinicopathological features and potential mechanism in the testing dataset were consistent with those in the training set. Conclusions: Our findings provide a new accurate and stable classification for developing personalized treatments for the new specific subtypes.

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