Search results for " Ranking"
showing 10 items of 50 documents
Application of the Morris method for screening the influential parameters of fuzzy controllers applied to wastewater treatment plants
2011
In this paper,we evaluate the application of a sensitivity analysis to help fine-tuning a fuzzy controller for a biological nitrogen and phosphorus removal (BNPR) plant. TheMorris Screeningmethod is proposed and evaluated as a prior step to obtain the parameter significance ranking. First, an iterative procedure has been performed in order to find out the proper repetition number of the elementary effects (r) of the method. The optimal repetition number found in this study (r = 60) is in direct contrast to previous applications of the Morris method, which usually use low repetition number, e.g. r = 10 ~ 20. Working with a non-proper repetition number (r) could lead to Type I error (identify…
Ensemble methods for item-weighted label ranking: a comparison
2022
Label Ranking (LR), an emerging non-standard supervised classification problem, aims at training preference models that order a finite set of labels based on a set of predictor features. Traditional LR models regard all labels as equally important. However, in many cases, failing to predict the ranking position of a highly relevant label can be considered more severe than failing to predict a trivial one. Moreover, an efficient LR classifier should be able to take into account the similarity between the items to be ranked. Indeed, swapping two similar elements should be less penalized than swapping two dissimilar ones. The contribution of the present paper is to formulate more flexible item…
Fair Pairwise Learning to Rank
2020
Ranking algorithms based on Neural Networks have been a topic of recent research. Ranking is employed in everyday applications like product recommendations, search results, or even in finding good candidates for hiring. However, Neural Networks are mostly opaque tools, and it is hard to evaluate why a specific candidate, for instance, was not considered. Therefore, for neural-based ranking methods to be trustworthy, it is crucial to guarantee that the outcome is fair and that the decisions are not discriminating people according to sensitive attributes such as gender, sexual orientation, or ethnicity.In this work we present a family of fair pairwise learning to rank approaches based on Neur…
New Flexible Probability Distributions for Ranking Data
2015
Recently, several models have been proposed in literature for analyzing ranks assigned by people to some object. These models summarize the liking feeling for this object, possibly also with respect to a set of explanatory variables. Some recent works have suggested the use of the Shifted Binomial and of the Inverse Hypergeometric distribution for modelling the approval rate, while mixture models have been developed for taking into account the uncertainty of the ranking process. We propose two new probabilistic models, based on the Discrete Beta and the Shifted-Beta Binomial distributions, that ensure much flexibility and allow the joint modelling of the scale (approval rate) and the shape …
General Overview
2016
Il capitolo introduce alla tematica smart city attraverso un exscursus storico che ne traccia i passaggi salienti: la nascita delle politiche globali ambientali sino al livello della maturità raggiunto con il Protocollo di Kyoto (1997); poi ancora il Pacchetto Clima 20-20-20 redatto dalla Commissione Europea nel 2008 che traccia un'altro punto cruciale che prelude ai progetti e alle iniziative in ambito smart cities. La Strategia Energetica Europea al 2050 rappresenta il quadro di riferimento a cui tendere. Il capitolo si conclude con una rassegna dei sistemi di ranking più popolari e con una proposta di analisi. The chapter introduces to smart city issue through a historical excursus, whic…
Universities' Reporting on SDGs: Using THE Impact Rankings to Model and Measure Their Contribution to Sustainability
2021
Higher education institutions (HEIs) have voiced growing concerns about sustainability issues since Agenda 2030 was approved, but this is not enough for societal stakeholders seeking and delivering innovation and excellence. The 17 Sustainable Development Goals (SDGs) were adopted by all UN Member States in 2015 as a universal call to action, and pose a challenge for HEIs as for the efforts made to fulfill them and knowing how to assess their performance. However, the metric management system implemented by HEIs quickly led to rankings emerging, which compare HEIs to metrics not related to the sustainability dimensions of the 17 SDGs. The main aim of the paper is to assess the level of repo…
Alcune considerazioni sul processo di costruzione degli indicatori composti
2008
In questo lavoro si illustra il processo di costruzione di un indicatore composto, espresso nella forma IC = f[T1(x1), T2(x2), …, TJ(xJ)], dove IC è l’indicatore composto, xj sono gli indicatori semplici, Tj sono le trasformazioni e f è la funzione di aggregazione. L’obiettivo del lavoro concerne due aspetti: il primo è l’analisi delle proprietà statistiche e matematiche delle Tj per tentare di individuare misure delle loro performance (per es. variabilità, resistenza, etc.), condizionatamente alla natura dei dati; il secondo è fornire indicazioni circa l’adeguatezza di alcune Tj non lineari, basate sui ranghi e molto usate in pratica, per costruire un buon indicatore composto.
On some flaws of university rankings: The example of the SCImago report
2012
International audience; Using France as our main example, we show there is a much scope for improving the SCImago ranking. We detect problems of nomenclature, double affiliation, aggregation and of bias toward large public-funded research organizations. The output per scholar is more important than the output per organization. The examples we cite suggest that only detailed knowledge of the situation can help in addressing the issue and take us beyond any automatic reading of the metadata.
Creating Individual Journal Rankings Based on a Community Approach
2010
Selecting appropriate publication outlets is crucial to any researcher. Journal rankings can be used to guide the selection, but their usefulness may be limited for particular audiences. In this paper, it is argued that especially young researchers and researchers in interdisciplinary fields can benefit from targeting research efforts to a specific community. This can be facilitated by an individually built journal ranking that exploits a community building perspective and by a more transparent process of use. The approach introduced here is based on an analysis of both traditional journal rankings and behavior of academic communities. As a result, we present a procedure for building and us…
A comparison of ensemble algorithms for item-weighted Label Ranking
2023
Label Ranking (LR) is a non-standard supervised classification method with the aim of ranking a finite collection of labels according to a set of predictor variables. Traditional LR models assume indifference among alternatives. However, misassigning the ranking position of a highly relevant label is frequently regarded as more severe than failing to predict a trivial label. Moreover, switching two similar alternatives should be considered less severe than switching two different ones. Therefore, efficient LR classifiers should be able to take into account the similarities and individual weights of the items to be ranked. The contribution of this paper is to formulate and compare flexible i…