Search results for "Soft computing"
showing 10 items of 45 documents
Un algoritmo evolutivo per il posizionamento di agenti su spazi geometrici di forme arbitrarie
2014
Explicandum vs Explicatum and Soft Computing
2010
The aim of this paper is twofold. First af all I want to present some old ideas revisited in the light of some of the many interesting new developments occurred in the course of these last ten years in the field of the foundations of fuzziness. Secondly I desire to present a tentative general framework in which it is possible (or at least it is possible FOR ME) to compare different attitudes and different approaches to the clarification of the conceptual problems arising from fuzziness and soft computing.
Obtaining the Compatibility between Musicians Using Soft Computing
2010
Modeling the musical notes as fuzzy sets provides a flexible framework which better explains musicians’ daily practices. Taking into account one of the characteristics of the sound: the pitch (the frequency of a sound as perceived by human ear), a similarity relation between two notes can be defined. We call this relation compatibility. In the present work, we propose a method to asses the compatibility between musicians based on the compatibility of their interpretations of a given composition. In order to aggregate the compatibilities between the notes offered and then obtain the compatibility between musicians, we make use of an OWA operator. We illustrate our approach with a numerical e…
Fuzzy Degree of Geographic Appropriateness for Social Impact Investing
2017
Impact investing is an investment practice that is characterized by the explicit intentionality of attaining a social impact and the requisite of report and measure this impact in a transparent way. The investment decision making process has two main stages. In the first stage, filters are applied regarding four critical issues: target geography, impact theme, asset class and target return category. In this phase, the set of possible investment alternatives are determined based on their appropriateness for impact investment in terms of those four essential aspects. In a second stage, efficient portfolios are obtained taking into account financial criteria (maximizing expected return, minimi…
Regional models based on Multi-Gene Genetic Programming for the simulation of monthly runoff series
2022
Accurate estimates of runoff in river basins are useful for several applications. The use of data-driven procedures for simulating the complex runoff generation process is a promising frontier that could allow for overcoming some typical problems related to more complex traditional approaches. This study explores soft computing based regional models for the reconstruction of monthly runoff in river basins. The region under analysis is the Sicily (Italy), where a regressive rainfall-runoff model, here used as benchmark model, was previously built using data from almost a hundred gauged watersheds across the region. This previous model predicts monthly river runoff based on a unique regional,…
Performance evaluation of fuzzy-neural HTTP request distribution for Web clusters
2006
In this paper we present the performance evaluation of our fuzzy-neural HTTP request distribution algorithm called FNRD, which assigns each incoming request to the server in the Web cluster with the quickest expected response time. The fuzzy mechanism is used to estimate the expected response times. A neural-based feedback loop is used for real-time tuning of response time estimates. To evaluate the system, we have developed a detailed simulation and workload model using CSIM19 package. Our simulations show that FNRD can be more effective than its competitors.
RANKING DECISION MAKING UNITS BY MEANS OF SOFT COMPUTING DEA MODELS
2011
This paper presents a method for ranking a set of decision making units according to their level of efficiency and which takes into account uncertainty in the data. Efficiency is analysed using fuzzy DEA techniques and the ranking is based on the statistical analysis of cases that include representative situations. The method enables the removal of the sometimes unrealistic hypothesis of a perfect trade-off between increased inputs and outputs. This model is compared with other DEA models that work with imprecise or fuzzy data. As an illustration, we apply our ranking method to the evaluation of a group of Spanish seaports, as well as teams playing in the Spanish football league. We compar…
A Memetic Island Model for Discrete Tomography Reconstruction
2011
Soft computing is a term indicating a coalition of methodologies, and its basic dogma is that, in general, better results can be obtained through the use of constituent methodologies in combination, rather than in a stand alone mode. Evolutionary computing belongs to this coalition, and thus memetic algorithms. Here, we present a combination of several instances of a recently proposed memetic algorithm for discrete tomography reconstruction, based on the island model parallel implementation. The combination is motivated by the fact that, even though the results of the recently proposed approach are finally better and more robust compared to other approaches, we advised that its major drawba…
SIOPRED performance in a Forecasting Blind Competition
2012
In this paper we present the results obtained by applying our automatic forecasting support system, named SIOPRED, over a data set of time series in a Forecasting Blind Competition. In order to apply our procedure for providing point forecasts it has been necessary to develop an interactive strategy for the choice of the suitable length of the seasonal cycle and the seasonality form for a generalized exponential smoothing method, which have been obtained using SIOPRED. For the choice of those essential characteristics of forecasting methods, also a certain multi-objective formulation which minimizes several measures of fitting is used. Once these specifications are established, the model pa…
Soft computing-based aggregation methods for human resource management
2008
Abstract We are interested in the personnel selection problem. We have developed a flexible decision support system to help managers in their decision-making functions. This DSS simulates experts’ evaluations using ordered weighted average (OWA) aggregation operators, which assign different weights to different selection criteria. Moreover, we show an aggregation model based on efficiency analysis to put the candidates into an order.