Search results for "Ensemble"

Performance assessment of individual and ensemble data-mining techniques for gully erosion modeling

2017

Gully erosion is identified as an important sediment source in a range of environments and plays a conclusive role in redistribution of eroded soils on a slope. Hence, addressing spatial occurrence pattern of this phenomenon is very important. Different ensemble models and their single counterparts, mostly data mining methods, have been used for gully erosion susceptibility mapping; however, their calibration and validation procedures need to be thoroughly addressed. The current study presents a series of individual and ensemble data mining methods including artificial neural network (ANN), support vector machine (SVM), maximum entropy (ME), ANN-SVM, ANN-ME, and SVM-ME to map gully erosion …

Fuzzy mathematic models in economy

1986

Ce papier présente un "survey" de trois modèles mathématiques flous traitant du choix économique, du calcul économique et de l'équilibre économique général. Ces modèles constituent ensemble les éléments d'une théorie de la valeur floue. Le but de cette étude est de vérifier l'efficacité de l'application de la théorie des sous-ensembles flous à l'analyse des fondements de l'économie et ainsi de légitimer son emploi dans cette discipline.

Modeling the Mechanical Behavior of the Breast Tissues Under Compression in Real Time

2017

This work presents a data-driven model to simulate the mechanical behavior of the breast tissues in real time. The aim of this model is to speed up some multimodal registration algorithms, as well as some image-guided interventions. Ten virtual breast phantoms were used in this work. Their deformation during a mammography was performed off-line using the finite element method. Three machine learning models were trained with the data from those simulations. Then, they were used to predict the deformation of the breast tissues. The models were a decision tree and two ensemble methods (extremely randomized trees and random forest). Four experiments were designed to assess the performance of th…

An Integrated fuzzy Cells-classifier

2006

The term soft-computing has been introduced by Zadeh in 1994. Soft-computing provides an appropriate paradigm to program malleable and smooth concepts. In this paper a genetic algorithm is proposed to fuse the classification results due to different distance functions. The combination is based on the optimization of a vote strategy and it is applied to cells classification.

An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian Regions

2020

Abstract The availability of intensive care beds during the COVID‐19 epidemic is crucial to guarantee the best possible treatment to severely affected patients. In this work we show a simple strategy for short‐term prediction of COVID‐19 intensive care unit (ICU) beds, that has proved very effective during the Italian outbreak in February to May 2020. Our approach is based on an optimal ensemble of two simple methods: a generalized linear mixed regression model, which pools information over different areas, and an area‐specific nonstationary integer autoregressive methodology. Optimal weights are estimated using a leave‐last‐out rationale. The approach has been set up and validated during t…

Topological effects of a rigid chiral spacer on the electronic interactions in donor-acceptor ensembles

2005

Two triads (donor-spacer-acceptor), etTTF-BN-C 6 0 (6) and ZnP-BN-C 6 0 (7), in which electron donors (i.e., exTTF or ZnP) are covalently linked to C 6 0 through a chiral binaphthyl bridge (BN), have been prepared in a multistep synthetic procedure starting from a highly soluble enantiomerically pure binaphthyl building block (1). Unlike other oligomeric bridges, with hinaphthyl bridges, the conjugation between the donor and the acceptor units is broken and geometric conformational changes are facilitated. Consequently, distances and electronic interactions between the donor and C 6 0 are drastically changed. Both donor-spacer-acceptor (D-s-A) systems (i.e., 6 and 7) exhibit redox processes…

A genetic integrated fuzzy classifier

2005

This paper introduces a new classifier, that is based on fuzzy-integration schemes controlled by a genetic optimisation procedure. Two different types of integration are proposed here, and are validated by experiments on real data sets of biological cells. The performance of our classifier is tested against a feed-forward neural network and a Support Vector Machine. Results show the good performance and robustness of the integrated classifier strategies.

2020

Recommender systems are information software that retrieves relevant items for users from massive sources of data. The variational autoencoder (VAE) has proven to be a promising approach for recommendation systems, as it can explore high-level user-item relations and extract contingencies from the input effectively. However, the previous variants of VAE have so far seen limited application to domain-specific recommendations that require additional side information. Hence, The Ensemble Variational Autoencoder framework for recommendations (EnsVAE) is proposed. This architecture specifies a procedure to transform sub-recommenders’ predicted utility matrix into interest probabilities that allo…

Phase behaviour of heteronuclear dimers in three-dimensional systems—a Monte Carlo study

2008

Monte Carlo simulation in the grand canonical ensemble, the histogram reweighting technique and finite size scaling are used to study the phase behaviour of dimers in three-dimensional systems. A single molecule is composed of two segments A and B, and the bond between them cannot be broken. The phase diagrams have been estimated for a set of model systems. Different structures formed by heteronuclear dimers have been found. The results show a great variety of vapour–liquid coexistence behaviour depending on the strength of the interactions between segments.

TBSSvis: Visual Analytics for Temporal Blind Source Separation

2020

Temporal Blind Source Separation (TBSS) is used to obtain the true underlying processes from noisy temporal multivariate data, such as electrocardiograms. TBSS has similarities to Principal Component Analysis (PCA) as it separates the input data into univariate components and is applicable to suitable datasets from various domains, such as medicine, finance, or civil engineering. Despite TBSS’s broad applicability, the involved tasks are not well supported in current tools, which offer only text-based interactions and single static images. Analysts are limited in analyzing and comparing obtained results, which consist of diverse data such as matrices and sets of time series. Additionally, p…