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Irene Poli
Researcher at Ca' Foscari University of Venice
Publications - 93
Citations - 1030
Irene Poli is an academic researcher from Ca' Foscari University of Venice. The author has contributed to research in topics: Protocell & Artificial neural network. The author has an hindex of 17, co-authored 91 publications receiving 964 citations.
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A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices
TL;DR: In this paper, the problem of designing new energy-efficient static daylight devices that will surround the external windows of a residential building in Madrid is addressed, and a multi-objective optimization methodology based on Harmony Search and Pareto front approaches is proposed.
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Optimised design of energy efficient building façades via Evolutionary Neural Networks
TL;DR: In this article, an Evolutionary Neural Network Design (ENN-Design) has been adopted to drive the design of a typical facade module for an office building and both single-objective and multiobjective optimisations have been carried out.
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A Neural Net Model for Prediction
Irene Poli,Roger Jones +1 more
TL;DR: A Bayesian inferential procedure for this model, based on the Kalman filter, is derived, and the resulting learning algorithm generalizes the so-called onedimensional Newton method, an updating algorithm currently popular in the neural net literature.
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A stochastic model of the emergence of autocatalytic cycles
Alessandro Filisetti,Alex Graudenzi,Roberto Serra,Marco Villani,Davide De Lucrezia,Rudolf Marcel Füchslin,Stuart A. Kauffman,Norman H. Packard,Irene Poli +8 more
TL;DR: A novel stochastic model of catalytic reaction networks is introduced, in order to investigate the emergence of autocatalytic cycles, sensibly considering the importance of noise, of small-number effects and the possible growth of the number of different elements in the system.
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Sufficient conditions for emergent synchronization in protocell models.
TL;DR: General protocell models aiming to understand the synchronization phenomenon of genetic material and container productions are studied, a necessary condition to ensure sustainable growth in protocells and eventually leading to Darwinian evolution when applied to a population of protocells.