Search results for "Neural"

Assessment of indoor illuminance and study on best photosensors' position for design and commissioning of Daylight Linked Control Systems. A new meth…

2018

Abstract Artificial lighting systems have to ensure appropriate illuminance with high energy efficiency according to best design practice and technical standards. These aims can be tackled, by incorporating a Daylight linked control system. However, the system behaviour is strongly influenced by several factors and, in particular, by the sensors' position. Indeed, very often the illuminance on work-plane is not fully correlated with illuminance measured by the photo-sensor used to control the luminaires. This fact leads to wrong information for the Daylight linked control systems affecting its efficacy. The artificial intelligence of Neural Networks can be exploited to provide a method for …

Forecasting noise levels by means of neural networks for assessing urban traffic policies

2005

Within the assessment of the sustainability of plans and actions concerning the built environment, the transportation sector plays an increasing role, due to its importance in the economic and social life of countries. As that, the analysis of the sustainability concerning the transportation sector is now often embodied into the so called Strategic Environmental Analyses (SEA), that should provide local administrators with easy criteria for ranking the environmental suitability of designing policies, and that would seem to encounter the needed features for a correct evaluation of the urban masterplan. The urban noise forecast is very useful for local administrations, which have presently to…

Analisi e modelli predittivi di sistemi energetici a scala regionale, provinciale e locale: studi sperimentali, modellazione e analisi parametrica.

Il lavoro ha affrontato differenti ambiti tipici della pianificazione energetica, dell’analisi di dati e dei modelli predittivi. Tutti i predetti temi sono coniugati al fine di studiare le caratteristiche dei sistemi energetici, i bilanci energetici a scala regionale e locale, di valutare gli indicatori di efficienza dei sistemi su macro area utilizzando metodi statistici e previsionali. A tal fine sono stati applicati modelli e software predittivi basati su metodi di regressione e/o Neural Network per la predisposizione di scenari energetici a breve, medio e lungo termine. Nel complesso, il lavoro ha riguardato l’implementazione ed analisi di modelli numerici, in grado di determinare in ma…

A Neural Network Model to Forecast Urban Electricity Consumptions from Weather Data

2004

Analisi statistica dei regimi di vento e di producibilità di un impianto eolico sito in Sicilia. Stima di previsione della producibilità eolica attra…

2010

A neural classifier for the optimal selection of conduction transfer functions

2008

Improving Irony and Stereotype Spreaders Detection using Data Augmentation and Convolutional Neural Network

2022

In this paper we describe a deep learning model based on a Data Augmentation (DA) layer followed by a Convolutional Neural Network (CNN). The proposed model was developed by our team for the Profiling Irony and Stereotype Spreaders (ISSs) task proposed by the PAN 2022 organizers. As a first step, to classify an author as ISS or not (nISS), we developed a DA layer that expands each sample in the dataset provided. Using this augmented dataset we trained the CNN. Then, to submit our predictions, we apply our DA layer on the samples within the unlabeled test set too. Finally we fed our trained CNN with the augmented test set to generate our final predictions. To develop and test our model we us…

Adaptive Feed-Forward Neural Network for Wind Power Delivery

2022

This paper describes a grid connected wind energy conversion system. The interconnecting filter is a simple inductor with a series resistor to minimize three-phase current Total Harmonic Distortion (THD). Using the Recursive Least Squares (RLS) Estimator, an online grid impedance technique is proposed in the stationary reference frame using the Recursive Least Squares (RLS) Estimator. An Adaptive Feedforward Neural (AFN) Controller has also been developed using the inverse of the system to improve the performance of the current Proportional-Integral controller under dynamical conditions and provide better DC link voltage stability. The neural network weights are computed in real-time using …

Deep Motion Model for Pedestrian Tracking in 360 Degrees Videos

2019

This paper proposes a deep convolutional neural network (CNN) for pedestrian tracking in 360◦ videos based on the target’s motion. The tracking algorithm takes advantage of a virtual Pan-Tilt-Zoom (vPTZ) camera simulated by means of the 360◦ video. The CNN takes in input a motion image, i.e. the difference of two images taken by using the vPTZ camera at different times by the same pan, tilt and zoom parameters. The CNN predicts the vPTZ camera parameter adjustments required to keep the target at the center of the vPTZ camera view. Experiments on a publicly available dataset performed in cross-validation demonstrate that the learned motion model generalizes, and that the proposed tracking algo…

Real-Time Visual Grasp Synthesis Using Genetic Algorithms and Neural Networks

2007

This paper addresses the problem of automatic grasp synthesis of unknown planar objects. In other words, we must compute points on the object’s boundary to be reached by the robotic fingers such that the resulting grasp, among infinite possibilities, optimizes some given criteria. Objects to be grasped are represented as superellipses, a family of deformable 2D parametric functions. They can model a large variety of shapes occurring often in practice by changing a small number of parameters. The space of possible grasp configurations is analyzed using genetic algorithms. Several quality criteria from existing literature together with kinematical and mechanical considerations are considered.…