Search results for "source"
showing 10 items of 6139 documents
Assessment of the Operating Temperature of Crystalline PV Modules Based on Real Use Conditions
2014
Determining the operating temperatureTcof photovoltaic panelsPVis important in evaluating the actual performance of these systems. In the literature, different correlations exist, in either explicit or implicit forms, which often do not account for the electrical behaviour of panels; in this way, estimatingTcis based only on the passive behaviour of thePV. In this paper, the authors propose a new implicit correlation that takes into account the standard weather variables and the electricity production regimes of aPVpanel in terms of the proximity to the maximum power points. To validate its reliability, the new correlation was tested on two different PV panels (Sanyo and Kyocera panels) and…
Hopfield Neural Network - Based Approach for Joint Dynamic Resource Allocation in Heterogeneous Wireless Networks
2006
This paper presents a comprehensive approach to solve the problem of joint dynamic resource allocation (JDRA) in heterogeneous wireless networks using a Hopfield neural network (HNN). A generic formulation for packet services with delay constraints is proposed to decide the optimal bit rate and radio access technology (RAT) allocation. Some illustrative simulations results in a basic scenario are presented to evaluate performance of the proposed algorithm.
Web Usage Mining by Neural Hybrid Prediction with Markov Chain Components
2021
This paper presents and evaluates a two-level web usage prediction technique, consisting of a neural network in the first level and contextual component predictors in the second level. We used Markov chains of different orders as contextual predictors to anticipate the next web access based on specific web access history. The role of the neural network is to decide, based on previous behaviour, whose predictor’s output to use. The predicted web resources are then prefetched into the cache of the browser. In this way, we considerably increase the hit rate of the web browser, which shortens the load times. We have determined the optimal configuration of the proposed hybrid predictor on a real…
An Adaptive Global-Local Memetic Algorithm to Discover Resources in P2P Networks
2007
This paper proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA) for performing the training of the neural network. This training is very challenging due to the large number of weights and noise caused by the dynamic neural network testing. The AGLMA is a memetic algorithm consisting of an evolutionary framework which adaptively employs two local searchers having different exploration logic and pivot rules. Furthermore, the AGLMA makes an adaptive noise compensation by means of explicit averaging on the fitness values and a dynamic population sizing which aims to follow the ne…
Joint Dynamic Resource Allocation for Coupled Heterogeneous Wireless Networks Based on Hopfield Neural Networks
2008
This paper proposes an algorithm to solve the problem of Joint Dynamic Resource Allocation in heterogeneous wireless networks. The algorithm is based on Hopfield Neural Networks to achieve fast and suboptimal solutions. The generic formulation is particularized and evaluated in an HSDPA and 802.11e WLAN coupled networks. Some illustrative simulations results are presented to evaluate the performance of the new algorithm as compared with other strategies. The obtained results confirm the validity of the proposal.
A Memetic-Neural Approach to Discover Resources in P2P Networks
2008
This chapter proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA) for performing in training of the neural network. The neural network, which is a multi-layer perceptron neural network, allows the P2P nodes to efficiently locate resources desired by the user. The necessity of testing the network in various working conditions, aiming to obtain a robust neural network, introduces noise in the objective function. The AGLMA is a memetic algorithm which employs two local search algorithms adaptively activated by an evolutionary framework. These local searchers, having different fe…
Human factor policy testing in the sequencing of manual mixed model assembly lines
2004
In this paper the human resource management in manual mixed model assembly U-lines is considered. The objective is to minimise the total conveyor stoppage time to achieve the full efficiency of the line. A model, that includes effects of the human resource, was developed in order to evaluate human factor policies impact on the optimal solution of this line sequencing problem. Different human resource management policies are introduced to cope with the particular layout of the proposed line. Several examples have been proposed to investigate the effects of line dimensions on the proposed management policies. The examples have been solved through a genetic algorithm. The obtained results conf…
Astrophysics with the Laser Interferometer Space Antenna
2023
Full list of authors: Amaro-Seoane, Pau; Andrews, Jeff; Sedda, Manuel Arca; Askar, Abbas.; Baghi, Quentin; Balasov, Razvan; Bartos, Imre; Bavera, Simone S.; Bellovary, Jillian; Berry, Christopher P. L.; Berti, Emanuele; Bianchi, Stefano; Blecha, Laura; Blondin, Stephane; Bogdanovic, Tamara; Boissier, Samuel; Bonetti, Matteo; Bonoli, Silvia; Bortolas, Elisa; Breivik, Katelyn; Capelo, Pedro R.; Caramete, Laurentiu; Cattorini, Federico; Charisi, Maria; Chaty, Sylvain; Chen, Xian; Chruslinska, Martyna; Chua, Alvin J. K.; Church, Ross; Colpi, Monica; D'Orazio, Daniel; Danielski, Camilla; Davies, Melvyn B.; Dayal, Pratika; De Rosa, Alessandra; Derdzinski, Andrea; Destounis, Kyriakos; Dotti, Massi…
A first search for coincident gravitational waves and high energy neutrinos using LIGO, Virgo and ANTARES data from 2007
2013
A search for high-energy neutrinos coming from the direction of the Sun has been performed using the data recorded by the ANTARES neutrino telescope during 2007 and 2008. The neutrino selection criteria have been chosen to maximize the selection of possible signals produced by the self-annihilation of weakly interacting massive particles accumulated in the centre of the Sun with respect to the atmospheric background. After data unblinding, the number of neutrinos observed towards the Sun was found to be compatible with background expectations. The 90% CL upper limits in terms of spin-dependent and spin-independent WIMP-proton cross-sections are derived and compared to predictions of two sup…
First search for neutrinos in correlation with gamma-ray bursts with the ANTARES neutrino telescope
2013
A search for neutrino-induced muons in correlation with a selection of 40 gamma-ray bursts that occurred in 2007 has been performed with the ANTARES neutrino telescope. During that period, the detector consisted of 5 detection lines. The ANTARES neutrino telescope is sensitive to TeV-PeV neutrinos that are predicted from gamma-ray bursts. No events were found in correlation with the prompt photon emission of the gamma-ray bursts and upper limits have been placed on the flux and fluence of neutrinos for different models.