Search results for " search"
showing 10 items of 654 documents
Tabu and Scatter Search for Artificial Neural Networks
2003
In this paper we address the problem of training multilayer feed-forward neural networks. These networks have been widely used for both prediction and classification in many different areas. Although the most popular method for training these networks is back propagation, other optimization methods such as tabu search or scatter search have been applied to solve this problem. This paper presents a new training algorithm based on the tabu search methodology that incorporates elements for search intensification and diversification by utilizing strategic designs where other previous approaches resort to randomization. Our method considers context and search information, as it is provided by th…
Neural network prediction in a system for optimizing simulations
2002
Neural networks have been widely used for both prediction and classification. Back-propagation is commonly used for training neural networks, although the limitations associated with this technique are well documented. Global search techniques such as simulated annealing, genetic algorithms and tabu search have also been used for this purpose. The developers of these training methods, however, have focused on accuracy rather than training speed in order to assess the merit of new proposals. While speed is not important in settings where training can be done off-line, the situation changes when the neural network must be trained and used on-line. This is the situation when a neural network i…
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…
The Belle II Physics Book
2019
cd. autorów: L. Cao48,‡, G. Caria145,‡, G. Casarosa57,‡, C. Cecchi56,‡,D. Cˇ ervenkov10,‡,M.-C. Chang22,‡, P. Chang92,‡, R. Cheaib146,‡, V. Chekelian83,‡, Y. Chen154,‡, B. G. Cheon28,‡, K. Chilikin77,‡, K. Cho70,‡, J. Choi14,‡, S.-K. Choi27,‡, S. Choudhury35,‡, D. Cinabro170,‡, L. M. Cremaldi146,‡, D. Cuesta47,‡, S. Cunliffe16,‡, N. Dash33,‡, E. de la Cruz Burelo9,‡, E. de Lucia52,‡, G. De Nardo54,‡, †Editor. ‡Belle II Collaborator. §Theory or external contributing author. M. De Nuccio16,‡, G. De Pietro59,‡, A. De Yta Hernandez9,‡, B. Deschamps129,‡, M. Destefanis60,‡, S. Dey116,‡, F.Di Capua54,‡, S.Di Carlo75,‡, J. Dingfelder129,‡, Z. Doležal10,‡, I. Domínguez Jiménez125,‡, T.V. Dong30,26,…
SANIST: optimization of a technology for compound identification based on the European Union directive with applications in forensic, pharmaceutical …
2016
Electrospray Ionization and collision induced dissociation tandem mass spectrometry are usually employed to obtain compound identification through a mass spectra match. Different algorithms have been developed for this purpose (for example the nist match algorithm). These approaches compare the tandem mass spectra of the unknown analyte with the tandem mass spectra spectra of known compounds inserted in a database. The compounds are usually identified on the basis of spectral match value associated with a probability of recognition. However, this approach is not usually applied to multiple reaction monitoring transition spectra achieved by means of triple quadrupole apparatus, mainly due to…
BlotBase: a northern blot database.
2008
With the availability of high-throughput gene expression analysis, multiple public expression databases emerged, mostly based on microarray expression data. Although these databases are of significant biomedical value, they do hold significant drawbacks, especially concerning the reliability of single gene expression profiles obtained by microarray data. Simultaneously, reliable data on an individual gene's expression are often published as single northern blots in individual publications. These data were not yet available for high-throughput screening. To reduce the gap between high-throughput expression data and individual highly reliable expression data, we designed a novel database "Blo…
Fast Algorithms for Pseudoarboricity
2015
The densest subgraph problem, which asks for a subgraph with the maximum edges-to-vertices ratio d∗, is solvable in polynomial time. We discuss algorithms for this problem and the computation of a graph orientation with the lowest maximum indegree, which is equal to ⌈d∗⌉. This value also equals the pseudoarboricity of the graph. We show that it can be computed in O(|E| √ log log d∗) time, and that better estimates can be given for graph classes where d∗ satisfies certain asymptotic bounds. These runtimes are achieved by accelerating a binary search with an approximation scheme, and a runtime analysis of Dinitz’s algorithm on flow networks where all arcs, except the source and sink arcs, hav…
A new compact formulation for the discrete p-dispersion problem
2017
Abstract This paper addresses the discrete p -dispersion problem (PDP) which is about selecting p facilities from a given set of candidates in such a way that the minimum distance between selected facilities is maximized. We propose a new compact formulation for this problem. In addition, we discuss two simple enhancements of the new formulation: Simple bounds on the optimal distance can be exploited to reduce the size and to increase the tightness of the model at a relatively low cost of additional computation time. Moreover, the new formulation can be further strengthened by adding valid inequalities. We present a computational study carried out over a set of large-scale test instances i…
Optimal standalone data center renewable power supply using an offline optimization approach
2022
Abstract Because of the increasing energy consumption of data centers and their C O 2 emissions, the ANR DATAZERO2 project aims to design autonomous data centers running solely on local renewable energy coupled with storage devices to overcome the intermittency issue. In order to optimize the use of renewable energy and storage devices, a MILP solver is usually in charge of assigning the power to be supplied to the data center. However, in order to reduce the computation time and make the approach scalable, it would be more appropriate to use a polynomial time algorithm. This paper aims at showing and proving that it is possible to provide an optimal power profile via a deterministic algori…
Behavior of polyether-ether-ketone (PEEK) in prostheses on dental implants. A review.
2020
Background The development of new and innovative materials such as high performance polymers (PEEK) opens a wide therapeutic range in implant prostheses. They are presented as alternative materials to metal and zirconium alloys in the manufacture of structures and attachments for implant prostheses and fixed and removable dental substitutes. The objective of this review is to know the characteristics of this material and thus assess its advantages and disadvantages in its possible applications in prostheses on dental implants. Material and methods A bibliographic search was carried out through the PubMed and Scopus search engines, of articles published from 2007 to 2020, excluding all artic…