Search results for "curse of dimensionality"

Self-Assembly of Zr(C2O4)44– Metallotectons and Bisimidazolium Cations: Influence of the Dication on H-Bonded Framework Dimensionality and Material P…

2011

Assemblies involving [Zr(C2O4)4]4– metallotectons (C2O42– = oxalate) and linear, flexible, or V-shaped organic cations (H2-Lx)2+ derived from the 1,4-bisimidazol-1-ylbenzene molecule have been envisioned to elaborate porous frameworks based on ionic H-bonds. Five architectures of formula [{(H2-L1)2Zr(C2O4)4}·2H2O] (1), [{(H2-L2)2Zr(C2O4)4}·6H2O] (2), [{(H2-L3)2Zr(C2O4)4}·6H2O] (3), [{(H2-L4)2Zr(C2O4)4}·H2O] (4), and [{(H2-L5)2Zr(C2O4)4}·6H2O] (5) (with L1 = p-bis(imidazol-1-yl)benzene, L2 = p-bis(2-methylimidazol-1-yl)benzene, L3 = p-bis(imidazol-1-yl)-2,5-dimethylbenzene, L4 = p-bis(imidazol-1-ylmethyl)benzene, L5 = m-bis(imidazol-1-yl)benzene) have been obtained; 1–3, and 5 show an open-f…

Ligand effects on the dimensionality of oxamato-bridged mixed-metal open-framework magnets

2012

Increasing dimensionality [from 2D (1) to 3D (2)] and T(C) [from 10 (1) to 20 K (2)] in two new oxamato-bridged heterobimetallic Mn(II)(2)Cu(II)(3) open-frameworks result from the steric hindrance provided by the different alkyl substituents of the N-phenyloxamate bridging ligands.

A Differential Evolution Framework with Ensemble of Parameters and Strategies and Pool of Local Search Algorithms

2014

The file attached to this record is the author's final peer reviewed version. The publisher's final version can be found by following the DOI link. The ensemble structure is a computational intelligence supervised strategy consisting of a pool of multiple operators that compete among each other for being selected, and an adaptation mechanism that tends to reward the most successful operators. In this paper we extend the idea of the ensemble to multiple local search logics. In a memetic fashion, the search structure of an ensemble framework cooperatively/competitively optimizes the problem jointly with a pool of diverse local search algorithms. In this way, the algorithm progressively adapts…

Enhanced superconductivity in atomically thin TaS2

2016

The ability to exfoliate layered materials down to the single layer limit has presented the opportunity to understand how a gradual reduction in dimensionality affects the properties of bulk materials. Here we use this top–down approach to address the problem of superconductivity in the two-dimensional limit. The transport properties of electronic devices based on 2H tantalum disulfide flakes of different thicknesses are presented. We observe that superconductivity persists down to the thinnest layer investigated (3.5 nm), and interestingly, we find a pronounced enhancement in the critical temperature from 0.5 to 2.2 K as the layers are thinned down. In addition, we propose a tight-binding …

The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions.

2019

Although the field of learning automata (LA) has made significant progress in the past four decades, the LA-based methods to tackle problems involving environments with a large number of actions is, in reality, relatively unresolved. The extension of the traditional LA to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and so, most components of the vector will soon have values that are smaller than the machine accuracy permits, implying that they will never be chosen . This paper presents a solution that extends the continuous pursuit paradigm to …

The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions

2018

Part 10: Learning - Intelligence; International audience; Although the field of Learning Automata (LA) has made significant progress in the last four decades, the LA-based methods to tackle problems involving environments with a large number of actions are, in reality, relatively unresolved. The extension of the traditional LA (fixed structure, variable structure, discretized, and pursuit) to problems within this domain cannot be easily established when the number of actions is very large. This is because the dimensionality of the action probability vector is correspondingly large, and consequently, most components of the vector will, after a relatively short time, have values that are smal…

2004

This paper presents the use of Support Vector Machines (SVMs) for prediction and analysis of antisense oligonucleotide (AO) efficacy. The collected database comprises 315 AO molecules including 68 features each, inducing a problem well-suited to SVMs. The task of feature selection is crucial given the presence of noisy or redundant features, and the well-known problem of the curse of dimensionality. We propose a two-stage strategy to develop an optimal model: (1) feature selection using correlation analysis, mutual information, and SVM-based recursive feature elimination (SVM-RFE), and (2) AO prediction using standard and profiled SVM formulations. A profiled SVM gives different weights to …

Local dimensionality reduction within natural clusters for medical data analysis

2005

Inductive learning systems have been successfully applied in a number of medical domains. Nevertheless, the effective use of these systems requires data preprocessing before applying a learning algorithm. Especially it is important for multidimensional heterogeneous data, presented by a large number of features of different types. Dimensionality reduction is one commonly applied approach. The goal of this paper is to study the impact of natural clustering on dimensionality reduction for classification. We compare several data mining strategies that apply dimensionality reduction by means of feature extraction or feature selection for subsequent classification. We show experimentally on micr…

A novel method for network intrusion detection based on nonlinear SNE and SVM

2017

In the case of network intrusion detection data, pre-processing techniques have been extensively used to enhance the accuracy of the model. An ideal intrusion detection system (IDS) is one that has appreciable detection capability overall the group of attacks. An open research problem of this area is the lower detection rate for less frequent attacks, which result from the curse of dimensionality and imbalanced class distribution of the benchmark datasets. This work attempts to minimise the effects of imbalanced class distribution by applying random under-sampling of the majority classes and SMOTE-based oversampling of minority classes. In order to alleviate the issue arising from the curse…

Solvatochromy and electro-optical study of new fluorine-containing chromophores

1998

technology requires tailored functional materials which fulfill the demands for optimal operation parameters, reliability andprocessability. Organic chromophores and polymers which contain covalently bound chromophores are promising materialclasses which can satisfy a broad spectrum of demands on functional materials for photonics, and they are, therefore,favorites for the development of new photonic devices. However, it is almost impossible to satisfy all physico-chemical andtechnological requirements simultaneously with a polymer consisting of only one type of functional unit. The developmentof a series of different building blocks which allow to cover the whole range of physico-chemical …