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Algorithms, Volume 13, Issue 5

2020 May - 25 articles

Cover Story: Civil engineering applications are often characterized by large uncertainties regarding the material parameters. Discretization of the underlying equations is typically done by means of the Galerkin finite element method. The uncertain material parameter can then be expressed as a random field represented by means of a Karhunen–Loève expansion. Computation of the stochastic responses remains very costly, even when state-of-the-art multilevel Monte Carlo is used. A significant cost reduction can be achieved by using p-refined multilevel quasi-Monte Carlo (p-MLQMC). This novel method is based on a variance reduction scheme by employing a hierarchical p-refinement discretization of the problem, which is then combined with a rank-1 lattice rule. In this work, we developed algorithms for the p-MLQMC method and benchmarked them on two model problems. View this paper
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Articles (25)

  • Article
  • Open Access
8 Citations
4,558 Views
17 Pages

22 May 2020

One of the main issues addressed in any engineering design problem is to predict the performance of the component or system as accurately and realistically as possible, taking into account the variability of operating conditions or the uncertainty on...

  • Article
  • Open Access
5 Citations
4,306 Views
16 Pages

21 May 2020

One of the most challenging aspects of medical modalities such as Computed Tomography (CT) as well hybrid techniques such as CT/PET (Computed Tomography/Positron emission tomography) and PET/MRI is finding a balance between examination time, radiatio...

  • Article
  • Open Access
5 Citations
5,371 Views
16 Pages

20 May 2020

It is very often the case that at some moment a time series process abruptly changes its underlying structure and, therefore, it is very important to accurately detect such change-points. In this problem, which is called a change-point (or break-poin...

  • Article
  • Open Access
5 Citations
5,707 Views
14 Pages

19 May 2020

Salient segmentation is a critical step in biomedical image analysis, aiming to cut out regions that are most interesting to humans. Recently, supervised methods have achieved promising results in biomedical areas, but they depend on annotated traini...

  • Article
  • Open Access
9 Citations
4,324 Views
18 Pages

The Effect of Different Deep Network Architectures upon CNN-Based Gaze Tracking

  • Hui-Hui Chen,
  • Bor-Jiunn Hwang,
  • Jung-Shyr Wu and
  • Po-Ting Liu

19 May 2020

In this paper, we explore the effect of using different convolutional layers, batch normalization and the global average pooling layer upon a convolutional neural network (CNN) based gaze tracking system. A novel method is proposed to label the parti...

  • Article
  • Open Access
14 Citations
6,015 Views
34 Pages

18 May 2020

Sequential pattern mining is a fundamental data mining task with application in several domains. We study two variants of this task—the first is the extraction of frequent sequential patterns, whose frequency in a dataset of sequential transact...

  • Review
  • Open Access
62 Citations
8,655 Views
33 Pages

Moving Deep Learning to the Edge

  • Mário P. Véstias,
  • Rui Policarpo Duarte,
  • José T. de Sousa and
  • Horácio C. Neto

18 May 2020

Deep learning is now present in a wide range of services and applications, replacing and complementing other machine learning algorithms. Performing training and inference of deep neural networks using the cloud computing model is not viable for appl...

  • Article
  • Open Access
11 Citations
5,125 Views
30 Pages

18 May 2020

Inference of chemical compounds with desired properties is important for drug design, chemo-informatics, and bioinformatics, to which various algorithmic and machine learning techniques have been applied. Recently, a novel method has been proposed fo...

  • Article
  • Open Access
5,158 Views
17 Pages

10 May 2020

Developing tools for precise quantification of brain metabolites using magnetic resonance spectroscopy (MRS) is an active area of research with broad application in non-invasive neurodegenerative disease studies. The tools are mainly developed based...

  • Article
  • Open Access
125 Citations
16,011 Views
21 Pages

Ensemble Deep Learning Models for Forecasting Cryptocurrency Time-Series

  • Ioannis E. Livieris,
  • Emmanuel Pintelas,
  • Stavros Stavroyiannis and
  • Panagiotis Pintelas

10 May 2020

Nowadays, cryptocurrency has infiltrated almost all financial transactions; thus, it is generally recognized as an alternative method for paying and exchanging currency. Cryptocurrency trade constitutes a constantly increasing financial market and a...

  • Article
  • Open Access
14 Citations
8,939 Views
16 Pages

Forecasting Electricity Prices: A Machine Learning Approach

  • Mauro Castelli,
  • Aleš Groznik and
  • Aleš Popovič

8 May 2020

The electricity market is a complex, evolutionary, and dynamic environment. Forecasting electricity prices is an important issue for all electricity market participants. In this study, we shed light on how to improve electricity price forecasting acc...

  • Article
  • Open Access
2 Citations
4,717 Views
12 Pages

Distributional Reinforcement Learning with Ensembles

  • Björn Lindenberg,
  • Jonas Nordqvist and
  • Karl-Olof Lindahl

7 May 2020

It is well known that ensemble methods often provide enhanced performance in reinforcement learning. In this paper, we explore this concept further by using group-aided training within the distributional reinforcement learning paradigm. Specifically,...

  • Article
  • Open Access
10 Citations
5,516 Views
18 Pages

6 May 2020

The expected utility principle is often used to compute the insurance premium through a second-order approximation of the expected value of the utility of losses. We investigate the impact of using a more accurate approximation based on the fourth-or...

  • Article
  • Open Access
19 Citations
6,445 Views
19 Pages

A Novel Hybrid Metaheuristic Algorithm for Optimization of Construction Management Site Layout Planning

  • Doddy Prayogo,
  • Min-Yuan Cheng,
  • Yu-Wei Wu,
  • A. A. N. Perwira Redi,
  • Vincent F. Yu,
  • Satria Fadil Persada and
  • Reny Nadlifatin

6 May 2020

Symbiotic organisms search (SOS) is a promising metaheuristic algorithm that has been studied recently by numerous researchers due to its capability to solve various hard and complex optimization problems. SOS is a powerful optimization technique tha...

  • Article
  • Open Access
7 Citations
4,616 Views
22 Pages

2 May 2020

Upgrading ordinary streetlights to smart streetlights to help monitor traffic flow is a low-cost and pragmatic option for cities. Fine-grained classification of vehicles in the sight of smart streetlights is essential for intelligent transportation a...

  • Article
  • Open Access
10 Citations
4,606 Views
18 Pages

2 May 2020

Risk maturity evaluation is an efficient tool which can assist construction organizations in the identification of their strengths and weaknesses in risk management processes and in taking necessary actions for the improvement of these processes. The...

  • Article
  • Open Access
1 Citations
4,843 Views
22 Pages

30 April 2020

We consider initial value problems (IVPs) where we are interested in a quantity of interest (QoI) that is the integral in time of a functional of the solution. For these, we analyze goal oriented time adaptive methods that use only local error estima...

  • Article
  • Open Access
24 Citations
8,840 Views
14 Pages

29 April 2020

Since its creation by Nawaz, Enscore, and Ham in 1983, NEH remains the best heuristic method to solve flowshop scheduling problems. In the large body of literature dealing with the application of this heuristic, it can be clearly noted that results d...

  • Article
  • Open Access
9 Citations
5,160 Views
18 Pages

29 April 2020

In person re-identification, extracting image features is an important step when retrieving pedestrian images. Most of the current methods only extract global features or local features of pedestrian images. Some inconspicuous details are easily igno...

  • Article
  • Open Access
3 Citations
4,980 Views
24 Pages

28 April 2020

In this paper, we briefly present several modifications and generalizations of the concept of self-organizing neural networks—usually referred to as self-organizing maps (SOMs)—to illustrate their advantages in applications that range fro...

  • Article
  • Open Access
8 Citations
4,653 Views
30 Pages

p-Refined Multilevel Quasi-Monte Carlo for Galerkin Finite Element Methods with Applications in Civil Engineering

  • Philippe Blondeel,
  • Pieterjan Robbe,
  • Cédric Van hoorickx,
  • Stijn François,
  • Geert Lombaert and
  • Stefan Vandewalle

28 April 2020

Civil engineering applications are often characterized by a large uncertainty on the material parameters. Discretization of the underlying equations is typically done by means of the Galerkin Finite Element method. The uncertain material parameter ca...

  • Article
  • Open Access
6 Citations
6,150 Views
18 Pages

26 April 2020

The quality assurance of publication data in collaborative knowledge bases and in current research information systems (CRIS) becomes more and more relevant by the use of freely available spatial information in different application scenarios. When i...

  • Article
  • Open Access
6 Citations
4,621 Views
18 Pages

26 April 2020

Many modern real-valued optimization tasks use “black-box” (BB) models for evaluating objective functions and they are high-dimensional and constrained. Using common classifications, we can identify them as constrained large-scale global...

  • Article
  • Open Access
10 Citations
5,035 Views
15 Pages

Diagnosis in Tennis Serving Technique

  • Eugenio Roanes-Lozano,
  • Eduardo A. Casella,
  • Fernando Sánchez and
  • Antonio Hernando

25 April 2020

Tennis is a sport with a very complex technique. Amateur tennis players have trainers and/or coaches, but are not usually accompanied by them to championships. Curiously, in this sport, the result of many matches can be changed by a small hint like &...

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Algorithms - ISSN 1999-4893