Hull-form stochastic optimization via computational-cost reduction methods

2021 ◽  
Author(s):  
Andrea Serani ◽  
Frederick Stern ◽  
Emilio F. Campana ◽  
Matteo Diez
Keyword(s):  
Stochastic Optimization ◽  
Cost Reduction ◽  
Computational Cost ◽  
Hull Form ◽  
Reduction Methods

scholarly journals Breaking the problem into pieces: pre-clustering on-the-fly with the NGLMS

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
James Farrow
Keyword(s):  
Cost Reduction ◽  
Linked Data ◽  
Selection Criteria ◽  
Transitive Closure ◽  
Computational Cost ◽  
Quality Analysis ◽  
Clustering Techniques ◽  
Computationally Intensive ◽  
The Cost ◽  
Manual Review

ABSTRACT ObjectivesThe SA.NT DataLink Next Generation Linkage Management System (NGLMS) stores linked data in the form of a graph (in the computer science sense) comprised of nodes (records) and edges (record relationships or similarities). This permits efficient pre-clustering techniques based on transitive closure to form groups of records which relate to the same individual (or other selection criteria). ApproachOnly information known (or at least highly likely) to be relevant is extracted from the graph as superclusters. This operation is computationally inexpensive when the underlying information is stored as a graph and may be able to be done on-the-fly for typical clusters. More computationally intensive analysis and/or further clustering may then be performed on this smaller subgraph. Canopy clustering and using blocking used to reduce pairwise comparisons are expressions of the same type of approach. ResultsSubclusters for manual review based on transitive closure are typically computationally inexpensive enough to extract from the NGLMS that they are extracted on-demand during manual clerical review activities. There is no necessity to pre-calculate these clusters. Once extracted further analysis is undertaken on these smaller data groupings for visualisation and presentation for review and quality analysis. More computationally expensive techniques can be used at this point to prepare data for visualisation or provide hints to manual reviewers. 
Extracting high-recall groups of data records for review but providing them to reviews grouped further into high precision groups as the result of a second pass has resulted in a reduction of the time taken for clerical reviewers at SANT DataLink to manual review a group by 30–40%. The reviewers are able to manipulate whole groups of related records at once rather than individual records. ConclusionPre-clustering reduces the computational cost associated with higher order clustering and analysis algorithms. Algorithms which scale by n^2 (or more) are typical in comparison scenarios. By breaking the problem into pieces the computational cost can be reduced. Typically breaking a problem into many pieces reduces the cost in proportion to the number of pieces the problem can be broken into. This cost reduction can make techniques possible which would otherwise be computationally prohibitive.

scholarly journals A Simplified Milstein Scheme for SPDEs with Multiplicative Noise

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
B. Ghayebi ◽  
S. M. Hosseini
Keyword(s):  
Cost Reduction ◽  
Order Of Convergence ◽  
Multiplicative Noise ◽  
Research Question ◽  
Computational Cost ◽  
Order Of Accuracy ◽  
Milstein Scheme ◽  
Exponential Term ◽  
Numerical Tests ◽  
Computational Reduction

This paper deals with a research question raised by Jentzen and Röckner (A Milstein scheme for SPDEs, arXiv:1001.2751v4 (2012)), whether the exponential term in their introduced scheme can be replaced by a simpler mollifier. This replacement can lead to more simplification and computational reduction in simulation. So, in this paper, we essentially replace the exponential term with a Padé approximation of order 1 and denote the resulting scheme by simplified Milstein scheme. The convergence analysis for this scheme is carried out and it is shown that even with this replacement the order of convergence is maintained, while the resulting scheme is easier to implement and slightly more efficient computationally. Some numerical tests are given that confirm the order of accuracy and also computational cost reduction.

scholarly journals Parametric space-frequency reduction for second-order system models

2018 ◽  
Author(s):  
Vanessa Cool ◽  
Frank Naets ◽  
Ward Rottiers ◽  
Wim Desmet
Keyword(s):  
Frequency Response ◽  
Cost Reduction ◽  
Frequency Response Function ◽  
Performance Metrics ◽  
Computational Cost ◽  
Order System ◽  
Model Parameters ◽  
Frequency Content ◽  
Space Frequency ◽  
Set Up

This research focusses on the computational cost reduction of frequency domain simulations in many-query applications with varying model parameters. These analyses are often encountered during the design of mechanical structures, where frequency response function (FRF) amplitudes are still one of the key performance metrics to be considered. Moreover, often inputs (number and frequency content) can vary broadly, which makes it all the more challenging to set up the reduced model.

scholarly journals Advances in Hierarchical Model Reduction and combination with other computational reduction methods

2018 ◽  
Author(s):  
Giulia Meglioli ◽  
Matteo Zancanaro ◽  
Francesco Ballarin ◽  
Simona Perotto ◽  
Gianluigi Rozza
Keyword(s):  
Hierarchical Model ◽  
Computational Cost ◽  
Order Reduction ◽  
Reduced Basis ◽  
Element Discretization ◽  
Modal Expansion ◽  
Reduction Techniques ◽  
Computational Performance ◽  
Reduction Methods ◽  
Computational Reduction

In this work we present address the combination of the Hierarchical Model (Hi-Mod) reduction approach with projection-based reduced order methods, exploiting either on Greedy Reduced Basis (RB) or Proper Orthogonal Decomposition (POD), in a parametrized setting. The Hi-Mod approach, introduced in, is suited to reduce problems in pipe-like domains featuring a dominant axial dynamics, such as those arising for instance in haemodynamics. The Hi-Mod approach aims at reducing the computational cost by properly combining a finite element discretization of the dominant dynamics with a modal expansion in the transverse direction. In a parametrized context, the Hi-Mod approach has been employed as the high-fidelity method during the offline stage of model order reduction techniques based on RB or POD. The resulting combined reduction methods, which have been named Hi-RB and Hi-POD, respectively, will be presented with applications in diffusion-advection problems, fluid dynamics and optimal control problems, focusing on the approximation stability of the proposed methods and their computational performance.

scholarly journals Accuracy, Robustness and Scalability of Dimensionality Reduction Methods for Single Cell RNAseq Analysis

2019 ◽  
Author(s):  
Shiquan Sun ◽  
Jiaqiang Zhu ◽  
Ying Ma ◽  
Xiang Zhou
Keyword(s):  
Data Analysis ◽  
Dimensionality Reduction ◽  
Single Cell ◽  
Comprehensive Evaluation ◽  
Computational Cost ◽  
Noise Removal ◽  
Data Sets ◽  
Vast Number ◽  
Cell Clustering ◽  
Reduction Methods

ABSTRACTBackgroundDimensionality reduction (DR) is an indispensable analytic component for many areas of single cell RNA sequencing (scRNAseq) data analysis. Proper DR can allow for effective noise removal and facilitate many downstream analyses that include cell clustering and lineage reconstruction. Unfortunately, despite the critical importance of DR in scRNAseq analysis and the vast number of DR methods developed for scRNAseq studies, however, few comprehensive comparison studies have been performed to evaluate the effectiveness of different DR methods in scRNAseq.ResultsHere, we aim to fill this critical knowledge gap by providing a comparative evaluation of a variety of commonly used DR methods for scRNAseq studies. Specifically, we compared 18 different DR methods on 30 publicly available scRNAseq data sets that cover a range of sequencing techniques and sample sizes. We evaluated the performance of different DR methods for neighborhood preserving in terms of their ability to recover features of the original expression matrix, and for cell clustering and lineage reconstruction in terms of their accuracy and robustness. We also evaluated the computational scalability of different DR methods by recording their computational cost.ConclusionsBased on the comprehensive evaluation results, we provide important guidelines for choosing DR methods for scRNAseq data analysis. We also provide all analysis scripts used in the present study atwww.xzlab.org/reproduce.html. Together, we hope that our results will serve as an important practical reference for practitioners to choose DR methods in the field of scRNAseq analysis.

scholarly journals Intelligent Contact Force Regulation of Pantograph–Catenary Based on Novel Type-Reduction Technology

Electronics ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 132
Author(s):  
Tsung-Chih Lin ◽  
Chien-Wen Sun ◽  
Yu-Chen Lin ◽  
Majid Moradi Zirkohi
Keyword(s):  
Contact Force ◽  
Reduction Method ◽  
Computational Cost ◽  
Reference Value ◽  
Current Collection ◽  
Type Reduction ◽  
Control Scheme ◽  
Reduction Methods ◽  
Adaptive Fuzzy Logic ◽  
Interval Type

In this paper, an intelligent control scheme is proposed to suppress vibrations between the pantograph and the catenary by regulating the contact force to a reference value, thereby achieving stable current collection. In order to reduce the computational cost, an interval Type-2 adaptive fuzzy logic control with the Moradi–Zirhohi–Lin type reduction method is applied to deal with model uncertainties and exterior interference. Based on a simplified pantograph–catenary system model, the comparative simulation results show that variation of the contact force can be attenuated and variation disturbances can be repressed simultaneously. Furthermore, in terms of computational burden, the proposed type reduction method outperforms other type reduction methods.

scholarly journals Transient Dynamical-Thermal-Optical System Modeling and Simulation

2020 ◽  
Vol 238 ◽  
pp. 12001
Author(s):  
Luzia Hahn ◽  
Peter Eberhard
Keyword(s):  
Optical System ◽  
High Performance ◽  
System Modeling ◽  
Computational Cost ◽  
Order Reduction ◽  
Optical Systems ◽  
Model Order ◽  
Transient Simulations ◽  
Reduction Methods ◽  
Low Computational Cost

In this work, methods and procedures are investigated for the holistic simulation of the dynamicalthermal behavior of high-performance optics like lithography objectives. Flexible multibody systems in combination with model order reduction methods, finite element thermal analysis and optical system analyses are used for transient simulations of the dynamical-thermal behavior of optical systems at low computational cost.

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