Πλοήγηση ανά Θέμα "Iterative methods"
Αποτελέσματα 1-20 από 49
-
A 3-D Fast transform-based preconditioner for large-scale power grid analysis on massively parallel architectures
(2014)Efficient analysis of on-chip power delivery networks is one of the most challenging problems that EDA is confronted with. This paper addresses the problem of simulating general multi-layer power delivery networks with ... -
Accelerating techniques on nested decomposition
(2017)In this paper, we consider the nested decomposition method in the context of multistage stochastic problems with scenario trees where we contribute with improvements in accelerating convergence to optimum. We first propose ... -
Application of deep learning and chaos theory for load forecasting in Greece
(2021)In this paper, a novel combination of deep learning recurrent neural network and Lyapunov time is proposed to forecast the consumption of electricity load, in Greece, in normal/abrupt change value areas. Our method verifies ... -
Auto-Tuned Weighted-Penalty Parameter ADMM for Distributed Optimal Power Flow
(2021)The Alternating Direction Method of Multipliers (ADMM) is widely utilized to solve the distributed Optimal Power Flow (OPF) problem, providing convergence under certain assumptions. ADMM relies on a penalty parameter ρ to ... -
Band Preconditioners for Non-Symmetric Real Toeplitz Systems with Unknown Generating Function
(2021)Toeplitz systems appear in a variety of applications in real life such as signal processing, image processing and restoration and discretization of PDEs. The fast convergence to the accurate solution of the system seems ... -
A Bayesian Expectation-Maximization (BEM) methodology for joint input-state estimation and virtual sensing of structures
(2022)The joint input-state estimation and virtual sensing of structures are reformulated on a Bayesian probabilistic foundation, focusing on data-driven uncertainty quantification and propagation. The variation of input forces ... -
Bayesian optimal estimation for output-only nonlinear system and damage identification of civil structures
(2018)This paper presents a new framework for output-only nonlinear system and damage identification of civil structures. This framework is based on nonlinear finite element (FE) model updating in the time-domain, using only the ... -
Bilevel programming solution algorithms for optimal price-bidding of energy producers in multi-period day-ahead electricity markets with non-convexities
(2021)We consider the problem of devising optimal price-offers (bids) for an energy producer participating in a multi-period day-ahead electricity market which exhibits non-convexities due to the discrete nature of the generation ... -
Comparison of three classes of algorithms for the solution of the linear complementarity problem with an H+-matrix
(2018)There are three main classes of iterative methods for the solution of the linear complementarity problem (LCP). In order of appearance these classes are: the “projected iterative methods”, the “(block) modulus algorithms” ... -
Computational study of the effect of gradient magnetic field in navigation of spherical particles
(2017)The use of spherical magnetic nanoparticles that are coated with drugs and can be navigated in arteries to attack tumors is proposed as an alternative to chemotherapy. Navigation of particles is due to magnetic field ... -
Computational study of the optimum gradient magnetic field for the navigation of spherical particles into targeted areas
(2015)Spherical magnetic nanoparticles coated with drugs are navigated to targeted areas, for the treatment of cancer. The particles are navigated by magnetic field gradients that can be produced by an MRI device. In the present ... -
Decentralized blockchain-based consensus for Optimal Power Flow solutions
(2021)We design, implement and analyze a decentralized consensus algorithm based on the blockchain technology for the solution of the Optimal Power Flow problem. The proposed algorithm enables independent power grid nodes, without ... -
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification
(2018)This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only ... -
Determinative Brain Storm Optimization
(2020)Brain Storm Optimization (BSO) is a swarm intelligence optimization algorithm, based on the human brainstorming process. The ideas of a brainstorming process comprise the solutions of the algorithm, which iteratively applies ... -
Distributed Fuzzy Cognitive Maps for Feature Selection in Big Data Classification
(2022)The features of a dataset play an important role in the construction of a machine learning model. Because big datasets often have a large number of features, they may contain features that are less relevant to the machine ... -
Domocus: Lock free parallel legalization in standard cell placement
(2017)In the cell placement problem a circuit's cells must be placed within a specified chip area so that they are row aligned and contain no overlaps. The problem is usually tackled in phases, whereby in the first phase a global ... -
Efficient linear system solution techniques in the simulation of large dense mutually inductive circuits
(2019)The verification of integrated Circuits (ICs) in deep submicron technologies requires that all mutual inductive effects are taken into account to properly validate the performance and reliable operation of the chip. However, ... -
Efficient solution of large sparse linear systems in modern hardware
(2016)The solution of large-scale sparse linear systems arises in numerous scientific and engineering problems. Typical examples involve study of many real world multi-physics problems and the analysis of electric power systems. ... -
Experiments in acoustic source localization using sparse arrays in adverse indoors environments
(2014)In this paper we experiment with 2-D source localization in smart homes under adverse conditions using sparse distributed microphone arrays. We propose some improvements to deal with problems due to high reverberation, ... -
Fast Doubling Algorithm for the Solution of the Riccati Equation Using Cyclic Reduction Method
(2020)A new iterative doubling algorithm for the solution of the discrete time Riccati equation is proposed. The algorithm is based on the Cyclic Reduction Method (CRM). The proposed doubling algorithm does not require non-singularity ...