scholarly journals Global-Entropy Driven Exploration with Distributed Models under Sparsity Constraints

2018 ◽  
Vol 8 (10) ◽  
pp. 1722 ◽  
Author(s):  
Christoph Manss ◽  
Dmitriy Shutin
Keyword(s):  
Optimization Problem ◽  
Data Distribution ◽  
Consensus Algorithm ◽  
Estimation Methods ◽  
Model Estimation ◽  
Individual Agent ◽  
Distributed Models ◽  
Heterogeneous Learning ◽  
Sparsity Constraints ◽  
The Individual

This paper focuses on exploration when using different data distribution schemes and ADMM as a solver for swarms. By exploration, we mean the estimation of new measurement locations that are beneficial for the model estimation. In particular, the different distribution schemes are splitting-over-features or heterogeneous learning and splitting-over-examples or homogeneous learning. Each agent contributes a solution to solve the joint optimization problem by using ADMM and the consensus algorithm. This paper shows that some information is unknown to the individual agent, and thus, the estimation of new measurement positions is not possible without further communication. Therefore, this paper shows results for how to distribute only necessary information for a global exploration. We show the benefits between the proposed global exploration scheme and benchmark exploration schemes such as random walk and systematic traversing, i.e., meandering. The proposed waypoint estimation methods are then tested against each other and with other movement methods. This paper shows that a movement method, which considers the current information within the model, is superior to the benchmark movement methods.

scholarly journals First Cost Calculation Methods for Road Freight Transport Activity

2017 ◽  
Vol 18 (2) ◽  
pp. 107-117 ◽  
Author(s):  
György Kovács
Keyword(s):  
State Of The Art ◽  
Common Type ◽  
Estimation Methods ◽  
Cost Calculation ◽  
Transport Activity ◽  
Calculation Methods ◽  
Transport Costs ◽  
Art Practices ◽  
Road Freight ◽  
The Individual

Abstract The transport activity is one of the most expensive processes in the supply chain. Forwarding and transport companies focuses on the optimization of transportation and the reduction of transport costs. The goal of this study is to develop a method which calculate the first (prime) cost of a given transport task more precisely than the state of the art practices. In practice the calculation of transport fee depends on the individual estimation methods of the transport managers, which could result losses for the company. In this study the elaborated calculation method for total first cost is detailed for three types of fulfilment of transport tasks. The most common type of achievement is, when “own vehicle is used with own driver”. A software was also developed for this case based on the elaborated method. Based on the calculations of our software, the first cost can be defined quickly and precisely to realize higher profit.

scholarly journals Low Complexity Sparse Beamspace DOA Estimation Via Single Measurement Vectors for Uniform Circular Array

2021 ◽  
Author(s):  
Di Zhao ◽  
Weijie Tan ◽  
Zhongliang Deng ◽  
Gang Li
Keyword(s):  
Optimization Problem ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Doa Estimation ◽  
Low Complexity ◽  
Estimation Methods ◽  
Circular Array ◽  
Single Measurement ◽  
Signal Model ◽  
Convex Optimization Problem

Abstract In this paper, we present a low complexity beamspace direction-of-arrival (DOA) estimation method for uniform circular array (UCA), which is based on the single measurement vectors (SMVs) via vectorization of sparse covariance matrix. In the proposed method, we rstly transform the signal model of UCA to that of virtual uniform linear array (ULA) in beamspace domain using the beamspace transformation (BT). Subsequently, by applying the vectorization operator on the virtual ULA-like array signal model, a new dimension-reduction array signal model consists of SMVs based on Khatri-Rao (KR) product is derived. And then, the DOA estimation is converted to the convex optimization problem. Finally, simulations are carried out to verify the eectiveness of the proposed method, the results show that without knowledge of the signal number, the proposed method not only has higher DOA resolution than subspace-based methods in low signal-to-noise ratio (SNR), but also has much lower computational complexity comparing other sparse-like DOA estimation methods.

scholarly journals Nerve agents: emergency preparedness

2020 ◽  
Vol 166 (1) ◽  
pp. 42-46
Author(s):  
Alan George Andrew Weir ◽  
S Makin ◽  
J Breeze
Keyword(s):  
Emergency Preparedness ◽  
Emergency Services ◽  
Chemical Properties ◽  
Chemical Warfare Agents ◽  
Nerve Agents ◽  
Clinical Effects ◽  
Individual Agent ◽  
Warfare Agents ◽  
The Individual ◽  
The Uk

Nerve agents (NAs) are a highly toxic group of chemical warfare agents. NAs are organophosphorus esters with varying physical and chemical properties depending on the individual agent. The most recently developed class of NA is ‘Novichok’, the existence of which was first revealed in the early 1990s, just before Russia signed the Chemical Weapons Convention. In 1984, Iraq became the first nation to deploy NA on the battlefield when they used tabun against Iranian military forces in Majnoon Island near Basra. The first terrorist use of an NA is believed to be the attack in Matsumoto, Japan, on 27 June 1994 by the Aum Shinrikyo doomsday cult. Symptoms and ultimate toxicity from NA poisoning are related to the agent involved, the form and degree of exposure, and rapidity of medical treatment. The classic toxidrome of significant exposure to NA comprises bronchorrhoea, bronchospasm, bradycardia and convulsions, with an onset period of as early as a few seconds depending on the mode and extent of exposure. If medical management is not instituted rapidly, death may occur in minutes by asphyxiation and cardiac arrest. In the UK, emergency preparedness for NA poisoning includes an initial operational response programme across all blue light emergency services and key first responders. This paper describes the development, pathophysiology, clinical effects and current guidance for management of suspected NA poisoning. It also summarises the known events in which NA poisoning has been confirmed.

scholarly journals On the Performance of Efficient Channel Estimation Strategies for Hybrid Millimeter Wave MIMO System

Entropy ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. 1121
Author(s):  
Prateek Saurabh Srivastav ◽  
Lan Chen ◽  
Arfan Haider Wahla
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Optimization Problem ◽  
Mimo Systems ◽  
Mimo System ◽  
Low Rank ◽  
Potential Candidate ◽  
Alternating Direction ◽  
The Individual ◽  
Joint Channel

Millimeter wave (mmWave) relying upon the multiple output multiple input (MIMO) is a new potential candidate for fulfilling the huge emerging bandwidth requirements. Due to the short wavelength and the complicated hardware architecture of mmWave MIMO systems, the conventional estimation strategies based on the individual exploitation of sparsity or low rank properties are no longer efficient and hence more modern and advance estimation strategies are required to recapture the targeted channel matrix. Therefore, in this paper, we proposed a novel channel estimation strategy based on the symmetrical version of alternating direction methods of multipliers (S-ADMM), which exploits the sparsity and low rank property of channel altogether in a symmetrical manner. In S-ADMM, at each iteration, the Lagrange multipliers are updated twice which results symmetrical handling of all of the available variables in optimization problem. To validate the proposed algorithm, numerous computer simulations have been carried out which straightforwardly depicts that the S-ADMM performed well in terms of convergence as compared to other benchmark algorithms and also able to provide global optimal solutions for the strictly convex mmWave joint channel estimation optimization problem.

CURVELET-WAVELET REGULARIZED SPLIT BREGMAN ITERATION FOR COMPRESSED SENSING

2011 ◽  
Vol 09 (01) ◽  
pp. 79-110 ◽  
Author(s):  
GERLIND PLONKA ◽  
JIANWEI MA
Keyword(s):  
Compressed Sensing ◽  
Optimization Problem ◽  
Constrained Optimization Problem ◽  
Split Bregman ◽  
Split Bregman Iteration ◽  
Special Cases ◽  
Sparsity Constraints ◽  
Iteration Methods ◽  
Wave Atoms ◽  
Sparsity Constrained Optimization

Compressed sensing is a new concept in signal processing. Assuming that a signal can be represented or approximated by only a few suitably chosen terms in a frame expansion, compressed sensing allows one to recover this signal from much fewer samples than the Shannon–Nyquist theory requires. Many images can be sparsely approximated in expansions of suitable frames as wavelets, curvelets, wave atoms and others. Generally, wavelets represent point-like features while curvelets represent line-like features well. For a suitable recovery of images, we propose models that contain weighted sparsity constraints in two different frames. Given the incomplete measurements f = Φu + ϵ with the measurement matrix Φ ∈ ℝK × N, K ≪ N, we consider a jointly sparsity-constrained optimization problem of the form [Formula: see text]. Here Ψc and Ψw are the transform matrices corresponding to the two frames, and the diagonal matrices Λc, Λw contain the weights for the frame coefficients. We present efficient iteration methods to solve the optimization problem, based on Alternating Split Bregman algorithms. The convergence of the proposed iteration schemes will be proved by showing that they can be understood as special cases of the Douglas–Rachford Split algorithm. Numerical experiments for compressed sensing-based Fourier-domain random imaging show good performances of the proposed curvelet-wavelet regularized split Bregman (CWSpB) methods, where we particularly use a combination of wavelet and curvelet coefficients as sparsity constraints.

Cost Minimum Proportioning of Non-Slump Concrete Mix Using Genetic Algorithms

2012 ◽  
Vol 468-471 ◽  
pp. 50-54 ◽  
Author(s):  
Md. Moshiur Rahman ◽  
Mohd Zamin Jumaat
Keyword(s):  
Compressive Strength ◽  
Optimization Problem ◽  
Constrained Optimization Problem ◽  
Nonlinear Constrained Optimization ◽  
Constituent Material ◽  
Optimization Formulation ◽  
Materials Used ◽  
The Individual ◽  
The Cost ◽  
Optimal Quantity

This paper presents a generalized formulation for determining the optimal quantity of the materials used to produce Non-Slump Concrete with minimum possible cost. The proposed problem is formulated as a nonlinear constrained optimization problem. The proposed problem considers cost of the individual constituent material costs as well as the compressive strength and other requirement. The optimization formulation is employed to minimize the cost function of the system while constraining it to meet the compressive strength and workability requirement. The results demonstrate the efficiency of the proposed approach to reduce the cost as well as to satisfy the above requirement.

An Approach for Structural-Acoustic Optimization of Ribbed Panels Using Component Mode Synthesis

2012 ◽  
Author(s):  
Micah R. Shepherd ◽  
Stephen A. Hambric
Keyword(s):  
Optimization Problem ◽  
Optimization Problems ◽  
Sound Radiation ◽  
Component Mode Synthesis ◽  
Complex Structures ◽  
Couple Dynamics ◽  
The Individual ◽  
Global Design Optimization ◽  
Control Designs ◽  
Speed And Accuracy

Component mode synthesis (CMS) is an approach used to couple dynamics of complex structures using modes of individual components. A CMS approach is developed to determine the response of a ribbed panel based on the individual rib and plate modes. The CMS method allows for rapid evaluation of noise-control designs as component modes need to be solved only once. Since efficient evaluation is required for global design optimization procedures, the CMS approach can be well suited in optimization problems. A simple structural-acoustic optimization problem was created to demonstrate the utility of the formulation by finding the optimal rib location and material to reduce sound radiation for a point-driven plate. Several parameters of the optimization algorithm are varied to test convergence speed and accuracy.

Effective Generation of Pareto Sets Using Genetic Programming

2001 ◽  
Author(s):  
John Eddy ◽  
Kemper Lewis
Keyword(s):  
Genetic Programming ◽  
Optimization Problem ◽  
Complete Solution ◽  
Pareto Frontier ◽  
Multi Objective ◽  
Pareto Sets ◽  
Effective Generation ◽  
Final Design ◽  
The Individual ◽  
Measure Of Performance

Abstract Many designers concede that there is typically more than one measure of performance for an artifact. Often, a large system is decomposed into smaller subsystems each having its own set of objectives, constraints, and parameters. The performance of the final design is a function of the performances of the individual subsystems. It then becomes necessary to consider the tradeoffs that occur in a multi-objective design problem. The complete solution to a multi-objective optimization problem is the entire set of non-dominated configurations commonly referred to as the Pareto set. Common methods of generating points along a Pareto frontier involve repeated conversion of multi-objective problems into single objective problems using weights. These methods have been shown to perform poorly when attempting to populate a Pareto frontier. This work presents an efficient means of generating a thorough spread of points along a Pareto frontier using genetic programming.

scholarly journals Locomotor Development Prediction Based on Statistical Model Parameters Identification

2012 ◽  
Vol 2012 ◽  
pp. 1-5
Author(s):  
A. V. Wildemann ◽  
A. A. Tashkinov ◽  
V. A. Bronnikov
Keyword(s):  
Optimization Problem ◽  
Real Data ◽  
Parameters Identification ◽  
Model Parameters ◽  
Large Set ◽  
Constrained Optimization Problem ◽  
Unknown Parameters ◽  
Locomotor Development ◽  
Feasible Solutions ◽  
The Individual

This paper introduces an approach for parameters identification of a statistical predicting model with the use of the available individual data. Unknown parameters are separated into two groups: the ones specifying the average trend over large set of individuals and the ones describing the details of a concrete person. In order to calculate the vector of unknown parameters, a multidimensional constrained optimization problem is solved minimizing the discrepancy between real data and the model prediction over the set of feasible solutions. Both the individual retrospective data and factors influencing the individual dynamics are taken into account. The application of the method for predicting the movement of a patient with congenital motility disorders is considered.

Commercial microwave links in urban rainfall-runoff modelling: Two different approaches to removing the bias

2020 ◽  
Author(s):  
Jaroslav Pastorek ◽  
Martin Fencl ◽  
Jörg Rieckermann ◽  
Vojtěch Bareš
Keyword(s):  
Wave Attenuation ◽  
Temporal Dynamics ◽  
Estimation Methods ◽  
Rainfall Runoff ◽  
Geophysical Research ◽  
Urban Catchment ◽  
Individual Level ◽  
The Individual ◽  
Commercial Microwave Links ◽  
Heavy Rainfalls

<p>Commercial microwave links (CMLs) are point-to-point radio connections widely used as cellular backhaul and thus very well covering urbanized areas. They can provide path-integrated quantitative precipitation estimates (QPEs) as they operate at frequencies where radio wave attenuation caused by raindrops is almost proportional to rainfall intensity. Pastorek et al. (2019b) demonstrated the feasibility of using CML QPEs to predict rainfall-runoff in a small urban catchment. Unfortunately, runoff volumes were highly biased, mostly for QPEs from short CMLs, although the temporal runoff dynamics were predicted very well, especially during heavy rainfall events. It was also shown that, for the heavy rainfalls, reducing the bias by adjusting the CML QPEs to traditional rainfall measurements (Fencl et al., 2017) leads to less accurate reproduction of the runoff temporal dynamics.</p><p>Current understanding is that the bias in CML QPEs is often caused by imprecise estimation of wet antenna attenuation (WAA), which is a complex process influenced by many physical phenomena, including radome hardware or positioning of the outdoor unit. However, traditional WAA estimation methods are typically unable to take into account all the individual-level factors. We proposed (Pastorek et al., 2019a) to estimate WAA separately for each of the examined CMLs by using discharge measurements at the outlet of a small urban catchment and showed that this approach can reduce the bias in CML QPEs, leading to generally satisfying performance of rainfall-runoff models, mainly for heavy rainfalls.</p><p>In the presented study, we evaluate the effect of the method proposed in Pastorek et al. (2019a) (method i) on rainfall-runoff modelling in more detail and compare it to the method of Fencl et al. (2017) (method ii). For a case study in Prague-Letňany, Czech Rep., a calibrated rainfall-runoff model is used to predict discharges at the outlet of the small urban catchment (1.3 km<sup>2</sup>) using QPEs from 16 CMLs. First results confirm that minimizing the bias in CML QPEs using method i is convenient mainly for heavy rainfalls, as Nash-Sutcliffe efficiency is considerably higher in this case for all but one CML (on average 0.65; only 0.40 for method ii). Moreover, method i preserves the information about the rainfall temporal dynamics during heavy rainfalls better than method ii for most of the individual CMLs (correlation coefficient with observed runoffs on average 0.83 for method i and 0.78 for method ii). Next steps should include generalization for other case studies, including an exploratory analysis of the potential mismatches.</p><p> </p><p>References</p><p>Fencl, M., Dohnal, M., Rieckermann, J., Bareš, V., 2017. Gauge-adjusted rainfall estimates from commercial microwave links. Hydrol. Earth Syst. Sci. 21, 617–634.</p><p>Pastorek, J., Fencl, M., Rieckermann, J. and Bareš, V., 2019b. Commercial microwave links for urban drainage modelling: The effect of link characteristics and their position on runoff simulations. Journal of environmental management 251, 109522.</p><p>Pastorek, J., Fencl, M., and Bareš, V., 2019a. Calibrating microwave link rainfall retrieval model using runoff observations. Geophysical Research Abstracts 21, EGU2019-10072.</p><p> </p><p>This study was supported by the project no. 20-14151J of the Czech Science Foundation and by the project of the Czech Technical University in Prague no. SGS19/045/OHK1/1T/11.</p>

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