Multiple data parameter identification for nonlinear conceptual models

1997 ◽  
Vol 36 (5) ◽  
pp. 61-68 ◽  
Author(s):  
Hermann Eberl ◽  
Amar Khelil ◽  
Peter Wilderer
Keyword(s):  
Optimization Problem ◽  
Conceptual Models ◽  
Reference Data ◽  
Transport Model ◽  
Calibration Method ◽  
Data Sets ◽  
Multiple Data ◽  
Marquardt Algorithm ◽  
Multicriteria Optimization Problem ◽  
Higher Order Differential Equations

A numerical method for the identification of parameters of nonlinear higher order differential equations is presented, which is based on the Levenberg-Marquardt algorithm. The estimation of the parameters can be performed by using several reference data sets simultaneously. This leads to a multicriteria optimization problem, which will be treated by using the Pareto optimality concept. In this paper, the emphasis is put on the presentation of the calibration method. As an example identification of the parameters of a nonlinear hydrological transport model for urban runoff is included, but the method can be applied to other problems as well.

scholarly journals A new empirical model for stormwater TSS event mean concentrations (EMCs)

2011 ◽  
Vol 64 (9) ◽  
pp. 1926-1934 ◽  
Author(s):  
A. Dembélé ◽  
J.-L. Bertrand-Krajewski ◽  
C. Becouze ◽  
B. Barillon
Keyword(s):  
Empirical Model ◽  
Threshold Value ◽  
Calibration Method ◽  
Model Verification ◽  
Model Parameters ◽  
Data Sets ◽  
Combined System ◽  
Marquardt Algorithm ◽  
Rainfall Depth ◽  
Separate System

An empirical model for TSS event mean concentrations in storm weather discharges has been derived from the analysis of data sets collected in two experimental catchments (Chassieu, separate system and Ecully, combined system) in Lyon, France. Preliminary tests have shown that the values of TSS EMCs were linked to the variable X =TP ×ADWP (TP rainfall depth, ADWP antecedent dry weather period) with two distinct behaviours under and above a threshold value of X named λ: EMCs are increasing if X < λ and are decreasing if X > λ. An empirical equation is proposed for both behaviours. A specific calibration method is used to calibrate λ while the 4 other parameters of the model are calibrated by means of the Levenberg-Marquardt algorithm. The calibration results obtained with 8 events in both sites indicate that the model calibration is satisfactory: Nash Sutcliffe coefficients are all above 0.7. Monte Carlo simulations indicate a low variability of the model parameters for both sites. The model verification with 5 events in Chassieu shows maximum levels of uncertainty of approximately 20%, equivalent to levels of uncertainty observed in the calibration phase.

scholarly journals A tropospheric chemistry reanalysis for the years 2005–2012 based on an assimilation of OMI, MLS, TES, and MOPITT satellite data

2015 ◽  
Vol 15 (14) ◽  
pp. 8315-8348 ◽  
Author(s):  
K. Miyazaki ◽  
H. J. Eskes ◽  
K. Sudo
Keyword(s):  
Transport Model ◽  
Lower Troposphere ◽  
Tropospheric Chemistry ◽  
Atmospheric Environment ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Multiple Data ◽  
Multiple Data Sets ◽  
Observational Estimate ◽  
Multiple Species

Abstract. We present the results from an 8-year tropospheric chemistry reanalysis for the period 2005–2012 obtained by assimilating multiple data sets from the OMI, MLS, TES, and MOPITT satellite instruments. The reanalysis calculation was conducted using a global chemical transport model and an ensemble Kalman filter technique that simultaneously optimises the chemical concentrations of various species and emissions of several precursors. The optimisation of both the concentration and the emission fields is an efficient method to correct the entire tropospheric profile and its year-to-year variations, and to adjust various tracers chemically linked to the species assimilated. Comparisons against independent aircraft, satellite, and ozonesonde observations demonstrate the quality of the analysed O3, NO2, and CO concentrations on regional and global scales and for both seasonal and year-to-year variations from the lower troposphere to the lower stratosphere. The data assimilation statistics imply persistent reduction of model error and improved representation of emission variability, but they also show that discontinuities in the availability of the measurements lead to a degradation of the reanalysis. The decrease in the number of assimilated measurements increased the ozonesonde-minus-analysis difference after 2010 and caused spurious variations in the estimated emissions. The Northern/Southern Hemisphere OH ratio was modified considerably due to the multiple-species assimilation and became closer to an observational estimate, which played an important role in propagating observational information among various chemical fields and affected the emission estimates. The consistent concentration and emission products provide unique information on year-to-year variations in the atmospheric environment.

The development of nurses’ foundational values

2021 ◽  
pp. 096973302110032
Author(s):  
Sastrawan Sastrawan ◽  
Jennifer Weller-Newton ◽  
Gabrielle Brand ◽  
Gulzar Malik
Keyword(s):  
Professional Training ◽  
Reference Points ◽  
Constructivist Grounded Theory ◽  
Professional Values ◽  
Data Sets ◽  
Value System ◽  
Institutional Values ◽  
Multiple Data ◽  
Human Ethics ◽  
Multiple Data Sets

Background: In the ever-changing and complex healthcare environment, nurses encounter challenging situations that may involve a clash between their personal and professional values resulting in a profound impact on their practice. Nevertheless, there is a dearth of literature on how nurses develop their personal–professional values. Aim: The aim of this study was to understand how nurses develop their foundational values as the base for their value system. Research design: A constructivist grounded theory methodology was employed to collect multiple data sets, including face-to-face focus group and individual interviews, along with anecdote and reflective stories. Participants and research context: Fifty-four nurses working across various nursing settings in Indonesia were recruited to participate. Ethical considerations: Ethics approval was obtained from the Monash University Human Ethics Committee, project approval number 1553. Findings: Foundational values acquisition was achieved through family upbringing, professional nurse education and organisational/institutional values reinforcement. These values are framed through three reference points: religious lens, humanity perspective and professionalism. This framing results in a unique combination of personal–professional values that comprise nurses’ values system. Values are transferred to other nurses either in a formal or informal way as part of one’s professional responsibility and customary social interaction via telling and sharing in person or through social media. Discussion: Values and ethics are inherently interweaved during nursing practice. Ethical and moral values are part of professional training, but other values are often buried in a hidden curriculum, and attained and activated through interactions during nurses’ training. Conclusion: Developing a value system is a complex undertaking that involves basic social processes of attaining, enacting and socialising values. These processes encompass several intertwined entities such as the sources of values, the pool of foundational values, value perspectives and framings, initial value structures, and methods of value transference.

Auto-sharing parameters for transfer learning based on multi-objective optimization

2021 ◽  
pp. 1-13
Author(s):  
Hailin Liu ◽  
Fangqing Gu ◽  
Zixian Lin
Keyword(s):  
Transfer Learning ◽  
Optimization Problem ◽  
Data Sets ◽  
Multi Objective Optimization ◽  
Particle Swarm Optimizer ◽  
Real World Data ◽  
Data Set ◽  
Target Task ◽  
Main Research ◽  
Multi Objective

Transfer learning methods exploit similarities between different datasets to improve the performance of the target task by transferring knowledge from source tasks to the target task. “What to transfer” is a main research issue in transfer learning. The existing transfer learning method generally needs to acquire the shared parameters by integrating human knowledge. However, in many real applications, an understanding of which parameters can be shared is unknown beforehand. Transfer learning model is essentially a special multi-objective optimization problem. Consequently, this paper proposes a novel auto-sharing parameter technique for transfer learning based on multi-objective optimization and solves the optimization problem by using a multi-swarm particle swarm optimizer. Each task objective is simultaneously optimized by a sub-swarm. The current best particle from the sub-swarm of the target task is used to guide the search of particles of the source tasks and vice versa. The target task and source task are jointly solved by sharing the information of the best particle, which works as an inductive bias. Experiments are carried out to evaluate the proposed algorithm on several synthetic data sets and two real-world data sets of a school data set and a landmine data set, which show that the proposed algorithm is effective.

scholarly journals Critical Aspects of Person Counting and Density Estimation

2021 ◽  
Vol 7 (2) ◽  
pp. 21
Author(s):  
Roland Perko ◽  
Manfred Klopschitz ◽  
Alexander Almer ◽  
Peter M. Roth
Keyword(s):  
Density Estimation ◽  
Network Architecture ◽  
Reference Data ◽  
State Of The Art ◽  
Limit State ◽  
Ground Truth ◽  
Data Sets ◽  
Ground Truth Generation ◽  
Baseline Approach ◽  
Critical Aspects

Many scientific studies deal with person counting and density estimation from single images. Recently, convolutional neural networks (CNNs) have been applied for these tasks. Even though often better results are reported, it is often not clear where the improvements are resulting from, and if the proposed approaches would generalize. Thus, the main goal of this paper was to identify the critical aspects of these tasks and to show how these limit state-of-the-art approaches. Based on these findings, we show how to mitigate these limitations. To this end, we implemented a CNN-based baseline approach, which we extended to deal with identified problems. These include the discovery of bias in the reference data sets, ambiguity in ground truth generation, and mismatching of evaluation metrics w.r.t. the training loss function. The experimental results show that our modifications allow for significantly outperforming the baseline in terms of the accuracy of person counts and density estimation. In this way, we get a deeper understanding of CNN-based person density estimation beyond the network architecture. Furthermore, our insights would allow to advance the field of person density estimation in general by highlighting current limitations in the evaluation protocols.

scholarly journals Sunset–sunrise difference in solar occultation ozone measurements (SAGE II, HALOE, and ACE–FTS) and its relationship to tidal vertical winds

2015 ◽  
Vol 15 (2) ◽  
pp. 829-843 ◽  
Author(s):  
T. Sakazaki ◽  
M. Shiotani ◽  
M. Suzuki ◽  
D. Kinnison ◽  
J. M. Zawodny ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Seasonal Variations ◽  
Climate Model ◽  
Transport Model ◽  
Stratospheric Aerosol ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Latitude Range ◽  
Solar Occultation ◽  
Vertical Winds

Abstract. This paper contains a comprehensive investigation of the sunset–sunrise difference (SSD, i.e., the sunset-minus-sunrise value) of the ozone mixing ratio in the latitude range of 10° S–10° N. SSD values were determined from solar occultation measurements based on data obtained from the Stratospheric Aerosol and Gas Experiment (SAGE) II, the Halogen Occultation Experiment (HALOE), and the Atmospheric Chemistry Experiment–Fourier transform spectrometer (ACE–FTS). The SSD was negative at altitudes of 20–30 km (−0.1 ppmv at 25 km) and positive at 30–50 km (+0.2 ppmv at 40–45 km) for HALOE and ACE–FTS data. SAGE II data also showed a qualitatively similar result, although the SSD in the upper stratosphere was 2 times larger than those derived from the other data sets. On the basis of an analysis of data from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and a nudged chemical transport model (the specified dynamics version of the Whole Atmosphere Community Climate Model: SD–WACCM), we conclude that the SSD can be explained by diurnal variations in the ozone concentration, particularly those caused by vertical transport by the atmospheric tidal winds. All data sets showed significant seasonal variations in the SSD; the SSD in the upper stratosphere is greatest from December through February, while that in the lower stratosphere reaches a maximum twice: during the periods March–April and September–October. Based on an analysis of SD–WACCM results, we found that these seasonal variations follow those associated with the tidal vertical winds.

scholarly journals Evaluation of daily precipitation statistics and monsoon onset/retreat over western Sahel in multiple data sets

2014 ◽  
Vol 45 (5-6) ◽  
pp. 1325-1354 ◽  
Author(s):  
Emilia Paula Diaconescu ◽  
Philippe Gachon ◽  
John Scinocca ◽  
René Laprise
Keyword(s):  
Daily Precipitation ◽  
Monsoon Onset ◽  
Data Sets ◽  
Multiple Data ◽  
Western Sahel ◽  
Multiple Data Sets

Can earning much lead to doing good? Firm performance implications for corporate social responsibility

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Siyu Hou ◽  
Zhaoyang Guo ◽  
Chuangneng Cai ◽  
Xiaobo Jiao
Keyword(s):  
Corporate Social Responsibility ◽  
Firm Performance ◽  
Social Responsibility ◽  
State Ownership ◽  
Data Sets ◽  
Content Type ◽  
Multiple Data ◽  
Instrumental Variable Regression ◽  
Multiple Data Sets ◽  
Corporate Social

Purpose The purpose of this study is to examine the influence of firm performance on corporate social responsibility (CSR) and its possible moderating effect. Despite the significance of CSR, there remains an extensive debate about how it is affected by firm performance. Design/methodology/approach The conceptual model is mainly built on goal-setting theory. Based on archival data from multiple data sets on 1,650 companies, collected from 2010 to 2017, the hypotheses are tested using the two-stage instrumental variable regression method. Findings There is an inverted U-shaped relationship between firm performance and CSR that first increases and then decreases. In addition, considering the boundary conditions, state ownership makes the inverted U-shaped curve steeper, while high executive wage concentration makes the inverted U-shaped curve flatter. Research limitations/implications This study harmonizes the traditional contradictory findings of the influence of firm performance on CSR, that is, it supports a positive, negative or neutral relationship between the two. Originality/value This research provides a necessary structure for the CSR literature. By delving deeply into the relationship between firm performance and CSR, it enables scholars to better address the critical management question of whether earning more will lead to doing good.

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