scholarly journals Optimizing functional groups in ecosystem models: Case study of the Great Barrier Reef

2019 ◽  
Author(s):  
Vanessa Haller-Bull ◽  
Elena Rovenskaya
Keyword(s):  
Computational Cost ◽  
Structural Uncertainty ◽  
Model Resolution ◽  
Optimal Model ◽  
Ecosystem Models ◽  
Production Ratio ◽  
Simulated Network ◽  
Node Aggregation ◽  
Biomass Ratio

AbstractUncertainty is inherent in ecosystem modelling, however its effects on modelling results are often poorly understood or ignored. This study addresses the issue of structural uncertainty or, more specifically, model resolution and its impact on the analysis of ecosystem vulnerability to threats. While guidelines for node assignments exist, they are not underlined with quantitative analysis. Different resolutions of a coral reef network are investigated by comparing the simulated network dynamics over time in various threat scenarios. We demonstrate that the error between a higher-resolution and a lower-resolution models increases, first slowly then rapidly with increased degree of node aggregation. This informs the choice of an optimal model resolution whereby a finer level of a food web representation yields only minimal additional accuracy, while increasing computational cost substantially. Furthermore, our analysis shows that species biomass ratio and the production ratio are important parameters to guide node aggregation to minimize the error.

Pros and cons of time-dependent hybrid density functional approach to optical spectra of solids: a case study of CeO2

2021 ◽  
Author(s):  
Huai-Yang Sun ◽  
Shuo-Xue Li ◽  
Hong Jiang
Keyword(s):  
First Principles ◽  
Density Functional ◽  
Computational Cost ◽  
Optical Spectra ◽  
First Principles Calculation ◽  
Many Body ◽  
Many Body Perturbation Theory ◽  
Pros And Cons ◽  
Hybrid Density Functional

Prediction of optical spectra of complex solids remains a great challenge for first-principles calculation due to the huge computational cost of the state-of-the-art many-body perturbation theory based GW-Bethe Salpeter equation...

An Optimal Model for Low-Carbon Urban Agglomeration Based on Energy Structure Reduction under Uncertainty

2012 ◽  
Vol 599 ◽  
pp. 211-215
Author(s):  
Lun Wang ◽  
Zhao Sun ◽  
Jing Ya Wen ◽  
Zhuang Li ◽  
Wen Jin Zhao ◽  
...  
Keyword(s):  
Regional Planning ◽  
Energy Intensity ◽  
Greenhouse Gas Emission ◽  
Urban Agglomeration ◽  
Carbon Intensity ◽  
Energy Structure ◽  
Low Carbon ◽  
Optimal Model ◽  
The Sustainable Development

This paper developed an optimal model of low-carbon urban agglomeration on the base of energy structure under uncertainty. The case study shows that the carbon intensity was decreased by [32.19, 41.20] (%) and energy intensity was reduced by [34.08, 43.19] (%) compared with those in 2010; meanwhile, the carbon intensity and energy intensity in the core area was reduced by [50.88, 54.11] (%) and [51.24, 54.57] (%) respectively, compared with those in 2010. The optimized scheme could not only meet the requirements of 12th Five-Year Planning Outline of Controlling Greenhouse Gas Emission, but also complied with the requirements of regional planning targets. The established model also provided more decision-making space for the sustainable development of low-carbon urban agglomeration.

scholarly journals Modeling and Visualizing Smart City Mobility Business Ecosystems: Insights from a Case Study

Information ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 270 ◽  
Author(s):  
Anne Faber ◽  
Sven-Volker Rehm ◽  
Adrian Hernandez-Mendez ◽  
Florian Matthes
Keyword(s):  
Smart City ◽  
Design Science ◽  
Smart Cities ◽  
Knowledge Flows ◽  
Sustainable Mobility ◽  
Ecosystem Models ◽  
Business Ecosystem ◽  
Proactive Management ◽  
Business Ecosystems

Smart mobility is a central issue in the recent discourse about urban development policy towards smart cities. The design of innovative and sustainable mobility infrastructures as well as public policies require cooperation and innovations between various stakeholders—businesses as well as policy makers—of the business ecosystems that emerge around smart city initiatives. This poses a challenge for deploying instruments and approaches for the proactive management of such business ecosystems. In this article, we report on findings from a smart city initiative we have used as a case study to inform the development, implementation, and prototypical deployment of a visual analytic system (VAS). As results of our design science research we present an agile framework to collaboratively collect, aggregate and map data about the ecosystem. The VAS and the agile framework are intended to inform and stimulate knowledge flows between ecosystem stakeholders in order to reflect on viable business and policy strategies. Agile processes and roles to collaboratively manage and adapt business ecosystem models and visualizations are defined. We further introduce basic categories for identifying, assessing and selecting Internet data sources that provide the data for ecosystem models and we detail the ecosystem data and view models developed in our case study. Our model represents a first explication of categories for visualizing business ecosystem models in a smart city mobility context.

scholarly journals A Case Study in Connecting Fisheries Management Challenges With Models and Analysis to Support Ecosystem-Based Management in the California Current Ecosystem

2021 ◽  
Vol 8 ◽  
Author(s):  
Desiree Tommasi ◽  
Yvonne deReynier ◽  
Howard Townsend ◽  
Chris J. Harvey ◽  
William H. Satterthwaite ◽  
...  
Keyword(s):  
Fisheries Management ◽  
West Coast ◽  
California Current ◽  
Fishing Communities ◽  
Target Species ◽  
Ecosystem Models ◽  
Protected Species ◽  
Forage Species ◽  
The U.S

One of the significant challenges to using information and ideas generated through ecosystem models and analyses for ecosystem-based fisheries management is the disconnect between modeling and management needs. Here we present a case study from the U.S. West Coast, the stakeholder review of NOAA’s annual ecosystem status report for the California Current Ecosystem established by the Pacific Fisheries Management Council’s Fisheries Ecosystem Plan, showcasing a process to identify management priorities that require information from ecosystem models and analyses. We then assess potential ecosystem models and analyses that could help address the identified policy concerns. We screened stakeholder comments and found 17 comments highlighting the need for ecosystem-level synthesis. Policy needs for ecosystem science included: (1) assessment of how the environment affects productivity of target species to improve forecasts of biomass and reference points required for setting harvest limits, (2) assessment of shifts in the spatial distribution of target stocks and protected species to anticipate changes in availability and the potential for interactions between target and protected species, (3) identification of trophic interactions to better assess tradeoffs in the management of forage species between the diet needs of dependent predators, the resilience of fishing communities, and maintenance of the forage species themselves, and (4) synthesis of how the environment affects efficiency and profitability in fishing communities, either directly via extreme events (e.g., storms) or indirectly via climate-driven changes in target species availability. We conclude by exemplifying an existing management process established on the U.S. West Coast that could be used to enable the structured, iterative, and interactive communication between managers, stakeholders, and modelers that is key to refining existing ecosystem models and analyses for management use.

scholarly journals Research on Optimization of Port Container Inland Collection and Distribution Network

2020 ◽  
Vol 165 ◽  
pp. 06024
Author(s):  
Xuan Wang ◽  
Yun Jing
Keyword(s):  
Distribution Network ◽  
Distribution Networks ◽  
Development Strategies ◽  
Optimal Model ◽  
Matlab Software ◽  
Belt And Road ◽  
Network Costs ◽  
The Belt And Road

With the advancement of country’s “the Belt and Road” strategy, each port is actively formulating development strategies to help implement the strategy. The port inland collection and distribution network is an important guarantee for the development of the port, and it is a key component to promote the connection between the port and the inland hinterland. It has an important role in expanding the scale of the port and improving the overall competitiveness of the port. Aiming at the current imbalance of the collection and distribution methods and the imperfect collection and distribution networks in most ports, this paper establishes an optimal model of collection and distribution network costs and quantitatively optimizes the collection and distribution network corridors. The Tianjin Port is selected as a case study object. And the MATLAB software is used to solve the analysis. The conclusion is that Tianjin Port could alleviate the pressure of the collection and distribution network by increasing the density of container trains with the hinterland cities, which verified the validity of the model.

Using Bayesian Optimization With Knowledge Transfer for High Computational Cost Design: A Case Study in Photovoltaics

2019 ◽  
Author(s):  
Mine Kaya ◽  
Shima Hajimirza
Keyword(s):  
Solar Cells ◽  
Design Problem ◽  
Cost Optimization ◽  
Computational Cost ◽  
Design Procedure ◽  
Bayesian Optimization ◽  
Optimization Framework ◽  
Previous Design ◽  
High Computational Cost

Abstract Engineering design is usually an iterative procedure where many different configurations are tested to yield a desirable end performance. When the design objective can only be measured by costly operations such as experiments or cumbersome computer simulations, a thorough design procedure can be limited. The design problem in these cases is a high cost optimization problem. Meta model-based approaches (e.g. Bayesian optimization) and transfer optimization are methods that can be used to facilitate more efficient designs. Transfer optimization is a technique that enables using previous design knowledge instead of starting from scratch in a new task. In this work, we study a transfer optimization framework based on Bayesian optimization using Gaussian Processes. The similarity among the tasks is determined via a similarity metric. The framework is applied to a particular design problem of thin film solar cells. Planar multilayer solar cells with different sets of materials are optimized to obtain the best opto-electrical efficiency. Solar cells with amorphous silicon and organic absorber layers are studied and the results are presented.

scholarly journals Vibration-Based Structural Health Monitoring Using Piezoelectric Transducers and Parametric t-SNE

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1716
Author(s):  
David Agis ◽  
Francesc Pozo
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Changes ◽  
Computational Cost ◽  
Principal Component ◽  
Piezoelectric Transducers ◽  
Majority Voting ◽  
Structural Health

In this paper, we evaluate the performance of the so-called parametric t-distributed stochastic neighbor embedding (P-t-SNE), comparing it to the performance of the t-SNE, the non-parametric version. The methodology used in this study is introduced for the detection and classification of structural changes in the field of structural health monitoring. This method is based on the combination of principal component analysis (PCA) and P-t-SNE, and it is applied to an experimental case study of an aluminum plate with four piezoelectric transducers. The basic steps of the detection and classification process are: (i) the raw data are scaled using mean-centered group scaling and then PCA is applied to reduce its dimensionality; (ii) P-t-SNE is applied to represent the scaled and reduced data as 2-dimensional points, defining a cluster for each structural state; and (iii) the current structure to be diagnosed is associated with a cluster employing two strategies: (a) majority voting; and (b) the sum of the inverse distances. The results in the frequency domain manifest the strong performance of P-t-SNE, which is comparable to the performance of t-SNE but outperforms t-SNE in terms of computational cost and runtime. When the method is based on P-t-SNE, the overall accuracy fluctuates between 99.5% and 99.75%.

An Analysis of Computational Cost in Image Processing: A Case Study

1978 ◽  
Vol C-27 (10) ◽  
pp. 904-910 ◽  
Author(s):  
Cordella ◽  
Duff ◽  
Levialdi
Keyword(s):  
Image Processing ◽  
Computational Cost
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