On the Impact of Small-World on Local Search

2005 ◽  
pp. 13-24 ◽  
Author(s):  
Andrea Roli
Keyword(s):  
Local Search ◽  
Small World ◽  
The Impact

Predictive Control and Simulation for Variable-Pitch Wind Turbines

2012 ◽  
Vol 562-564 ◽  
pp. 1012-1015
Author(s):  
S.X. Wang ◽  
Z.X. Li ◽  
D.X. Sun ◽  
X.X. Xie
Keyword(s):  
Neural Network ◽  
Predictive Control ◽  
Small World ◽  
Modeling Method ◽  
Reference Trajectory ◽  
System Delay ◽  
Variable Pitch ◽  
Electricity Grid ◽  
System Output ◽  
The Impact

In order to avoid the limitations of traditional mechanism modeling method, a neural network (NN) model of variable - pitch wind turbine is built by the NN modeling method based on field data. Then considering that from wind turbine’s startup to grid integration, the generator speed must be controlled to rise to the synchronous speed smoothly and precisely, a neural network model predictive control (NNMPC) strategy based on the small-world optimization algorithm (SWOA) is proposed. Simulation results show that the strategy can forecast the change of generator rotational speed based on the wind speed disturbance, making the controller act ahead to eliminate the impact of system delay. Furthermore, the system output can track the reference trajectory well, making sure that the system can connect the electricity grid steadily.

scholarly journals Emergent properties in microbiome networks reveal the anthropogenic disturbance of farming practices in vineyard soil fungal communities

2020 ◽  
Author(s):  
Rüdiger Ortiz-Álvarez ◽  
Hector Ortega-Arranz ◽  
Vicente J. Ontiveros ◽  
Charles Ravarani ◽  
Alberto Acedo ◽  
...  
Keyword(s):  
Small World ◽  
Fungal Communities ◽  
Local Network ◽  
Emergent Properties ◽  
Farming Practices ◽  
Natural Systems ◽  
Vineyard Soil ◽  
Global Agriculture ◽  
Network Properties ◽  
The Impact

AbstractAgro-ecosystems are human-managed natural systems, and therefore are subject to generalized ecological rules. A deeper understanding of the factors impacting on the biotic component of ecosystem stability is needed for promoting the sustainability and productivity of global agriculture. Here we propose a method to determine ecological emergent properties through the inference of network properties in local microbial communities, and to use them as biomarkers of the anthropogenic impact of different farming practices on vineyard soil ecosystem functioning. In a dataset of 350 vineyard soil samples from USA and Spain we observed that fungal communities ranged from random to small-world network arrangements with differential levels of niche specialization. Some of the network properties studied were strongly correlated, defining patterns of ecological emergent properties that are influenced by the intensification level of the crop management. Low-intervention practices (from organic to biodynamic approaches) promoted densely clustered networks, describing an equilibrium state based on mixed (generalist-collaborative) communities. Contrary, in conventionally managed vineyards, we observed highly modular (niche-specialized) low clustered communities, supported by a higher degree of selection (more co-exclusion proportion). We also found that, although geographic factors can explain the different fungal community arrangements in both countries, the relationship between network properties in local fungal communities better capture the impact of farming practices regardless of the location. Thus, we hypothesize that local network properties can be globally used to evaluate the effect of ecosystem disturbances in crops, but also in when evaluating the effect of clinical interventions or to compare microbiomes of healthy vs. disturbed conditions.

scholarly journals A Node-Based SIRS Epidemic Model with Infective Media on Complex Networks

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Leyi Zheng ◽  
Longkun Tang
Keyword(s):  
Epidemic Model ◽  
Small World ◽  
Spreading Rate ◽  
Node Degree ◽  
Strong Positive Correlation ◽  
Globally Asymptotically Stable ◽  
Sirs Epidemic Model ◽  
Theoretical Investigations ◽  
Fully Connected ◽  
The Impact

We focus on the node-based epidemic modeling for networks, introduce the propagation medium, and propose a node-based Susceptible-Infected-Recovered-Susceptible (SIRS) epidemic model with infective media. Theoretical investigations show that the endemic equilibrium is globally asymptotically stable. Numerical examples of three typical network structures also verify the theoretical results. Furthermore, comparison between network node degree and its infected percents implies that there is a strong positive correlation between both; namely, the node with bigger degree is infected with more percents. Finally, we discuss the impact of the epidemic spreading rate of media as well as the effective recovered rate on the network average infected state. Theoretical and numerical results show that (1) network average infected percents go up (down) with the increase of the infected rate of media (the effective recovered rate); (2) the infected rate of media has almost no influence on network average infected percents for the fully connected network and NW small-world network; (3) network average infected percents decrease exponentially with the increase of the effective recovered rate, implying that the percents can be controlled at low level by an appropriate large effective recovered rate.

scholarly journals Evolution and Determinants of an Air Transport Network: A Case Study of the Chinese Main Air Transport Network

2019 ◽  
Vol 11 (14) ◽  
pp. 3933 ◽  
Author(s):  
Min Su ◽  
Weixin Luan ◽  
Zeyang Li ◽  
Shulin Wan ◽  
Zhenchao Zhang
Keyword(s):  
Network Structure ◽  
High Speed ◽  
Information Source ◽  
Small World ◽  
Transport Network ◽  
Air Transport ◽  
Promoting Effect ◽  
High Speed Rail ◽  
Path Lengths ◽  
The Impact

The Chinese main air transport network (CMATN) is the framework for air passenger transport in the country. This study uses complex networks and an econometric model to analyze CMATN’s evolution and determinants. In terms of overall network structure, the network has always shown small-world properties, with smaller average path lengths (2.06–2.15) and larger clustering coefficients (0.68–0.77), while its cumulative degree distribution follows an exponential function. City passenger volumes conform to the degree power law function, which means that the more destinations a city connects to, the higher its passenger traffic will be. In major hub cities, such as Beijing, Shanghai, and Guangzhou, control power decreases, while Chengdu, Kunming, Chongqing, Xi’an, Urumqi, and other cities play an increasingly important role in CMATN. In terms of main route passenger volumes and formation, increases in GDP and tourism have had a promoting effect, while high-speed rail (HSR) poses a threat to overlapping routes. CMATN is primarily located in the central and eastern regions, focusing on China’s economy, tourism, and efficient HSR development. Although the competition from HSR affects the overall network structure of CMATN based on its influence on specific routes, we believe that the impact is limited due to the different transport attributes of the two networks. The research results of this study can become an information source for decision makers and provide a reference for air transport to seek sustainable development.

Network and equation-based models in epidemiology

2018 ◽  
Vol 11 (03) ◽  
pp. 1850046 ◽  
Author(s):  
Kossi Edoh ◽  
Elijah MacCarthy
Keyword(s):  
Network Models ◽  
Small World ◽  
Control Measures ◽  
Network Structures ◽  
Scale Free ◽  
Measles Outbreak ◽  
Spanish Flu ◽  
Spread Of Infection ◽  
Aggregate Population ◽  
The Impact

Network and equation-based (EB) models are two prominent methods used in the study of epidemics. While EB models use a global approach to model aggregate population, network models focus on the behavior of individuals in the population. The two approaches have been used in several areas of research, including finance, computer science, social science and epidemiology. In this study, epidemiology is used to contrast EB models with network models. The methods are based on the assumptions and properties of compartmental models. In EB models we solve a system of ordinary differential equations and in network models we simulate the spread of epidemics on contact networks using bond percolation. We examine the impact of network structures on the spread of infection by considering various networks, including Poisson, Erdős Rényi, Scale-free, and Watts–Strogatz small-world networks, and discuss how control measures can make use of the network structures. In addition, we simulate EB assumptions on Watts–Strogatz networks to determine when the results are similar to that of EB models. As a case study, we use data from the 1918 Spanish flu pandemic and that from measles outbreak to validate our results.

scholarly journals Disentangling network topology and pathogen spread

2021 ◽  
Author(s):  
Maria Perez-Ortiz ◽  
Petru Manescu ◽  
Fabio Caccioli ◽  
Delmiro Fernandez-Reyes ◽  
Parashkev Nachev ◽  
...  
Keyword(s):  
Network Topology ◽  
Large Scale ◽  
Social Contact ◽  
Small World ◽  
Pathogen Transmission ◽  
Stochastic Simulations ◽  
Equal Weight ◽  
Topological Features ◽  
Network Metrics ◽  
The Impact

How do we best constrain social interactions to prevent the transmission of communicable respiratory diseases? Indiscriminate suppression, the currently accepted answer, is both unsustainable long term and implausibly presupposes all interactions to carry equal weight. Transmission within a social network is determined by the topology of its graphical structure, of which the number of interactions is only one aspect. Here we deploy large-scale numerical simulations to quantify the impact on pathogen transmission of a set of topological features covering the parameter space of realistic possibility. We first test through a series of stochastic simulations the differences in the spread of disease on several classes of network geometry (including highly skewed networks and small world). We then aim to characterise the spread based on the characteristics of the network topology using regression analysis, highlighting some of the network metrics that influence the spread the most. For this, we build a dataset composed of more than 9000 social networks and 30 topological network metrics. We find that pathogen spread is optimally reduced by limiting specific kinds of social contact -- unfamiliar and long range -- rather than their global number. Our results compel a revaluation of social interventions in communicable diseases, and the optimal approach to crafting them.

scholarly journals Organization of Areal Connectivity in the Monkey Frontoparietal Network

2020 ◽  
Author(s):  
Bryan D. Conklin
Keyword(s):  
Cognitive Functions ◽  
Large Scale ◽  
Small World ◽  
Connectivity Matrix ◽  
Anatomical Connectivity ◽  
Optimal Arrangement ◽  
Frontoparietal Network ◽  
Simultaneous Integration ◽  
Single Scale ◽  
The Impact

AbstractAnatomical connectivity between cortical areas condition the set of observable functional activity in a neural network. The large-scale cortical monkey frontoparietal network (FPN) has been shown to facilitate complex cognitive functions. However, the organization of anatomical connectivity between areas in the FPN supporting such function is unknown. Here, a new connectivity matrix is proposed which shows the FPN utilizes a small-world architecture with an over-reliance on the M9 dynamical relay 3-node motif and degree distributions which can be characterized as single scale. The FPN uses its small-world architecture to achieve the kind of simultaneous integration and specialization of function which cognitive functions like attention and working memory require. Contrary to many real-world networks, the in and out single scale degree distributions illustrate the relatively homogeneous connectivity of each area in the FPN, suggesting an absence of hubs. Crucially, the M9 dynamical relay motif is the optimal arrangement for previously reported near-zero and non-zero phase synchrony to propagate through the network, serving as a candidate topological mechanism. These results signify the impact of the organization of anatomical connectivity in the FPN. They can serve as a benchmark to be used in the network-level treatment of neurological disorders where the types of cognition the FPN supports are impaired. Additionally, they can inform future neuromorphic circuit designs which aim to perform aspects of cognition.

The impact of small world on innovation: An empirical study of 16 countries

2010 ◽  
Vol 4 (1) ◽  
pp. 97-106 ◽  
Author(s):  
Zifeng Chen ◽  
Jiancheng Guan
Keyword(s):  
Empirical Study ◽  
Small World ◽  
The Impact
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