as in regular lattices. Communication is efficient because distances are orders of magnitude smaller than the system size. In real networks, the small world property is generally coupled with a high average clustering coefficient. The Watts–Strogatz model...
WFN are scale-free, the exponent being the fractal dimension. WFN exhibit the “small-world” property (i.e. slow (logarithmic) increase of the average shortest path with the network size) and large average clustering coefficient. Thus, the fractal dimension of weighted polymer networks is ...
This will make the above formula for ρk somewhat more concrete. Simulations and Correlograms MA(1) Let's start with a MA(1) process. If we set β1=0.6 we obtain the following model: xt=wt+0.6wt−1 As with the AR(p) models in the previous article we can use R to s...
Hence, for the above division of the finite, discrete representation pn of the continuous probability distribution p(x) one obtains the following grouping formula corresponding to the ordered (sequential) groups of histogramic points, (3.6.3)….<x1,α−1<x2,α−1,…<x1,α<x2,α,…<x1...
We have previously suggested that when reporting and interpreting risk factors, measures of average associations should be accompanied by analyses of heterogeneity using measures of DA, such as the area under the ROC curve or the intra-class correlation coefficient (ICC) obtained in multilevel ...
The maximum dissimilarity algorithm (a data-clustering algorithm) is used to separate the existing data sets in the training, validation, and testing groups to feed GP algorithm. Finally, by weighted combination, a new velocity formula with high accuracy and physical basis is proposed for submerged...
Based on the GPS data of floating cars in Chengdu in November 2016, we adopted a K-means Clustering algorithm to calculate the frequency distribution. Based on the frequency-intensive areas of GPS data and historical data, we also used the Pearson correlation coefficient [29] to analyze the co...
Keywords: average wind power; interval forecasts; optimal subtractive clustering method; ANFIS; SSA; Model comparison 1. Introduction 1.1. Motivation Given the important environmental advantages of renewable energy sources, the installation of wind power plants has significantly increased in most ...