In this work, a new three-way receptor model, called "multi-site three way factor analysis" model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between ...
[16 hours] Directed research (weighted factor model) [10 hours] Finding and talking to experts (experts) [20 hours] Cost-effectiveness analysis creation (CEA) [4 hours] Directed research (weighted factor model) [10 hours]Summary writingand internal contemplation (informed consideration) ...
A weight coefficient is used in this new model to account for the contribution of each factor to the node degree. The proposed model is compared with the traditional degree model and an accessibility-based vulnerability model in the vulnerability analysis of a highway network. Experiment results ...
We study optimal design of the Exponentially Weighted Moving Average (EWMA) chart by a proper choice of the smoothing factor and the initial value (headstart) of the decision statistic. The particular problem addressed is that of quickest detection of an abrupt change in the parameter of a disc...
For Landsat ETM+ data, comparison of OLS and GWR models has been made to see the improvement in GWR model. However, the hot spot analysis of residuals is not essential as GWR has clearly provided an improved model when compared to OLS. The comparison of OLS and GWR results of models and...
A Fotheringham - 《Geographical Analysis》 被引量: 0发表: 2022年 The modeling of human development index (HDI) in Papua—Indonesia using geographically weighted ridge regression (GWRR) In regression model, there are several assumptions which have to be fulfilled, one of which is the absence of...
Grey Relational Analysis Model Based on Weighted Entropy and its Application In order to improve the low evaluation precision that the grey relational analysis method has been, the entropy theory was integrated to establish a new mo... G Li,F Qiang,G Li - International Conference on Wireless ...
The performance of the proposed KCGWO for clustering is initially compared with standalone K-means clustering algorithms and the Gaussian Mixture Model (GMM). The non-linear, unsupervised t-distributed Stochastic Neighbor Embedding (t-SNE) is typically employed for data analysis and high-dimensional ...
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Combined with a corresponding refined analysis of the algorithm, this results in a faster running time of O⁎(1.415t) on graphs of bounded degree 3. Interestingly, given a vertex cover U of the input graph G=(V,E), the rules of the algorithm in [11] rely only on the structure of ...