Recently, clustering algorithms combined conventional methods and artificial intelligence. FSCSOM is designed to handle the problem of SOM, such as defining the number of clusters and initial value of neuron weights. FSC find the number of clusters and the cluster centers which become the parameter of SOM. FSC-SOM is expected to improve the quality of FSC since the determination of the cluster ...

The basic concept of the subtractive clustering algorithm is to choose a data point that has highest density (potential) in space (variable) as center cluster. number and position cluster centers formed are influenced by given radius (r) parameter value. If value very small, it will result neglect potential points around too large, increases contribution all points, thereby canceling effect den...

Design of a decision-aiding model between subtractive manufacturing and 3Dprinting Tuan Minh Ryan Pham and Colton Harrison 3D-printing is becoming more and more widely used in industry. As this happens, manufacturers are becoming unsure of when to use this new technology and when to trudge on with subtractive (conventional) manufacturing processes. Subtractive manufacturing processes are well-e...

The existence of recorded accelerograms to perform dynamic inelastic time history analysis is of the utmost importance especially in near-fault regions where directivity pulses impose extreme demands on structures and cause widespread damages. But due to the scarcity of recorded acceleration time histories, it is common to generate proper artificial ground motions. In this paper an alternative ...

in this research, the framework is presented for unsupervised change detection using multitemporal sar images based on integration clustering and level set methods. spatial correlation between pixels were considered by using contextual information. also as proposed method was used integration of gustafson-kessel clustering techniques (gkc) and level set methods for change detection. using clust...

Support vector regression (SVR) is a learning method based on the support vector machine (SVM) that can be used for curve fitting and function estimation. In this paper, the ability of the nu-SVR to predict the catalytic activity of the Fischer-Tropsch (FT) reaction is evaluated and the result is compared with two other prediction techniques including: multilayer perceptron (MLP) and subtractiv...