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His research interests include image processing, soft computing, computer vision, and medical image analysis.
Table 1 Development of the soft computing boundaries [2] Methods Presenters Years Neural network McCulloch 1943 Evolutionary computing Rechenberg 1960 Fuzzy logic Zadeh 1965 Soft computing Zadeh 1981.
Soft computing.
The conclusion part is determined using soft computing techniques.
Therefore, soft computing can be applied to solve it.
His research interest are Power system and soft computing technique.
Fig. 2 Overview of main soft computing techniques.
This paper reviews the development of soft computing techniques.
A soft computing based prediction model was developed.
Intelligent soft computing scheme Support Vector Regression (SVR) is implemented.
This paper is structured as follows: "Social computing" section overviews the main stream soft computing techniques; Then, a comprehensive taxonomy and its soft computing techniques based SNA approaches are presented in "Soft computing" section.
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