A soft linen emulsion rate intelligent control system based on the domain interpolation algorithm with self adjusting is introduced. In the hemp textile industry, soft linen deal processes can directly affect its following process. We take the lead to use the fuzzy control method applied in soft linen emulsion rate of Intelligent Control System. In the research process, the improvement of produ...

In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the most commonly used clustering method. However, the FCM algorithm is usually affected by initializations. Incorporating FCM into switching regressions, called the fuzzy c-regressions (FCR), has also the same drawback as FCM, where bad initializations may cause difficulties in obtaining appropriate clustering and regression results. In...

Fuzzy clustering based on generalized entropy is studied. By introducing the generalized entropy into objective function of fuzzy clustering, a unified model is given for fuzzy clustering in this paper. Then fuzzy clustering algorithm based on the generalized entropy is presented. At the same time, by introducing the spatial information of image into the generalized entropy fuzzy clustering alg...

Train energy saving problem investigates how to control train's velocity such that the quantity of energy consumption is minimized and some system constraints are satis ed. On the assumption that the train's weights on different links are estimated by fuzzy variables when making the train scheduling strategy, we study the fuzzy train energy saving problem. First, we propose a fuzzy energy ...

In the past, we demonstrated how fuzzy concepts can easily be used in the Johnson algorithm for managing uncertain scheduling on two-machine flow shops. This paper extends these concepts to fuzzy flow shops with more than two machines. A new fuzzy heuristic flow-shop scheduling algorithm (the fuzzy Gupta algorithm) is then designed since optimal solutions seem unnecessary for uncertain environm...

Advantages of a fuzzy predictive control algorithm are discussed in the paper. The discussed fuzzy predictive algorithm is a combination of a DMC (Dynamic Matrix Control) algorithm and Takagi–Sugeno fuzzy modeling inheriting advantages of both techniques. The algorithm is numerically effective. Moreover, information about measured disturbance can be included in it in an easy way. A simple and e...

Middle spatial resolution multi-spectral remote sensing image is a kind of color image with low contrast, fuzzy boundaries and informative features. In view of these features, the fuzzy C-means clustering algorithm is an ideal choice for image segmentation. However, fuzzy C-means clustering algorithm requires a pre-specified number of clusters and costs large computation time, which is easy to ...