A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS). Actor-Critic learning is used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to impro...

Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introduced, which has been shown to outperform previous semi-supervised clustering approaches. However, the setting of the kernel’s parameter is left to manual tuning, and the chosen value can largely affect the quality of ...

We provide a new way to compute and evaluate Gaussian radial basis function interpolants in a stable way with a special focus on small values of the shape parameter, i.e., for “flat” kernels. This work is motivated by the fundamental ideas proposed earlier by Bengt Fornberg and his co-workers. However, following Mercer’s theorem, an L2(R, ρ)-orthonormal expansion of the Gaussian kernel allows u...

In this paper, a status assessment model based on fuzzy comprehensive support vector machine (FC-SVM) is proposed for the scientific basis in the maintenance of secondary equipment in substation is insufficient. Then, an effective utilization and information extraction of various assessment factors is achieved by using fuzzy comprehensive assessment method (FCA) and the secondary equipment stat...

A piezo-resistive pressure sensor is made of silicon, the nature of which is considerably influenced by ambient temperature. The effect of temperature should be eliminated during the working period in expectation of linear output. To deal with this issue, an approach consists of a hybrid kernel Least Squares Support Vector Machine (LSSVM) optimized by a chaotic ions motion algorithm presented. ...

With the rapid and unregulated nature of urban expansion occurring in Chattogram, Bangladesh, adoption growth restriction mechanisms such as boundary (UGB) can provide a robust framework necessary to direct development built-up areas way that curtails environmentally sensitive city. Using support vector machine (SVM)-based simulation model, this paper examines future contiguous city aid delinea...

The flow field is difficult to evaluate, and underwater robotics can only partly adapt the submarine environment. However, fish sense complex environment by their lateral line system. In order reveal sensing mechanism, a robust nonlinear signal estimation method based on Volterra series model with Kautz kernel function provided, which named KKF-VSM. around square target used as original signal....

The Gaussian radial basis function (RBF) is a widely used kernel function in support vector machine (SVM). The kernel parameter σ is crucial to maintain high performance of the Gaussian SVM. Most previous studies on this topic are based on optimization search algorithms that result in large computation load. In this paper, we propose an analytical algorithm to determine the optimal σ with the p...

With more severe resource scarcity and environmental problems, the evaluation of circular economy in microcosmic level has become the focus of the academic world. Based on the concept of circular economy, this paper not only structures the evaluation index system of circular economy for iron and steel enterprises, builds the evaluation model of circular economy for iron and steel enterprises ba...

Predicting the maneuvering motion of an unmanned surface vehicle (USV) plays important role in intelligent applications. To more precisely predict this empirically, study proposes a method based on support vector regression with mixed kernel function (MK-SVR) combined polynomial (PK) and radial basis (RBF). A mathematical model USV was established subjected to zig-zag test DW-uBoat platform obt...