the present article investigates the application of high order tsk (takagi sugeno kang) fuzzy systems in modeling photo voltaic (pv) cell characteristics. a method has been introduced for training second order tsk fuzzy systems using anfis (artificial neural fuzzy inference system) training method. it is clear that higher order tsk fuzzy systems are more precise approximators while they cover n...

In this paper, subtractive clustering method is combined with least squares estimation algorithms to pre-identify a type-1 Takagi-Sugeno-Kang (TSK) fuzzy model from input/output data. Then the type-2 fuzzy theory is used to expand the type-1 model to a type-2 model. A sensitivity analysis is used to ascertain how a type-1 TSK model output depends upon the pre-initialized parameters and determin...

Transfer learning can address the tasks of unlabeled data in target domain by leveraging plenty labeled from a different but related source domain. A core issue transfer is to learn shared feature space where distributions two domains are matched. This process be named as representation (TRL). Feature transformation methods crucial ensure success TRL. The most commonly used method TRL kernel-ba...

Changes in the skin temperature (Tsk) are known to be connected with diseases and subsequently infrared thermography (IRT) has been proposed to be a diagnostic aid, e.g. in musculoskeletal disorders (MSD). However, mostly due to conflicting results of previous studies, IRT lost credibility. Now interest in IRT is growing again but valid methodological studies are needed in order to avoid new di...

The paper presents a modified structure of Takaga-Sugeno-Kang (TSK) network with a fully automated building and learning algorithm. The modification has resulted in a great reduction of nonlinear parameters of the network (almost three times). The modified network can be initiated using Gustafson-Kessel clustering algorithm. After initiation all parameters are further fine-tuned by an gradient ...

in this paper, a theorem is derived for the existence of a common quadratic Lyapunov function for stability analysis of TSK fuzzy model. This paper proposed a new method based on stochastic stability. In this paper we study the stochastic stability properties of certain TSK Fuzzy system has been studied.

OBJECTIVES Modify the Tampa Scale for Kinesiophobia (TSK) for 'fear of passive motion' beliefs. METHODS With permission, a 14-item modification, the TSK-PM (passive movement), was created. Test-retest reliability was tested first. Construct validity was tested in chronic whiplash patients by comparing the TSK-PM with the TSK, the Neck Disability Index (NDI) and cervical ranges of motion. RE...

The Tight skin (Tsk) mutation is a duplication of the mouse fibrillin 1 (Fbn1) gene that results in a larger (418 kD) than normal (350 kD) protein; Tsk/+ mice display increased connective tissue, bone overgrowth, and lung emphysema. Lung emphysema, bone overgrowth, and vascular complications are the distinctive traits of mice with reduced Fbn1 gene expression and of Marfan syndrome (MFS) patien...

This article presents a new learning methodology based on a hybrid algorithm for interval type-2 TSK fuzzy logic systems (FLS). Using input-output data pairs during the forward pass of the training process, the interval type-2 TSK FLS output is calculated and the consequent parameters are estimated by recursive least-squares (RLS) method. In the backward pass, the error propagates backward, and...

To achieve an effective and safe operation on the machine system where the human interacts with the machine mutually, there is a need for the machine to understand the human state, especially cognitive state, when the human’s operation task demands an intensive cognitive activity. Due to a well-known fact with the human being, a highly uncertain cognitive state and behavior as well as expressio...