the purpose of this study was to estimate the torque from high‑density surface electromyography signals of biceps brachii, brachioradialis, and the medial and lateral heads of triceps brachii muscles during moderate‑to‑high isometric elbow flexion‑extension. the elbow torque was estimated in two following steps: first, surface electromyography (emg) amplitudes were estimated using principal com...

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) methodology for the backcalculation of airport flexible pavement layer moduli. The proposed ANFIS-based backcalculation approach employs a hybrid learning procedure to construct a non-linear input-output mapping based on qualitative aspects of human knowledge and pavement engineering experience incorporated in...

In the current paper, consider the fuzzy normed linear space $(X,N)$ which is defined by Bag and Samanta. First, we construct a new fuzzy topology on this space and show that these spaces are Hausdorff locally convex fuzzy topological vector space. Some necessary and sufficient conditions are established to illustrate that the presented fuzzy topology is equivalent to two previously studied fuz...

This paper presents a new hybrid neuro-fuzzy model which is capable of learning structure and parameters by means of recursive binary space partitioning BSP. Introduction Neuro-fuzzy systems (NFSs) [1] combine the learning ability of artificial neural nets (ANNs) with the linguistic interpretation capacity of fuzzy inference systems (FISs) [2]. This work makes use of BSP (Binary Space Partition...

In this paper, dynamic modeling of a Vestas 660 kW wind turbine and its validation are performed based on operational data extracted from Eoun-Ebn-Ali wind farm in Tabriz, Iran. The operational data show that the turbine under study, with a classical PI controller, encounters high fluctuations when controlling the output power at its rated value. The turbine modeling is performed by deriving th...

In this paper we propose adaptive brain-inspired emotional decayed learning to predict Kp, AE and Dst indices that characterize the chaotic activity of the earth's magnetosphere by their extreme lows and highs. In mammalian brain, the limbic system processes emotional stimulus and consists of two main components: Amygdala and Orbitofrontal Cortex (OFC). Here, we propose a learning algorithm for...

OBJECTIVES To develop a neuro-fuzzy system to predict the presence of prostate cancer. Neuro-fuzzy systems harness the power of two paradigms: fuzzy logic and artificial neural networks. We compared the predictive accuracy of our neuro-fuzzy system with that obtained by total prostate-specific antigen (tPSA) and percent free PSA (%fPSA). METHODS The data from 1030 men (both outpatients and ho...

Abstract: An adaptive identifier for neuro-fuzzy control system nonlinear dynamic object operating in conditions of uncertainty intrinsic properties and the environment. The algorithms of structural and parametric identification in real time are a combination of an identification algorithm coefficients of linear management and methods of the theory of interactive adaptation. Adaptive neuro-fuzz...