Objective: This research is focused in the creation and validation of a solution to the inverse kinematics problem for a 6 degrees of freedom human upper limb. This system is intended to work within a realtime dysfunctional motion prediction system that allows anticipatory actuation in physical Neurorehabilitation under the assisted-as-needed paradigm. For this purpose, a multilayer perceptron-...

This paper analyzes the performance of two different maximum power point tracking (MPPT) algorithms for photovoltaic (PV) system: artificial neural network (ANN) and adaptive neuro fuzzy inference (ANFIS) as used by an interleaved soft switching boost converter (ISSBC) system with different conditions, such as partially shaded, condition, changing solar insolation and PV cell temperature. Howev...

The present study investigates the prediction efficiency of nonlinear system-identification models, in assessing the behavior of a coupled structure-passive vibration controller. Two system-identification models, including Nonlinear AutoRegresive with eXogenous inputs (NARX) and adaptive neuro-fuzzy inference system (ANFIS), are used to model the behavior of an experimentally scaled three-story...

in modern agriculture, image processing technique is used for mechanization and intelligent machines instead of humans. one of them is identifying varieties of plants and fruits. identifying plant varieties is important in plant eugenic programs. visual examination of plant leaves and fruits are the common processes for this aim. identification and classification of plants using machine vision ...

Despite the importance of dams for water distribution various uses, adequate forecasting on a day-to-day scale is still in great need intensive study worldwide. Machine learning models have had wide application resource studies and shown satisfactory results, including time series levels dam flows. In this study, neural network (NN) adaptive neuro-fuzzy inference systems (ANFIS) were generated ...

The purpose of this paper is to explore the dynamics of neural networks in forecasting crop (wheat) yield using remote sensing and other data. We use the Adaptive Neuro-Fuzzy Inference System (ANFIS). The input to ANFIS are several parameters derived from the crop growth simulation model (CGMS) including soil moisture content, above ground biomass, and storage organs biomass. In addition we use...

In this paper river stage discharge models using Adaptive NeuroFuzzy Inference System (ANFIS) and Linear Multiple Regression (MLR) methods have been developed. This paper also investigates the best model to forecast river discharge. From the literature it is clear that ANN models and Fuzzy logic models are quite applicable on river stage discharge modelling. Hence this present study carried out...

In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated ...

In this paper, the thermal field of underground power cable is solved using two intelligent techniques which are newly introduced for thermal assessment of power cables. A backpropagation neural network (BPNN) and an adaptive neuro-fuzzy inference system (ANFIS) models were developed to predict the cable temperature under geometrical parameter variations. The effect of cable spacing and cable b...