in this study, a multi-objective genetic algorithm (moga) is utilized to extract interpretable and compact fuzzy rule bases for modeling nonlinear multi-input multi-output (mimo) systems. in the process of non- linear system identi cation, structure selection, parameter estimation, model performance and model validation are important objectives. furthermore, se- curing low-level and high-level ...

latticed columns are frequently used in industrial steel structures. in some countries these built-up columns might be even used in other types of steel structures such as residential and commercial buildings. besides, latticed columns are parts of skeletons of many historic buildings all around the world. to analyze a steel structure with latticed columns a more accurate numerical model for su...

nowadays, atomic force microscope is considered as a useful tool in the determination of intermolecular forces and surface topography with the resolution of nanometers. in this kind of microscope, micro cantilever is considered as the heart of the microscope and is used as a measuring tool.  this paper is aimed towards investigating the behavior of a piezoelectric micro cantilever with a triang...

Takagi-Sugeno (TS) fuzzy modeling and control techniques are applied to the classical nonlinear Ball and Beam problem. The nonlinear model is segmented to different local linear models. Local controllers are hence designed using LMI theory for achieving a robust control behavior for ball position. TS fuzzy modeling is applied to generate suitable fuzzy models, and the associated controllers. Us...

Structural models are tools conceptually useful in time series modeling, because they allow the individual interpretation behavior of each structural component in the series; however, the difficult in the representation of nonlinear relationships of these models, have despised their use in real series. The Artificial Neural Networks (RNA) models are a promising alternative by the nonlinear time...

In practical engineering, it is difficult to establish complex nonlinear dynamic equations based on theories of mechanics. Data-driven models are built using neural networks in this paper meet the needs high dimension, multi-scale and precision. We construct a two-coefficient loss function for whole data-driven modeling substructure according linear multi-step method. The forward Euler method c...

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 research, using the modified compression field theory (mcft), a new truss based model is proposed to predict the behavior of reinforced concrete coupling beams with diagonal reinforcement. the model is able to consider the effects of shear and axial forces and bending moment, simultaneously. the proposed model includes a nonlinear shear spring, an axial spring, two inclined truss member...