—State estimation for uncertain systems affected by external noises is an important problem in control theory even for continuous and discrete systems. This paper deals with the state observation problem when the dynamic model of a plant contains uncertainties or is partially unknown and it is oriented to discrete time nonlinear systems because most of the existent results have been developed f...

The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm de...

This study deals with predicting nonlinear time history deflection of scallop domes subject to earthquake loading employing neural network technique. Scallop domes have alternate ridged and grooves that radiate from the centre. There are two main types of scallop domes, lattice and continuous, which the latticed type of scallop domes is considered in the present paper. Due to the large number o...

this study investigates the oil extraction from pistacia khinjuk by the application of enzyme.artificial neural network (ann) and adaptive neuro fuzzy inference system (anfis) were applied formodeling and prediction of oil extraction yield. 16 data points were collected and the ann was trained with onehidden layer using various numbers of neurons. a two-layered ann provides the best results, us...

Due to the hostile marine environment, there will inevitably be unpredictable factors during operation of unmanned underwater vehicles, including changes in ocean currents, hull dimensions, and velocity measurement uncertainties. An improved finite-time adaptive tracking control issue is considered for autonomous vehicles (AUVs) with uncertain dynamics, unknown external disturbances, unavailabl...

this paper addresses adaptive observer design problem for joint estimation of the states and unknown parameters for a class of nonlinear systems which satisfying one-sided lipschitz and quadratic inner bounded conditions. it’s shown that the stability of the proposed observer is related to finding solutions to a quadratic inequality consists of state and parameter errors. a coordinate transform...

Graph neural networks (GNNs) have demonstrated great success in representation learning for graph-structured data. The layer-wise graph convolution GNNs is shown to be powerful at capturing topology. During this process, are usually guided by pre-defined kernels such as Laplacian matrix, adjacency or their variants. However, the adoptions of may restrain generalities different graphs: mismatch ...