this paper presents a new observer-based control scheme for a class of nonlinear systems. in the proposed method, nonlinear observer and twisting algorithm controller are employed to realize a sensor-less control strategy for complex systems which makes use of non measurable process information instead of installing as many sensors as possible. due to lack of availability of the complex system ...

in this study, we focused on the gait of parkinson’s disease (pd) and presented a gray box model for it. we tried to present a model for basal ganglia structure in order to generate stride time interval signal in model output for healthy and pd states. because of feedback role of dopamine neurotransmitter in basal ganglia, this part is modelled by “elman network”, which is a neural network stru...

Standard particle swarm optimization (SPSO) algorithm was modified by escape strategy of the particle velocity, and an escape PSO (EPSO) was proposed to overcome the shortcomings of being trapped in local optima because of premature convergence. To enhance the performance of radial basis function (RBF) neural network, the EPSO is combined with RBF neural network to form a EPSON hybrid algorithm...

Prediction of traffic is very crucial for its management. Because of human involvement in the generation of this phenomenon, traffic signal is normally accompanied by noise and high levels of non-stationarity. Therefore, traffic signal prediction as one of the important subjects of study has attracted researchers’ interests. In this study, a combinatorial approach is proposed for traffic signal...

ystem identification is mainly the process of improving a mathematical modeling of a physical system using experimental data. In this paper, a new hybrid wavelet neural network is proposed for the system identification purposes. The Gravitational Search Algorithm (GSA) is a new evolutionary algorithm which recently introduced and has a good performance in different optimization problems. The GS...

this paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. this architecture of articial neural networks, can get a real input vector and calculates its corresponding fu...

today, with the advanced statistical techniques and neural networks, predictive models of distribution have been rapidly developed in ecology. purpose of this research is to predict and map the distribution of tetranychus urticae koch (acari: tetranychidae) using mlp neural networks combined with genetic algorithm in surface of farm. population data of pest was obtained in 2016 by sampling in 1...

Air material demand forecast is an important content of air material management, How to scientifically determine the general aircraft material demand has always been a key research subject of general aviation enterprise. Consider the general aircraft material demand forecast problem, forecast method is proposed by using Modified Particle Swarm Optimization (MPSO) algorithm to optimize the BP ne...