This study presents a robust and rigorous method based on intelligent models, namely radial basis function networks optimized by particle swarm optimization (PSO-RBF), multilayer perceptron neural networks (MLP-NNs), and adaptive neuro-fuzzy inference system optimized by particle swarm optimization methods (PSO-ANFIS), for predicting the equilibrium and kinetics of the adsorption of sulfur and ...

Wind energy has been well recognized as renewable resource in electricity generation. In this paper, a novel hybrid approach is proposed for wind speed forecasting in a Rostamabad in Iran, from 2002 to 2004. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system (PSO-ANFIS). The 10-minute average wind speed data from Ro...

Routers are vital during network congestion. All routers have input and output packet buffers. V<span lang="EN-US">Various congestion control strategies been suggested. Some controller-based proportional-integral derivative (PIDs) recently offered as active queue management (AQM) solutions to alleviate the deterioration of transmission protocol (TCP) system performance. However, time dela...

This research looked into the viability of using metaheuristic algorithms in conjunction with an adaptive neurofuzzy system to predict seismicity and earthquakes. Different have been combined artificial intelligence (AI) algorithm. Subjected is a promising factor. The new sensors many advantages over older, more impressive-looking ones, including (a) generally linear relationship between measur...

Forecasting the bank profile shape of stable hydraulic channels using empirical, experimental and numerical models is special consideration among fluid mechanic river science engineers. In present paper, application soft computing methods evaluated in predicting geometry channel cross sections. this way, a combination Particle Swarm Optimization (PSO) algorithm with an Adaptive Neuro-Fuzzy Infe...

An e cient methodology is proposed to optimize space trusses considering geometric nonlinearity. The optimization task is performed by a continuous Particle Swarm Optimization (PSO). Design variables are cross sectional areas of the trusses and their weights are also taken as the objective function. Design constraints are de ned to restrict nodal displacements and element stresses and prevent t...