this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...

As one of the important artificial intelligence fields, brain-like computing attempts to give machines a higher level by studying and simulating cognitive principles human brain. Compared with traditional neural network, spiking network (SNN) has better biogenesis stronger power. In this paper, an SNN learning model based on evolutionary membrane algorithm is proposed solve problem supervised c...

this paper considers the problem of scheduling hybrid flowshops with machine availability constraints (mac) to minimize makespan. the paper deals with a specific case of mac caused by preventive maintenance (pm) operations. contrary to previous papers considering fixed or/and conservative policies, we explore a case in which pm activities might be postponed or expedited while necessary. regardi...

nowadays, economic load dispatch between generation units with least cost involved is one of the most important issues in utilizing power systems. in this paper, a new method i.e. water cycle algorithm (wca) which is similar to other intelligent algorithm and is based on swarm, is employed in order to solve the economic load dispatch problem between power plants. wca is used to solve complicate...

one of the most common signals used for achieving high range resolution in radar is stepped-frequency signals. when a target is stationary in these radars, dft (discrete fourier transform) based processing is used to attain high range resolution profile (hrrp). however, in the case of moving target, due to spreading of the echo signal spectrum, dft based processing is not optimal and decreases ...