the proposed iafc neural networks have both stability and plasticity because theyuse a control structure similar to that of the art-1(adaptive resonance theory) neural network.the unsupervised iafc neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. this fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. the supervised iafc ...

in recent years, researches on reinforcement learning (rl) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. neural network reinforcement learning (nnrl) is among the most popular algorithms in the rl framework. the advantage of using neural networks enables the rl to search for optimal policies more efficiently in several real-life applicat...

this article is a comparative study of estimation power of artificial neural networks and autoregressive time series models in inflation forecasting. using 37 years iran’s inflation data, neural networks performs better on average for short horizons than autoregressive models. this study shows usefulness of early stopping technique in learning stage of neural networks for estimating time series...

ad hoc mobile networks have dynamic topology with no central management. because of the high mobility of nodes, the network topology may change constantly, so creating a routing with high reliability is one of the major challenges of these networks .in the proposed framework first, by finding directions to the destination and calculating the value of the rout the combination of this value with ...

social learning and knowledge generation are two key factors to achieve successful natural resources co-management. social learning can be beneficial by broadcasting and transmitting experiences and problem solving ideas in a group of people. social learning networks can transmit knowledge and experiences from one node to another in the network. social learning can produce a suitable learning a...

coverage improvement is one of the main problems in wireless sensor networks. given a finite number of sensors, improvement of the sensor deployment will provide sufficient sensor coverage and save cost of sensors for locating in grid points. for achieving good coverage, the sensors should be placed in adequate places. this paper uses the genetic and learning automata as intelligent methods for...

a new structure learning approach for bayesian networks (bns) based on asexual reproduction optimization (aro) is proposed in this letter. aro can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. in aro, a parent produces a bud through a reproduction operator; thereafter the parent and its bud compete to survi...

the hybrid fuzzy differential equations have a wide range of applications in science and engineering. we consider the problem of nding their numerical solutions by using a novel hybrid method based on fuzzy neural network. here neural network is considered as a part of large eld called neural computing or soft computing. the proposed algorithm is illustrated by numerical examples and the resu...