Recurrent neural networks and hidden Markov models have been the popular tools for sequence recognition problems such as automatic speech recognition. This work investigates the combination of recurrent neural networks and hidden Markov models into the hybrid architecture. This combination is feasible due to the similarity of the architectural dynamics of the two systems. Initial experiments we...

EVOLUTION OF HYBRID INCOMPATIBILITIES IN GENE REGULATORY NETWORKS SEPTEMBER 2013 ALEXANDER Y. TULCHINSKY, B.S., VIRGINIA COMMONWEALTH UNIVERSITY, RICHMOND M.S., VIRGINIA COMMONWEALTH UNIVERSITY, RICHMOND Ph.D., UNIVERSITY OF MASSACHUSETTS, AMHERST Directed by: Adam H. Porter Under the Dobzhansky-Muller model, postzygotic isolation results from incompatibility between interacting genes. Evidence...

this paper investigates the forecasting gold coin futures contract price in iran mercantile exchange. this research has presented a hybrid model based on genetic fuzzy systems (gfs) and artificial neural network (ann) to forecast the gold futures contract, at first, we use stepwise regression analysis (sra) to determine factors which have most influence on stock prices. at the next stage we div...

the purpose of this research is to detect manipulation of stock prices in tehran stock exchange that it has been done through hybrid genetic algorithm-artificial neural network (ann-ga) model and the simplified quadratic discriminant function (sqdf) model. in this study, the variables of price, trading volume and free float stock to match the results of the model and the actual data of price ma...

Network security is one of the major concerns of studies have been conducted on the intrusion detection system. Cluster-based Wireless A novel hybrid intrusion detection method method for wireless sensor networks. Accepted papers & International Conference on Advanced Wireless, Paper title:A Low-Complex Coverage Eligibility Algorithm For Wireless Sensor Networks. Paper title: A Novel Cluster He...

In this paper, we introduce a hybrid approach based on neural network and optimization teqnique to solve ordinary differential equation. In proposed model we use heyperbolic secont transformation function in hiden layer of neural network part and bfgs teqnique in optimization part. In comparison with existing similar neural networks proposed model provides solutions with high accuracy. Numerica...

In this paper, a new hybrid routing protocol is presented for low power Wireless Sensor Networks (WSNs). The new system uses an integrated piezoelectric energy harvester to increase the network lifetime. Power dissipation is one of the most important factors affecting lifetime of a WSN. An innovative cluster head selection technique using Cuckoo optimization algorithm has been used in the desig...

the overwhelming trend in the network market for convergence of data communications, broadcast media and telecommunication demands that wireless networks handle mixed services. However, since the existing and forthcoming wireless networks still feature different data rates, network latencies, interaction capabilities, mobility support and cost per bit, each of those networks is only an optimal ...

in this paper, we present an application of evolved neural networks using a real coded genetic algorithm for simulations of monthly groundwater levels in a coastal aquifer located in the shabestar plain, iran. after initializing the model with groundwater elevations observed at a given time, the developed hybrid genetic algorithm-back propagation (ga-bp) should be able to reproduce groundwater ...