the oxidative coupling of methane (ocm) performance over na-w-mn/sio2 at elevated pressures has been simulated by adaptive neuro fuzzy inference system (anfis) using reaction data gathered in an isothermal fixed bed microreactor. in the designed neuro fuzzy models, three important parameters such as methane to oxygen ratio, gas hourly space velocity (ghsv), and reaction temperature were conside...

this study investigates the prediction model of compressive strength of self–compacting concrete (scc) by utilizing soft computing techniques. the techniques consist of adaptive neuro–based fuzzy inference system (anfis), artificial neural network (ann) and the hybrid of particle swarm optimization with passive congregation (psopc) and anfis called psopc–anfis. their performances are comparativ...

short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . these results made the hybrid tools and approaches a more common method for ...

Short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. Although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . These results made the hybrid tools and approaches a more common method for ...

using current employee performance data to predict the future behavior of the applicants is an interesting area which can broaden new horizons of knowledge lay in the organization. because of inherent ambiguity and uncertainty, cognitive limitations of the human mind make unknown behaviors of very complex systems difficult to predict. as a consequence, it is necessary to model the imprecise mod...

It is known that neuro-fuzzy system is easily stuck in local minimum. To improve these drawbacks, a two-stage algorithm combining the advantages of neuro-fuzzy and genetic algorithms (GA) is integrated in system identification. Genetic algorithms are general purposed optimization algorithms with adaptive reproduction, crossover, and mutation operators that provide a method to search optimal par...

A modular analogue neuro-chip set with on-chip learning capability is developed for active noise canceling. The analogue neuro-chip set incorporates the error backpropagation learning rule for practical applications, and allows pin-to-pin interconnections for multi-chip boards. The developed neuro-board demonstrated active noise canceling without any digital signal processor. Multi-path fading ...

A rule based signature verification system has been devised based on Adaptive Network Based Fuzzy Inference System (ANFIS). The histogram of the angle differences along the signature trajectory is used as a descriptor of the signatures. We partition the histogram to obtain a number of rules, which is limited to 4 at a time. The performance of the proposed system is found to be satisfactory on t...

In this paper, both the architecture and learning procedure underlying the parallel layer perceptron is presented. This topology, di1erent to the previous ones, uses parallel layers of perceptrons to map nonlinear input–output relationships. Comparisons between the parallel layer perceptron, multi-layer perceptron and ANFIS are included and show the e1ectiveness of the proposed topology. c © 20...

Telemetry systems is an innovative design of electronics and computer system which can be used to take measurements from a remote site by using any type of link like Radio link, optical fiber, co-axial cables etc. Telemetry systems can take any of the measurement like pressure, temperature, density, humidity etc. from a target location and sends the taken measurements via wired or wireless link...