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Nonlinear Dynamics

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Developing a support vector machine based QSPR model for prediction of half-life of some herbicides.

Ecotoxicology and environmental safety
The half-life (t1/2) of 58 herbicides were modeled by quantitative structure-property relationship (QSPR) based molecular structure descriptors. After calculation and the screening of a large number of molecular descriptors, the most relevant those o...

Vascular Dynamics Aid a Coupled Neurovascular Network Learn Sparse Independent Features: A Computational Model.

Frontiers in neural circuits
Cerebral vascular dynamics are generally thought to be controlled by neural activity in a unidirectional fashion. However, both computational modeling and experimental evidence point to the feedback effects of vascular dynamics on neural activity. Va...

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.

Computational intelligence and neuroscience
Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, l...

Chaotic Teaching-Learning-Based Optimization with Lévy Flight for Global Numerical Optimization.

Computational intelligence and neuroscience
Recently, teaching-learning-based optimization (TLBO), as one of the emerging nature-inspired heuristic algorithms, has attracted increasing attention. In order to enhance its convergence rate and prevent it from getting stuck in local optima, a nove...

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

Computational intelligence and neuroscience
In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the sa...

Neural Network-Based DOBC for a Class of Nonlinear Systems With Unmatched Disturbances.

IEEE transactions on neural networks and learning systems
In this brief, the problem of composite anti-disturbance tracking control for a class of strict-feedback systems with unmatched unknown nonlinear functions and external disturbances is investigated. A disturbance-observer-based control (DOBC) in comb...

Identification and Control for Singularly Perturbed Systems Using Multitime-Scale Neural Networks.

IEEE transactions on neural networks and learning systems
Many well-established singular perturbation theories for singularly perturbed systems require the full knowledge of system model parameters. In order to obtain an accurate and faithful model, a new identification scheme for singularly perturbed nonli...

Exponential stabilization and synchronization for fuzzy model of memristive neural networks by periodically intermittent control.

Neural networks : the official journal of the International Neural Network Society
The problem of exponential stabilization and synchronization for fuzzy model of memristive neural networks (MNNs) is investigated by using periodically intermittent control in this paper. Based on the knowledge of memristor and recurrent neural netwo...

FPGA-Based Stochastic Echo State Networks for Time-Series Forecasting.

Computational intelligence and neuroscience
Hardware implementation of artificial neural networks (ANNs) allows exploiting the inherent parallelism of these systems. Nevertheless, they require a large amount of resources in terms of area and power dissipation. Recently, Reservoir Computing (RC...

Using Genetic Programming with Prior Formula Knowledge to Solve Symbolic Regression Problem.

Computational intelligence and neuroscience
A researcher can infer mathematical expressions of functions quickly by using his professional knowledge (called Prior Knowledge). But the results he finds may be biased and restricted to his research field due to limitation of his knowledge. In cont...