This paper introduces a new structure in neural networks called TD-CMAC, an extension to the conventional Cerebellar Model Arithmetic Computer (CMAC), having reasonable ability in TIME series prediction. TD-CMAC, the conventional CMAC and a classical neural network model called Multi-Layer Perceptron (MLP) are simulated and evaluated for 1-hour-ahead prediction and 24-hour-ahead prediction of carbon monoxide as one of primary air pollutants. Carbon monoxide data used in this evaluation were recorded and averaged at Villa station in Tehran, Iran from October 3thrd. 2001 to March 14th. 2002 at one-hour intervals. The results show that the errors made by TD-CMAC is fewer than those made by other models.

In this paper, the problem of finite-TIME stability and finite-TIME stabilization for a specific class of dynamical systems with nonlinear functions in the presence TIME-varying DELAY and norm-bounded uncertainty terms is investigated. Nonlinear functions are considered to satisfy the Lipchitz conditions. At first, sufficient conditions to guarantee the finite-TIME stability for TIME-DELAY nonlinear system with uncertainties and based on the Lyapunov approach is presented. In the following, sufficient conditions to ensure finite TIME stabilization the considered system with state feedback are presented. In the proofs of proposed theorems are used from the appropriate Lyapunov-Krasovskii function and newton-Libniz-formula that can reduce the conservative. Also, all of the obtained conditions in this paper are DELAY-dependent and presented as linear matrix inequalities. Finally, the numerical examples and simulations exhibit the effectiveness of the proposed methods.

This paper introduces a new structure in neural networks called as TD-CMAC (TIME DELAY Cerebellar Model Articulation Controller), an extension to the conventional CMAC.,TD-CMAC has reasonable ability in TIME series prediction and requires fewer memory sizes. The suggested new model, the conventional CMAC and the classical multi-layer perceptron neural network (MLP) are demonstrated and validated for one-day-ahead prediction of daily minimum/maximum temperature. The comparison between different models shows that the TD-CMAC is likely to be suitable for our purpose.      

In this paper, Artificial Neural Networks are used to solve DELAY Differential Equations. We have suggested an appropriate approximation function based on ANN and then by solving an optimization problem of error function, the neural network is trained. The advantage of this technique is that the proposed approximation functions, with a slight modification, can be used for most types of DELAY differential equations, including DDE with constant DELAY, TIME-dependent DELAY and pantograph DELAY. To demonstrate the effectiveness of the method, various examples have been tested and the validity and efficiency of the method have been shown.

This paper is concerned with the problem of DELAY-dependent passive analysis and control for interval stochastic TIME-DELAY systems. The system matrices are assumed to be uncertain within given intervals, the TIME DELAY is a TIME-varying continuous function belonging to a given range, and the stochastic perturbation is in the form of a Brownian motion. By using ItO's differential formula and the Lyapunov stability theory, DELAY-dependent stochastic passive control criteria are proposed without ignoring any useful terms by considering the information of the lower bound and upper bound for the TIME DELAY. Based on the criteria obtained, a DELAY-dependent passive controller that ensures the stochastic passivity of the closed-loop system is presented. Then, the controller gain is characterized in terms of LMIs, which can be easily checked by resorting to available software packages. Numerical examples are given to demonstrate the effectiveness of the method.

In this paper, a new approach for constructing quadratic Lyapunov-Krasovskii functionals for a class of nonlinear TIME-DELAY systems is developed. The functionals are then used to derive DELAY dependent stability conditions. These conditions are sufficient and local. Numerical example shows that the results obtained using the proposed method is less conservative than those obtained by the existing methods.

For reasons of TIME and effort has exceeded the standard level. Based on field studies conducted in Port Shahidrajaee total TIME needed, including stops and DELAYs, and ... from point of entry to the port of loading and unloading operations to the exit point will be influenced by several factors that are not controlled operators and drivers. This concept is called latency or DELAY can be calculated. As can be seen in the areas of operation of the port, the traffic volume and value of this DELAY will not accept interference in effect, usually road intersections and railroad crossings and train and drill exercises parking, traffic flow is established. This paper attempts to identify the economic analysis of travel TIME information to estimate the benefits of saving TIME.