در میان شبکۀ معابر شهری، راه‌های اضطراری امدادرسانی حین زلزله، به‌ویژه مرحلۀ پاسخ به بحران، نقش مهمی ایفا می‌کنند. حفظ عملکرد این شبکه از معابر، ساعات اولیۀ پس اهمیت بسزایی دارد. محافظت و مقاوم‌سازی اجزای آسیب‌پذیر شبکه، به‌خصوص پل‌ها، پیش وقوع تأثیر شایان توجهی کاهش خسارات آسیب‌ها اغلب اوقات تمامی آسیب‌پذیر، به‌دلیل محدودیت بودجه، عملاً ناممکن است. ایجاب می‌کند که با شناسایی دقیق گزینه‌های ابتد...

High-dimensional large sample data sets, between feature variables and between samples, may cause some correlative or repetitive factors, occupy lots of storage space, and consume much computing time. Using the Elman neural network to deal with them, too many inputs will influence the operating efficiency and recognition accuracy; too many simultaneous training samples, as well as being not abl...

-. Port throughput forecast plays a great role in the development of port logistics economy. This paper works over that significant subject based on a new kind of nonlinear combination method, which is composed of linear exponential smoothing model, simple moving average method and Elman network. The forecasted values through the first two methods are taken as the inputs of Elman network, which...

This paper presents an intrusion detection system of hybrid neural network model based on RBF and Elman. It is used for anomaly detection and misuse detection. This model has the memory function .It can detect discrete and related aggressive behavior effectively. RBF network is a real-time pattern classifier, and Elman network achieves the memory ability for former event. Based on the hybrid mo...

In this paper, the gain in LD-CELP speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (PSO) algorithms to optimize the structure and parameters of neural networks. Elman, multi-layer perceptron (MLP) and fuzzy ARTMAP are the candidate neural models. The optimized number of nodes in the first and second hidden layers of El...

in this paper, the gain in ld-celp speech coding algorithm is predicted using three neural models, that are equipped by genetic and particle swarm optimization (pso) algorithms to optimize the structure and parameters of neural networks. elman, multi-layer perceptron (mlp) and fuzzy artmap are the candidate neural models. the optimized number of nodes in the first and second hidden layers of el...

A fuzzy Elman neural network (FENN) is proposed to identify and simulate nonlinear dynamic systems. Each of all the fuzzy rules used in FENN has a linear state-space equation as its consequence and the network, by use of firing strengths of input variables, combines these Takagi-Sugeno type rules to represent the modeled nonlinear system. The context nodes in FENN are used to perform temporal r...

We explore the idea of adding the ability to learn time dependent tasks into the Intelligent Adaptive Curiosity (IAC) learning scheme as presented by Oudeyer, et al. [2004, 2006]. We use a three layer architecture (IGE) consisting of a bottom-level IAC brain, an Elman network, and a toplevel IAC brain. For both IAC brains we use the equilibrium Growing Neural Gas (GNG) algorithm to cluster the ...