نتایج جستجو برای: we aim to model themusing adaptive neural
تعداد نتایج: 11508059 فیلتر نتایج به سال:
this paper addresses a nonlinear observer based control scheme to synchronize chaotic systems subject to uncertainties and external disturbances. it is assumed that the dynamic of slave system is not completely known. in order to compensate for the system perturbation resulting from parameter variations and mismodeling phenomena, an adaptive neural network observer is employed to handle this pr...
abstract foreign and iranian cultures are far distinct in the constraints imposed on writing and translating for children, since the iranian literary system is mainly concerned with cultural and religious instructions which lead to manipulation of translated texts. this study sought to identify the cultural and social constraints and norms which determined the strategies applied in the transl...
Aiming at the problem that tracking accuracy of unmanned vehicle path preview control is greatly affected by time, a BP neural network adaptive method proposed. Considering prediction effect limited to initial value setting, time adjuster based on SSA-BP was established; establishing relationship between front wheel steering angle and new direction driver model formed. The together constitute a...
The main aim of this short paper is to propose a new branch prediction approach called by us "neural branch prediction". We developed a first neural predictor model based on a simple neural learning algorithm, known as Learning Vector Quantization algorithm. Based on a trace driven simulation method we investigated the influences of the learning step and training processes. Also we compared the...
the purpose of this study is identifying effective factors which make customers shop online in iran and investigating the importance of discovered factors in online customers’ decision. in the identifying phase, to discover the factors affecting online shopping behavior of customers in iran, the derived reference model summarizing antecedents of online shopping proposed by change et al. was us...
linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints. in this paper, to solve this problem, we combine a discretization method and a neural network method. by a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem. then, we use...
the methods which are used to analyze microstrip antennas, are divited into three categories: empirical methods, semi-empirical methods and full-wave analysis. empirical and semi-empirical methods are generally based on some fundamental simplifying assumptions about quality of surface current distribution and substrate thickness. thses simplificatioms cause low accuracy in field evaluation. ful...
in common classical methods of cavity depth estimation through microgravity data, usually when a pre-geometrical model is considered for the cavity shape, the simple geometrical models of sphere, vertical cylinder and horizontal cylinder are commonly used. it is obviously an important fact that in real conditions the shapes of the cavities are not exactly sphere, horizontal cylinder or vertical...
Adaptive portfolio management has been studied in the literature of neural nets and machine learning. The recently developed Temporal Factor Analysis (TFA) model mainly targeted for further study of the Arbitrage Pricing Theory (APT) is found to have potential applications in portfolio management. In this paper, we aim to illustrate the superiority of APT-based portfolio management over return-...
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