نتایج جستجو برای: neural network control

تعداد نتایج: 2051162  

اورک, ناصر, جوجی زاده, خدیجه, فتوحی, صمد, نصیری, مریم,

Flood is a kind of natural disaster which causes financial damages and fatality for people. Every year, especially in areas like Maroon river basin which have changes in precipitation and temperatures, along with frequent and severe floods. This study aimed to identify the climatic parameters on flood area can be efficiently artificial neural network, better methods applied in anticipation of t...

Journal: :journal of optimization in industrial engineering 0
marjan niyati department of computer engineering and information technology qazvin azad university of technology ,iran amir masud eftekhari moghadam department of computer engineering and information technology qazvin azad university of technology ,iran

estimating the final price of products is of great importance. for manufacturing companies proposing a final price is only possible after the design process over. these companies propose an approximate initial price of the required products to the customers for which some of time and money is required. here using the existing data of already designed transformers and utilizing the bayesian anal...

 Background: Modeling is one of the most important ways for explanation of relationship between dependent and independent response. Since data, related to number of blood donations are discrete, to explain them it is better to use discrete variable distribution like Poison or Negative binomial. This research tries to analyze numerical methods by using neural network approach and compare ...

S.Samavi, V. Tahani and P. Khadivi,

Routing is one of the basic parts of a message passing multiprocessor system. The routing procedure has a great impact on the efficiency of a system. Neural algorithms that are currently in use for computer networks require a large number of neurons. If a specific topology of a multiprocessor network is considered, the number of neurons can be reduced. In this paper a new recurrent neural ne...

In this paper, stabilization of the structural system against earthquake is presented. Because the conventional PD controller is popular and simple in design, our controller is based on PD controller. The main problem of such a controller is its inability to produce desired response and instability against variations in the properties of the structural system. To obviate this issue, the neu...

A. Ghomashi F. Hosseinzadeh Lotfi G. R. Jahanshahloo

In this paper we present a recurrent neural network model to recognize efficient Decision Making Units(DMUs) in Data Envelopment Analysis(DEA). The proposed neural network model is derived from an unconstrained minimization problem. In theoretical aspect, it is shown that the proposed neural network is stable in the sense of lyapunov and globally convergent. The proposed model has a single-laye...

2005
Tianyou Chai Heng Yue

A new decoupling control structure is presented for complex industrial processes, which consists of a feedback controller, a decoupling compensator and a feedforward compensator for unmodeled dynamics. Using this structure, an intelligent decoupling control system is established which realizes an adaptive decoupling control strategy for industrial processes with integrated complexities by using...

Journal: :بین المللی مهندسی صنایع و مدیریت تولید 0
hamid amraei ellips masehian

statistical process control (spc) charts play a major role in quality control systems, and their correct interpretation leads to discovering probable irregularities and errors of the production system. in this regard, various artificial neural networks have been developed to identify mainly singular patterns of spc charts, while having drawbacks in handling multiple concurrent patterns. in this...

Journal: :مدلسازی در مهندسی 0
نویدی نویدی

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

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