نتایج جستجو برای: linear network

تعداد نتایج: 1117709  

Journal: :مهندسی صنایع 0
محمدجعفر تارخ دانشیار دانشکده صنایع - دانشگاه خواجه نصیرالدین توسی مهسا اسمعیلی گوکه دانشجوی کارشناسی ارشد it- دانشکده صنایع دانشگاه خواجه نصیرالدین توسی شهره ترابی دانشجوی کارشناسی ارشد مهندسی صنایع – دانشگاه پیام نور تهران

the environmental rules of reverse logistic networks have caused important economic growth in the past decades. to integrate forward logistic networks with reverse logistics networks a helpful method is to design both networks simultaneously. considering more retrieval choices in modeling reverse logistic systems can be very critical. this article contains a mixed integer linear programming mod...

Journal: :IEEE Transactions on Information Theory 2019

M. A. Aghaei, M. Moradzadeh fard, N. Mousazadeh Abbasi,

The goal of this research is to predict total stock market index of Tehran Stock Exchange, using the compound method of ARIMA and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. First, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

Journal: :مهندسی صنایع 0
طه حسین حجازی دکتری مهندسی صنایع دانشگاه آزاد اسلامی واحد قزوین، باشگاه پژوهشگران جوان و نخبگان مرتضی عباسی استادیار مجتمع مدیریت و فناوری های نرم دانشگاه صنعتی مالک اشتر

responsibility in demand networks is one of the most important measures of performance. the concept of agility and flexibility in service and production. variety and changes in demand need more flexible network design that can cope with potential shortage and delay. this paper presents new mathematical model to optimize the design of demand network when there are highly variable demands. it als...

Gary R. Weckman Harry S. Whiting Helmut W. Paschold John D. Dowler William A. Young

Neural networks were used to estimate the cost of jet engine components, specifically shafts and cases. The neural network process was compared with results produced by the current conventional cost estimation software and linear regression methods. Due to the complex nature of the parts and the limited amount of information available, data expansion techniques such as doubling-data and data-cr...

Journal: :international journal of supply and operations management 2014
mitra darvish mehdi seifabrghy mohammad ali saniei monfared fatemeh akbari

this paper explains a model for analyzing and measuring the propagation of order amplifications (i.e. bullwhip effect) for a single-product supply network topology considering exogenous uncertainty and linear and time-invariant inventory management policies for network entities. the stream of orders placed by each entity of the network is characterized assuming customer demand is ergodic. in fa...

Journal: :iranian journal of chemistry and chemical engineering (ijcce) 2006
mahmoud mousavi akram avami

an artificial neural network has been used to determine the volume flux and rejections of ca2+ , na+ and cl¯, as a function of transmembrane pressure and concentrations of ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. the feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidden la...

Journal: :iranian journal of applied animal science 2014
s. ghazanfari

this study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ann) in broiler chicken. artificial neural networks (anns) are powerful tools for modeling systems in a wide range of applications. the ann model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...

Alireza Zomorrodi Bahram Nasernejad, Jahanshah Kabudian

The biologists now face with the masses of high dimensional datasets generated from various high-throughput technologies, which are outputs of complex inter-connected biological networks at different levels driven by a number of hidden regulatory signals. So far, many computational and statistical methods such as PCA and ICA have been employed for computing low-dimensional or hidden represe...

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