نتایج جستجو برای: neural network
تعداد نتایج: 832182 فیلتر نتایج به سال:
predicting the maintenance and management costs and replacement age of tractors in agricultural mechanized units, is important from several points. so, doing a timely agricultural operations, more accurate measure of the amount of income including the cost of these items , determining the useful life of old tractors , replacement age, cost of the process changes and the possibility of examinin...
drought forecasting in khash city by using neural network model hossein negaresh associate professor of geography and environmental planningfaculty, university of sistan & baluchestan mohsen armesh holding master degree in climatology in environmental planning extended abstract 1- introduction drought is condition of lack of rainfall and increase in temperature occurring in any climatic condit...
malting is a complex biotechnological process that includes steeping; germination and drying of cereal grains under controlled conditions of temperature and humidity. in this research malting process parameters were predict by modular neural network with different activation function included, logsig-logsig, tanh-tanh, logsigtanh, logsig-identity and tanh-identity. steeping time (x1) and germin...
there is a complicated relation between cold flat rolling parameters such as effective input parameters of cold rolling, output cold rolling force and exit thickness of strips. in many mathematical models, the effect of some cold rolling parameters has been ignored and the outputs have not a desirable accuracy. in the other hand, there is a special relation among input thickness of strips, the ...
In this paper, we interpret a fuzzy differential equation by using the strongly generalized differentiability concept. Utilizing the Generalized characterization Theorem. Then a novel hybrid method based on learning algorithm of fuzzy neural network for the solution of differential equation with fuzzy initial value is presented. Here neural network is considered as a part of large eld called ne...
reservoir permeability is a critical parameter for the evaluation of hydrocarbon reservoirs. there are a lot of well log data related with this parameter. in this study, permeability is predicted using them and a supervised committee machine neural network (scmnn) which is combined of 30 estimators. all of data were divided in two low and high permeability populations using statistical study. e...
background and objectives: rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. materials and met...
In this paper, two kinds of chaotic neural networks are proposed to evaluate the efficiency of chaotic dynamics in robust pattern recognition. The First model is designed based on natural selection theory. In this model, attractor recurrent neural network, intelligently, guides the evaluation of chaotic nodes in order to obtain the best solution. In the second model, a different structure of ch...
abstract forecasting electrical energy demand and consumption is one of the important decision-making tools in distributing companies for making contracts scheduling and purchasing electrical energy. this paper studies load consumption modeling in hamedan city province distribution network by applying esn neural network. weather forecasting data such as minimum day temperature, average day temp...
tthe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. this paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. as a novelty, the proposed controller employs a simple gaussian radial-basis-function network as an uncertainty estimator. the proposed netw...
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