نتایج جستجو برای: fuzzy neural network
تعداد نتایج: 908608 فیلتر نتایج به سال:
realizing the difficulties involved in direct measurement of soil properties, in recent years, alternative methods have been employed. in the present research, soil texture, organic carbon, saturation percentage and lime as readily measurable parameters, wilting point, field capacity, cation exchange capacity as well as bulk density, as predicted variables were evaluated. the data set was then ...
Road accident prediction plays an important role in accessing and improving the road safety. Besides the conventional generalized linear regression, the prediction approaches based on fuzzy logic and neural networks have increasingly been proven to have a significant accident-predicting capability in recent years. However, fuzzy logic and neural network have their respective limitations. For ex...
Performance comparison of land change modeling techniques for land use projection of arid watersheds
The change of land use/land cover has been known as an imperative force in environmental alteration, especially in arid and semi-arid areas. This research was mainly aimed to assess the validity of two major types of land change modeling techniques via a three dimensional approach in Birjand urban watershed located in an arid climatic region of Iran. Thus, a Markovian approach based on two suit...
In this paper, we intend to offer a new method based on fuzzy neural networks for finding a real solution of fuzzy equations system. Our proposed fuzzified neural network is a fivelayer feed-back neural network that corresponding connection weights to output layer are fuzzy numbers. The proposed architecture of artificial neural network, can get a real input vector and calculates it’s correspon...
This paper deals with the design of single fuzzy neural network (SFNN) with sliding mode control (SMC) systems by using the approach of sliding mode control. The fuzzy sliding mode control (FSMC) in the system guarantee the state can reach the user-defined surface in finite time and then it slides into the origin along the surface. The key idea is to apply parameters of the membership function ...
A fuzzy neural network, Falcon-MART, is proposed in this paper. This is a modi®cation of the original Falcon-ART architecture. Both Falcon-ART and Falcon-MART are fuzzy neural networks that can be used as fuzzy controllers or applied to areas such as forgery detection, pattern recognition and data analysis. They constitute a group of hybrid systems that incorporate fuzzy logic into neural netwo...
Aimed at fuzzy clustering based on the generalized entropy, an image segmentation algorithm by joining space information of image is presented in this paper. For solving the optimization problem with generalized entropy’s fuzzy clustering, both Hopfield neural network and multi-synapse neural network are used in order to obtain cluster centers and fuzzy membership degrees. In addition, to impro...
Neural networks, which make no assumption about data distribution, have achieved improved image classification results compared to traditional methods. Unfortunately, a neural network is generally perceived as being a ‘black box’. It is extremely difficult to document how specific classification decisions are reached. Fuzzy systems, on the other hand, have the capability to represent classifica...
Fire alarm system is important in high-rise building. In this paper, a fire alarm system of high-rise building is designed using fuzzy system theory and neural network. The fuzzy system has superiority in inference and the neural network has superiority in learning. The design parameters of the fuzzy system can be adjusted automatically by combining the fuzzy system with the neural network. The...
This paper build a structure of fuzzy neural network, which is well sufficient to gain a fuzzy interpolation polynomial of the form [Formula: see text] where [Formula: see text] is crisp number (for [Formula: see text], which interpolates the fuzzy data [Formula: see text]. Thus, a gradient descent algorithm is constructed to train the neural network in such a way that the unknown coefficients ...
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