نتایج جستجو برای: then fuzzy rules achieved during the training process in multi adaptive neuro
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بررسی تطبیقی بازده حاصل از کاربرد تحلیل های تکنیکال و روش خرید و نگهداری در بورس اوراق بهادار تهران چکیده در این پژوهش بازدهی حاصل از روش های تجزیه و تحلیل تکنیکی و روش خرید و نگهداری در فرض قابل پیش بینی بودن قیمت ها و عدم وجود شکل ضعیف فرضیه بازار کارا که توسط فاما در سال 791 مطرح گردیده است ، فعالیت میکند . در این مطالعه چهار روش از پر کاربردترین و معتبر ترین روش های تحلیل تکنیکی مورد بر...
Proper models for prediction of time series data can be an advantage in making important decisions. In this study, we tried with the comparison between one of the most useful classic models of economic evaluation, auto-regressive integrated moving average model and one of the most useful artificial intelligence models, adaptive neuro-fuzzy inference system (ANFIS), investigate modeling procedur...
optimization of machining parameters is very important and the main goal in every machining process. surface finishing prediction is a pre-requirement to establish a center for automatic machining operations. in this research, a neuro-fuzzy approach is used in order to model and predict the surface roughness in dry turning. this approach has both the learning capability of neural network and li...
image classification is an issue which utilizes image processing, pattern recognition and classification methods. automatic medical image classification is a progressive area in image classification and it expected to be more developed in the future. due to this fact that automatic diagnosis which use intelligent methods such as medical image classification can assist pathologists by providing ...
An adaptive neuro fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part is presented in this paper. The capability of the proposed method (we named ANFIS2) for function approximation and dynamical system identification is remarkable. The structure o...
In this paper, an adaptive neuro-fuzzy system, called HyFIS, is proposed to build and optimise fuzzy models. The proposed model introduces the learning power of neural networks into the fuzzy logic systems and provides linguistic meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions can be optimally tuned from training eramples by a ...
This paper presents a novel adaptive neuro-fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part. The capability of the proposed ANFIS2 for function approximation and dynamical system identification is remarkable. The structure of ANFIS2 is very sim...
the following null hypothesis was proposed: h : there is no significant difference between the use of semantically or communicatively translates scientific texts. to test the null hypothesis, a number of procedures were taken first, two passages were selected form soyrcebooks of food and nutrition industry and gardening deciplines. each, in turn, was following by a number of comprehension quest...
126 abstract: in this research we studied the effects of cyclic hydration and dehydration of cysts of artemia urmiana and artemia parthenogenetica on the hatching percentage, survival and growth. the experiment was carried out in 3 treatments (1-3 hydration/dehydration cycles) with 3 replicates for each treatment. later effects of cold preservation at -20°c during three time periods were ...
Numerous learning tasks involve incomplete or connicting attributes. Most algorithms that automatically nd a set of fuzzy rules are not well suited to tolerate missing values in the input vector, and the usual technique to substitute missing values by their mean or another constant value can be quite harmful. In this paper a technique is proposed to tolerate missing values during the classiicat...
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