نتایج جستجو برای: self organized artificial neural networks
تعداد نتایج: 1362573 فیلتر نتایج به سال:
Artificial neural networks involve a network of simple processing elements (artificial neurons) which can exhibit complex global behavior. This behvavior is determined by the connections between the processing elements and element parameters. Artificial neural networks can be easily trained to perform a particular function by adjusting the values of the connections (weights) between elements. I...
This paper describes experiments involving the growth of human neural networks of stem cells on a MEA (microelectrode array) support. The microelectrode arrays (MEAs) are constituted by a glass support in which a set of tungsten electrodes are inserted. The artificial neural network (ANN) paradigm was used by stimulating the neurons in parallel with digital patterns distributed on eight channel...
سرعت موج برشی (vs) در لایه های خاک یکی از مولفه های اساسی برای انجام محاسبات ژئوتکنیکی وتحلیل های دینامیکی به خصوص تعیین مدول برشی دینامیکی لایه های خاک می باشد. مقادیر سرعت موج برشی خاک توسط اندازه گیری مستقیم در صحرا از روش هایی ژئوفیزیکی و یا در آزمایشگاه از روش های ژئوتکنیکی به دست می آید. تعیین سرعت موج برشی خاک به روش های مذکور اگر چه دقیق می باشد ولی عموماً پر هزینه بوده و در برخی از پروژ...
The paper focuses on the division of the sensor field into subsets of sensor events and proposes the linear transformation with the smallest achievable error for reproduction: the transform coding approach using the principal component analysis (PCA). For the implementation of the PCA, this paper introduces a new symmetrical, lateral inhibited neural network model, proposes an objective functio...
Rainfall-runoff models are used in the field of hydrology and runoff estimation for many years, but despite existing numerous models, the regular release of new models shows that there is still not a model that can provide sophisticated estimations with high accuracy and performance. In order to achieve the best results, modeling and identification of factors affecting the output of the model i...
artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. this paper is a scrutiny on the application of diverse learning methods in speed of convergence in neural networks. for this aim, first we introduce a perceptron method based on artificial neural networks which has been applied for solving a non-singula...
Time changes of return, inefficiency studies performed and presence of effective factors on share return rate are caused development modern and intelligent methods in estimation and evaluation of share return in stock companies. Aim of this research is prediction of return using financial variables with artificial neural network approach. Therefore, the statistical population of this study incl...
parallel architectures for artificial neural networks paradigms and implementations systems PDF neural smithing supervised learning in feedforward artificial neural networks PDF artificial neural networks in biomedicine perspectives in neural computing PDF quantum neural computation intelligent systems control and automation science and engineering PDF foundations of neural networks fuzzy syste...
This paper presents the results of modelling to predict the effluent biological oxygen demand (BOD5) concentration for primary clarifiers using a hybridisation of unsupervised and supervised artificial neural networks. The hybrid model is based on the unsupervised self-organising map (SOM) whose features were then used to train a multi-layered perceptron, feedforward back propagation artificial...
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