نتایج جستجو برای: esn neural network

تعداد نتایج: 832316  

2003
Li Zhang James J. Cimino

Objective: The Unified Medical Language System’s (UMLS’s) Semantic Network’s (SN’s) two-tree structure is restrictive because it does not allow a semantic type to be a specialization of several other semantic types. In this paper, the SN is expanded into a multiple subsumption structure with a directed acyclic graph (DAG) IS-A hierarchy, allowing a semantic type to have multiple parents. New vi...

‎By p-power (or partial p-power) transformation‎, ‎the Lagrangian function in nonconvex optimization problem becomes locally convex‎. ‎In this paper‎, ‎we present a neural network based on an NCP function for solving the nonconvex optimization problem‎. An important feature of this neural network is the one-to-one correspondence between its equilibria and KKT points of the nonconvex optimizatio...

Introduction: cardiovascular diseases are becoming the main cause of mortality and morbidity in most countries. This research goal was to predict the types of heart diseases for more accurate diagnosis by data mining and neural network technics. Method: This research was an applied-survey study and after data preprocessing, three approaches of neural network, decision making tree and Bayes simp...

2004
Benjamin Liebald

Echo State Networks (ESN) have been used successfully in a broad range of applications, from dynamic pattern recognition to channel equalization in digital communication systems [5, 7, 9]. Their simplicity and ease of use, paired with their underlying ”mathematical power” make them an ideal choice in many black-box modelling tasks. For many applications, however, it is mandatory to learn and ad...

2013
Elliott Forney Charles Anderson William Gavin Patricia Davies

We propose an EEG classification algorithm for the mental task BCI paradigm that uses Echo State Networks (ESN). In this approach, ESN are used to model the dynamics of EEG during each of several mental tasks. Classification is performed by applying several of these models and assigning the class label associated with the ESN that produces the lowest forecasting error. Experiments performed on ...

Journal: :پژوهش های حفاظت آب و خاک 0

infiltration rate is one of the most important soil physical parameters and is a basic input data in irrigation and drainage projects. although, a number of theoretical or experimental based equations are presented to describe this phenomenon but the evaluation of some new sciences such as artificial neural networks, for prediction of the phenomenon can be investigated. generally, the infiltrat...

Journal: :کشاورزی (منتشر نمی شود) 0
سید میثم مظلوم زاده مربی، دانشکده کشاورزی سراوان، دانشگاه سیستان و بلوچستان، سیستان و بلوچستان سید ناصر علوی استادیار، گروه مکانیک ماشین های کشاورزی، دانشکده کشاورزی، دانشگاه شهید باهنر کرمان، کرمان مجتبی نوری دانشجوی دکترای مهندسی منابع آب، دانشگاه آزاد اسلامی واحد علوم و تحقیقات

in this study the wavelet neural network (wnn) and artificial neural network (ann) were used to simulate barley breakage percentage in combine harvester. the models have been trained using the same data conditions. air temperature, thresher cylinder speed, distance between thresher cylinder and concave (back and forth) and the percentage of barely moisture were as the input variables. the resul...

Journal: :international journal of advanced biological and biomedical research 2013
amir hossein hashemian behrouz beiranvand mansour rezaei abdolrasoul bardideh eghbal zand-karimi

cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. in recent decades, artificial neural network model has been increasingly applied to predict survival data. this research was conducted to compare cox regression and artificial neural network models in prediction of kidney transplant survival. the prese...

In this study, artificial neural network was used to predict the surface tension of 20 hydrocarbon mixtures. Experimental data was divided into two parts (70% for training and 30% for testing). Optimal configuration of the network was obtained with minimization of prediction error on testing data. The accuracy of our proposed model was compared with four well-known empirical equations. The arti...

Journal: :journal of artificial intelligence in electrical engineering 2014
zolekh teadadi hassan changiziyan

in the near future the use of distributed generation systems will play a big role in the production ofelectrical energy. one of the most common types of dg technologies , fuel cells , which can be connectedto the national grid by power electronic converters or work alone studies the dynamic behavior andstability of the power grid is of crucial importance. these studies need to know the exact mo...

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