نتایج جستجو برای: keywords artificial neural network
تعداد نتایج: 2868227 فیلتر نتایج به سال:
In this study, we used the ARIMA time series model, the fuzzy-neural inference network, multi-layer perceptron artificial neural network, and ARIMA-ANN, ARIMA-ANFIS hybrid models for the modeling and prediction of the daily electrical conductivity parameter of daily teleZang hydrometric station over the statistical period of 49 years. For this purpose, the daily data for the 1996-2004 period we...
Inverse kinematics analysis plays an important role in developing a robot manipulator. But it is not too easy to derive the inverse kinematic equation of a robot manipulator especially robot manipulator which has numerous degree of freedom. This paper describes an application of Artificial Neural Network for modeling the inverse kinematics equation of a robot manipulator. In this case, the robo...
Bio-absorbent palm fiber was applied for removal of cationic violet methyl dye from water solution. For this purpose, a solid phase extraction method combined with the artificial neural network (ANN) was used for preconcentration and determination of removal level of violet methyl dye. This method is influenced by factors such as pH, the contact time, the rotation speed, and the adsorbent dosag...
Artificial Neural Networks (ANNs), especially back-propagation (BP) neural network, can improve the performance of intrusion detection systems. However, for the current network intrusion detection methods, the detection precision, especially for lowfrequent attacks, detection stability and training time are still needed to be enhanced. In this paper, a new model which based on optimized BP neur...
background: clinically frank thyroid nodules are common and believed to be present in 4% to 10% of the adult population in the united states. in the current literature, fine needle aspiration biopsies are considered to be the milestone of a model which helps the physician decide whether a certain thyroid nodule needs a surgical approach or not. a considerable fact is that sensitivity and specif...
This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...
Please cite this article in press as: M. Raj, V. Bhaskar Semwal, G.C.Nandi. Hybrid Model for Passive Locomotion Control of a Biped Humanoid:The Artificial Neural Network Approach, International Journal of Interactive Multimedia and Artificial Intelligence, (2017), http://dx.doi.org/10.9781/ijimai.2017.10.001 * Corresponding author. E-mail addresses: [email protected] (Manish Raj), vsemwal@...
Rivers are important as the main source of supply for drinking, agriculture and industry.However, drinking water quality in terms of qualitative parameters, is the most important variable. Studias and predicting changes in quality parameters along a river, are one of the goals of water resources planners and managers. In this regard, many water quality models in order to maintain better water ...
Background and purpose: Since the human health is an essential issue in medical sciences, accurate predicting the individual's disease status is of great importance. Therefore, predicting with models minimum error and maximum certainty should be used. This study used artificial neural network model for predicting coronary artery disease (CAD) because it is more precise Comared to after models. ...
in today’s business competitive world, decision makers of companies try to employ standard, efficient, theoretical and operational proven methods as a competitive advantage for making their critical strategic business decisions in order to survive in their industry. in this paper, a hybrid model based on fuzzy analytic hierarchy process (fahp) and artificial neural network (ann) is presented. t...
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