Understanding the function learned by a neural network is crucial in many domains, e.g., to detect model’s adaption concept drift online learning. Existing global surrogate model approaches generate explanations maximizing fidelity between and on sample-basis, which can be very time-consuming. Therefore, these are not applicable scenarios where timely or frequent required. In this paper, we int...

three artificial neural networks (ann) models; general regression neural network (grnn), redial basis function (rbf) and three layer multiple perceptron network were carried out to evaluate the prediction of the apparent metabolizable energy (ame) of wheat and corn from its chemical composition in broiler. input variables included: gross energy (ge), crude protein (cp), crude fiber (cf), ether ...

during the past few years, modeling in agriculture has attracted considerable attention. new modeling methods including neural networks are employed in various industries, and it is necessary that their use in agriculture be also considered. this research addressed the trend of energy use in broiler farms in alborz province and sought to model the trend of energy consumption and production in t...

in this paper, we introduce a hybrid approach based on neural network and optimization teqnique to solve ordinary differential equation. in proposed model we use heyperbolic secont transformation function in hiden layer of neural network part and bfgs teqnique in optimization part. in comparison with existing similar neural networks proposed model provides solutions with high accuracy. numerica...

the use of neural networks methodology is not as common in the investigation and pre-diction noise as statistical analysis. the application of artificial neural networks for pre-diction of power tiller noise is set out in the present paper. the sound pressure signals for noise analysis were obtained in a field experiment using a 13-hp power tiller. during measurement and recording of the sound ...

the effects of different climatic, soil, geometric, and management factors on soil organic carbon (soc) degradation and sequestration potential was evaluated in the semi-arid zone of mereg watershed, west of iran. two nonparametric methods, viz. classification and regression tree (cart) and feed forward back propagation artificial neural network (ann) were compared with parametric multivariate ...

introduction we aimed to introduce a 6-universal-prismatic-spherical (ups) parallel mechanism for the human jaw motion and theoretically evaluate its kinematic problem. we proposed a strategy to provide a fast and accurate solution to the kinematic problem. the proposed strategy could accelerate the process of solution-finding for the direct kinematic problem by reducing the number of required ...

vehicle crashes are amongst the major causes of mortality and results in losses of lives and properties. alarge number of the vehicle crashes occur on rural roads. accidents become more noteworthy in two-laneroads due to going and coming traffic. therefore, prediction of crashes and their causes are considerablyimportant to reduce the number and severity of the accidents. the safety index is a ...

rotating machines in particular induction electrical machines are important industry instruments. in manufacturing, electrical motors are exposed to many damages, and this causes stators and rotors not to work correctly. in this paper we addressed modal analysis and an intelligent method to detect motor load condition and also the stator faults such as turn-to-turn and coil-to-coil faults using...

the hybrid fuzzy differential equations have a wide range of applications in science and engineering. we consider the problem of nding their numerical solutions by using a novel hybrid method based on fuzzy neural network. here neural network is considered as a part of large eld called neural computing or soft computing. the proposed algorithm is illustrated by numerical examples and the resu...