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A GPU-accelerated OpenCL implementation of a back-propagation artificial neural network for the creation of QSAR models for drug discovery and virtual high-throughput screening is presented. A QSAR model for HSD achieved an enrichment of 5.9 and area under the curve of 0.83 on an independent data set which signifies sufficient predictive ability for virtual high-throughput screening efforts. The speed-up...
In order to overcome the disadvantages such as low calculation precision and convergence rate of traditional BP neural network algorithm, a kind of nonlinear optimization method-BFGS method for unconstrained extreme problem is introduced into BP neural network algorithm, and a BFGS-BP neural network model is developed, which is applied well in structure deformation monitoring data processing and forecasting...
We propose in this paper the K-means-Greedy Algorithm (KGA) model to automate the process of finding the optimal value of the number of neurons in the hidden layer. The premise is that a backpropagation (BP) network which has this optimal number of neurons in its hidden layer would be able to produce accurate predictions of unknown values of a time series that it is trained with. We show that the...
Call center has been paid more and more attention, a method for predicting call center service grade with improved neural network algorithm was put forward according to the call center service quality management requirements in the enterprise. The optimization algorithm Levenberg-Marquardt was utilized to increase the convergence speed of BP neural network. And overcome the shortcomings of falling...
Applying the original experimental data of series 60 ship models, four-layer back propagation neural network is founded. Test samples and interpolated samples are randomly selected as input vectors. The worse of the maximum relative error, the average relative error and the correlation coefficient between the outputs and the goals, their regression lines and the performance curves plotted by the neural...
Data fusion based on feed-forward natural network can get the goal of minimum error, as well as reduce redundant data to transmit and save energy consumption. BP neutral network is considered as one of the most mature algorithm, but the traditional BP algorithm converges slowly and easy traps in a local minimum value, so new improved BP algorithm named algebraic algorithm is put forward. The algebraic...
In this paper, a systematic multi-objective fuzzy modeling approach is proposed, which can be regarded as a three-stage modeling procedure. In the first stage, an evolutionary based clustering algorithm is developed to extract an initial fuzzy rule base from the data. Based on this model, a back-propagation algorithm with momentum terms is used to refine the initial fuzzy model. The refined model...
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