Titlebook: Engineering Applications of Neural Networks; 14th International C Lazaros Iliadis,Harris Papadopoulos,Chrisina Jayne Conference proceedings

窗帘等

Claudia Georgia Sabba,Ubiratan D’Ambrosioplexity of some dances increases the difficulty of identifying such dances, thus making the traditional dance recognition a challenging subset within the general field of activity recognition. In this paper, three types of features are extracted to represent traditional dance video sequences and a b

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Javed Ali Kalhoro,Alexander Cromwell’s seat pad and backrest and classifies the user posture and changes its conformation. We gathered the pressure maps for eleven standardized postures in order to perform the automatic posture classification, using neural networks. First we tried to find the best parameters for the neural network cla

果仁

极为愤怒

Neural Network Simulation of Photosynthetic Productionroposed simulation methods is illustrated by the optimal control problem of photosynthetic production described by discrete time delay differential equations. Results show that adaptive critic based systematic approach holds promise for obtaining the optimal control with control and state constraints.

愚蠢人

草率男

Application of Particle Swarm Optimization Algorithm to Neural Network Training Process in the Localhe given (x,y,floor) coordinates from more than two thousand points inside a five story building..We show that the PSO algorithm could be with success applied as an initial training algorithm for the MLP for both classification and regression problems.

SLUMP

A State Space Approach and Hurst Exponent for Ensemble Predictorst component classification is performed using novel variability measure derived from Hurst exponent. The validity of our concept is presented on the real problem of load forecasting in the Polish power system.

不满分子

Concluding Thoughts and Implicationsrature forecasts. Our proposed models were evaluated and compared in-sample and out-of-sample in various locations. Our findings suggest that the proposed nonlinear methods significantly outperform the alternative linear models and can be used for accurate weather derivative pricing.

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Luciana C. de Oliveira,Marta Civileters that have been studied are the R. and R.. A feed forward back propagation neural network was fitted on the experimental results. It was found that accurate predictions of performance can be achieved through the feed forward back propagation (FFBP) neural network developed for the surface texture parameters.

向下五度才偏

Temperature Forecasting in the Concept of Weather Derivatives: A Comparison between Wavelet Networksrature forecasts. Our proposed models were evaluated and compared in-sample and out-of-sample in various locations. Our findings suggest that the proposed nonlinear methods significantly outperform the alternative linear models and can be used for accurate weather derivative pricing.