The beam-to-column semirigid connection in a steel frame structure is represented by a zero-length rotational spring at the end of the beam element. The beam-to-column semirigid connection behavior is represented by i...The beam-to-column semirigid connection in a steel frame structure is represented by a zero-length rotational spring at the end of the beam element. The beam-to-column semirigid connection behavior is represented by its moment-rotation relationship. Several traditional mathematical models have been proposed to fit the moment-rotation curves from the experimental database,but they may be more reliable within certain ranges. In this paper, the intellectualized analytical model is proposed in the semirigid connections for top and seat angles with double web angles using the feed-forward back-propagation artificial neural network （BP-ANN） technique. the intellectualized analytical model from experimental results based on BP-ANN is more reliable and it is a better choice to the moment-rotation curves for beam-to-column semirigid connection. The results are found to provide effectiveness to the experimental response that is satisfactory for use in steel structural engineering design.展开更多
Bionic optimisation is one of the most popular and efficient applications of bionic engineering. As there are many different approaches and terms being used, we try to come up with a structuring of the strategies and ...Bionic optimisation is one of the most popular and efficient applications of bionic engineering. As there are many different approaches and terms being used, we try to come up with a structuring of the strategies and compare the efficiency of the different methods. The methods mostly proposed in literature may be classified into evolutionary, particle swarm and artificial neural net optimisation. Some related classes have to be mentioned as the non-sexual fern optimisation and the response surfaces, which are close to the neuron nets. To come up with a measure of the efficiency that allows to take into account some of the published results the technical optimisation problems were derived from the ones given in literature. They deal with elastic studies of frame structures, as the computing time for each individual is very short. General proposals, which approach to use may not be given. It seems to be a good idea to learn about the applicability of the different methods at different problem classes and then do the optimisation according to these experiences. Furthermore in many cases there is some evidence that switching from one method to another improves the performance. Finally the identification of the exact position of the optimum by gradient methods is often more efficient than long random walks around local maxima.展开更多
文摘The beam-to-column semirigid connection in a steel frame structure is represented by a zero-length rotational spring at the end of the beam element. The beam-to-column semirigid connection behavior is represented by its moment-rotation relationship. Several traditional mathematical models have been proposed to fit the moment-rotation curves from the experimental database,but they may be more reliable within certain ranges. In this paper, the intellectualized analytical model is proposed in the semirigid connections for top and seat angles with double web angles using the feed-forward back-propagation artificial neural network （BP-ANN） technique. the intellectualized analytical model from experimental results based on BP-ANN is more reliable and it is a better choice to the moment-rotation curves for beam-to-column semirigid connection. The results are found to provide effectiveness to the experimental response that is satisfactory for use in steel structural engineering design.
文摘Bionic optimisation is one of the most popular and efficient applications of bionic engineering. As there are many different approaches and terms being used, we try to come up with a structuring of the strategies and compare the efficiency of the different methods. The methods mostly proposed in literature may be classified into evolutionary, particle swarm and artificial neural net optimisation. Some related classes have to be mentioned as the non-sexual fern optimisation and the response surfaces, which are close to the neuron nets. To come up with a measure of the efficiency that allows to take into account some of the published results the technical optimisation problems were derived from the ones given in literature. They deal with elastic studies of frame structures, as the computing time for each individual is very short. General proposals, which approach to use may not be given. It seems to be a good idea to learn about the applicability of the different methods at different problem classes and then do the optimisation according to these experiences. Furthermore in many cases there is some evidence that switching from one method to another improves the performance. Finally the identification of the exact position of the optimum by gradient methods is often more efficient than long random walks around local maxima.
