An adaptive chaotic gradient descending optimization algorithm for single objective optimization was presented. A local minimum judged by two rules was obtained by an improved mutative-step gradient descending method....An adaptive chaotic gradient descending optimization algorithm for single objective optimization was presented. A local minimum judged by two rules was obtained by an improved mutative-step gradient descending method. A new optimal minimum was obtained to replace the local minimum by mutative-scale chaotic search algorithm whose scales are magnified gradually from a small scale in order to escape local minima. The global optimal value was attained by repeatedly iterating. At last, a BP (back-propagation) neural network model for forecasting slag output in matte converting was established. The algorithm was used to train the weights of the BP neural network model. The simulation results with a training data set of 400 samples show that the training process can be finished within 300 steps to obtain the global optimal value, and escape local minima effectively. An optimization system for operation parameters, which includes the forecasting model, is achieved, in which the output of converter increases by 6.0%, and the amount of the treated cool materials rises by 7.8% in the matte converting process.展开更多
Environmental warming places physiological constraints on organisms, which may be mitigated by their feeding behavior. Theory predicts that consumers should increase their feeding selectivity for more energetically va...Environmental warming places physiological constraints on organisms, which may be mitigated by their feeding behavior. Theory predicts that consumers should increase their feeding selectivity for more energetically valuable resources in warmer environments to offset the disproportionate increase in metabolic demand relative to ingestion rate. This may also result in a change in feeding strategy or a shift towards a more specialist diet. This study used a natural warming experiment to investigate temperature effects on the feeding selectivity of three freshwater invertebrate grazers： the snail Radix balthica, the blackfly larva Simulium aureum, and the midgefly larva Eukiefferiella minor. Chesson＇s Selectivity Index was used to compare the proportional abundance of diatom species in the guts of each invertebrate species with corresponding rock biofilms sampled from streams of different tem- perature. The snails became more selective in warmer streams, choosing high profile epilithic diatoms over other guilds and feeding on a lower diversity of diatom species. The blackfly larvae appeared to switch from active collector gathering of sessile high profile diatoms to more passive filter feeding of motile diatoms in warmer streams. No changes in selectivity were observed for the midgefly larvae, whose diet was representative of resource availability in the environment. These results suggest that key primary consumers in freshwater streams, which constitute a major portion of invertebrate biomass, can change their feeding behavior in warmer waters in a range of different ways. These patterns could potentially lead to fundamental changes in the flow of energy through freshwater food webs.展开更多
文摘An adaptive chaotic gradient descending optimization algorithm for single objective optimization was presented. A local minimum judged by two rules was obtained by an improved mutative-step gradient descending method. A new optimal minimum was obtained to replace the local minimum by mutative-scale chaotic search algorithm whose scales are magnified gradually from a small scale in order to escape local minima. The global optimal value was attained by repeatedly iterating. At last, a BP (back-propagation) neural network model for forecasting slag output in matte converting was established. The algorithm was used to train the weights of the BP neural network model. The simulation results with a training data set of 400 samples show that the training process can be finished within 300 steps to obtain the global optimal value, and escape local minima effectively. An optimization system for operation parameters, which includes the forecasting model, is achieved, in which the output of converter increases by 6.0%, and the amount of the treated cool materials rises by 7.8% in the matte converting process.
文摘Environmental warming places physiological constraints on organisms, which may be mitigated by their feeding behavior. Theory predicts that consumers should increase their feeding selectivity for more energetically valuable resources in warmer environments to offset the disproportionate increase in metabolic demand relative to ingestion rate. This may also result in a change in feeding strategy or a shift towards a more specialist diet. This study used a natural warming experiment to investigate temperature effects on the feeding selectivity of three freshwater invertebrate grazers： the snail Radix balthica, the blackfly larva Simulium aureum, and the midgefly larva Eukiefferiella minor. Chesson＇s Selectivity Index was used to compare the proportional abundance of diatom species in the guts of each invertebrate species with corresponding rock biofilms sampled from streams of different tem- perature. The snails became more selective in warmer streams, choosing high profile epilithic diatoms over other guilds and feeding on a lower diversity of diatom species. The blackfly larvae appeared to switch from active collector gathering of sessile high profile diatoms to more passive filter feeding of motile diatoms in warmer streams. No changes in selectivity were observed for the midgefly larvae, whose diet was representative of resource availability in the environment. These results suggest that key primary consumers in freshwater streams, which constitute a major portion of invertebrate biomass, can change their feeding behavior in warmer waters in a range of different ways. These patterns could potentially lead to fundamental changes in the flow of energy through freshwater food webs.
