In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of...In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of network,the rationale of recognition algorithm and the performance of proposed method were discussed in detail.The safety status pattern recognition problem of coalmines can be regard as a classification problem whose features are defined in a range,so using the ENN is most appropriate for this problem.The ENN-based recognition method can use a novel extension distance to measure the similarity between the object to be recognized and the class centers.To demonstrate the effectiveness of the proposed method,a real-world application on the geological safety status pattern recognition of coalmines was tested.Comparative experiments with existing method and other traditional ANN-based methods were conducted.The experimental results show that the proposed ENN-based recognition method can identify the safety status pattern of coalmines accurately with shorter learning time and simpler structure.The experimental results also confirm that the proposed method has a better performance in recognition accuracy,generalization ability and fault-tolerant ability,which are very useful in recognizing the safety status pattern in the process of coal production.展开更多
Many recent studies of ecological speciation have focused on ＂magic trait＂ scenarios, in which divergent selection on viability traits leads inextricably to corresponding divergence in mechanisms, especially mate re...Many recent studies of ecological speciation have focused on ＂magic trait＂ scenarios, in which divergent selection on viability traits leads inextricably to corresponding divergence in mechanisms, especially mate recognition systems, that facilitate assortative mating. Speciation however may also proceed via other scenarios, such as when populations experience directly se- lected or random divergence in mate recognition systems. The relative contributions of magic trait versus other scenarios for speciation remain virtually unexplored. The present study aims to test the relative contribution of the magic trait scenario in the divergence of populations of the medium ground finch Geospiza fortis of Santa Cruz Island, Galapagos. First, we assess differ- ences in G. fortis song between a northern population （Borrero Bay） and a southeastern population （El Garrapatero）, differences that we propose （along with other within-island geographic song variations） have arisen via scenarios that do not involve a magic trait scenario. Pairwise comparisons of raw and composite （PC） song parameters, as well as discriminant functions analyses, re- veal significant patterns of song divergence between sites. Second, we test the ability of territorial males at Borrero Bay to dis- criminate songs from the two sites. We find that G. fortis males can discriminate within-island song variants, responding more strongly to local than to ＂foreign＂ songs, along 3 raw and 1 composite response measures. Third, we compare these findings to prior data sets on song divergence and discrimination in Santa Cruz G. fortis. These comparisons suggest that song divergence and discrimination are shaped less strongly by geographic sources than by morphological （beak-related） sources. We thus argue that interpopulation song divergence and discrimination, fundamental elements of assortative mating in Darwin＇s finches, can be fos- tered in early stages of divergence under magic trait as well as alternative scenarios for speciation, but with more emphasis on the magic trait scenario, at least for this species on this island [Current Zoology 59 （1）： 8-19, 2013].展开更多
基金Project(107021) supported by the Key Foundation of Chinese Ministry of Education Project(2009643013) supported by China Scholarship Fund
文摘In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of network,the rationale of recognition algorithm and the performance of proposed method were discussed in detail.The safety status pattern recognition problem of coalmines can be regard as a classification problem whose features are defined in a range,so using the ENN is most appropriate for this problem.The ENN-based recognition method can use a novel extension distance to measure the similarity between the object to be recognized and the class centers.To demonstrate the effectiveness of the proposed method,a real-world application on the geological safety status pattern recognition of coalmines was tested.Comparative experiments with existing method and other traditional ANN-based methods were conducted.The experimental results show that the proposed ENN-based recognition method can identify the safety status pattern of coalmines accurately with shorter learning time and simpler structure.The experimental results also confirm that the proposed method has a better performance in recognition accuracy,generalization ability and fault-tolerant ability,which are very useful in recognizing the safety status pattern in the process of coal production.
文摘Many recent studies of ecological speciation have focused on ＂magic trait＂ scenarios, in which divergent selection on viability traits leads inextricably to corresponding divergence in mechanisms, especially mate recognition systems, that facilitate assortative mating. Speciation however may also proceed via other scenarios, such as when populations experience directly se- lected or random divergence in mate recognition systems. The relative contributions of magic trait versus other scenarios for speciation remain virtually unexplored. The present study aims to test the relative contribution of the magic trait scenario in the divergence of populations of the medium ground finch Geospiza fortis of Santa Cruz Island, Galapagos. First, we assess differ- ences in G. fortis song between a northern population （Borrero Bay） and a southeastern population （El Garrapatero）, differences that we propose （along with other within-island geographic song variations） have arisen via scenarios that do not involve a magic trait scenario. Pairwise comparisons of raw and composite （PC） song parameters, as well as discriminant functions analyses, re- veal significant patterns of song divergence between sites. Second, we test the ability of territorial males at Borrero Bay to dis- criminate songs from the two sites. We find that G. fortis males can discriminate within-island song variants, responding more strongly to local than to ＂foreign＂ songs, along 3 raw and 1 composite response measures. Third, we compare these findings to prior data sets on song divergence and discrimination in Santa Cruz G. fortis. These comparisons suggest that song divergence and discrimination are shaped less strongly by geographic sources than by morphological （beak-related） sources. We thus argue that interpopulation song divergence and discrimination, fundamental elements of assortative mating in Darwin＇s finches, can be fos- tered in early stages of divergence under magic trait as well as alternative scenarios for speciation, but with more emphasis on the magic trait scenario, at least for this species on this island [Current Zoology 59 （1）： 8-19, 2013].
