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
A fuzzy synthetic assessment model of construction safety in a mountainous freeway is established as well as a relevant safety assessment factor system. The weights of factors are calculated by analytic hierarchy proc...A fuzzy synthetic assessment model of construction safety in a mountainous freeway is established as well as a relevant safety assessment factor system. The weights of factors are calculated by analytic hierarchy process, and the influence sequence of assessment is determined. Choosing Cauchy distribution, subjection function of factor sets and judging matrix were obtained. Safe evaluation vector was calculated and the safety status grade of the freeway was estimated through fuzzy synthetic assessment. The construction safety status of five work sites in Hubei Hurongxi Freeway is evaluated by using fuzzy synthetic evaluation model. Construction safety evaluation ranks and degrees of all work sites were calculated. Results show that the situations of safety control management and the security of the third work site should be strengthened. Results also reveal that the whole safety on thespot can be determined by adopting fuzzy assessment. Also, corresponding preventive and improvement measures are provided.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.
基金Supported by the Project of Transportation Science and Technology of Hubei Province (2007-582)
文摘A fuzzy synthetic assessment model of construction safety in a mountainous freeway is established as well as a relevant safety assessment factor system. The weights of factors are calculated by analytic hierarchy process, and the influence sequence of assessment is determined. Choosing Cauchy distribution, subjection function of factor sets and judging matrix were obtained. Safe evaluation vector was calculated and the safety status grade of the freeway was estimated through fuzzy synthetic assessment. The construction safety status of five work sites in Hubei Hurongxi Freeway is evaluated by using fuzzy synthetic evaluation model. Construction safety evaluation ranks and degrees of all work sites were calculated. Results show that the situations of safety control management and the security of the third work site should be strengthened. Results also reveal that the whole safety on thespot can be determined by adopting fuzzy assessment. Also, corresponding preventive and improvement measures are provided.
