A preliminary estimation of ablation property for carbon-carbon composites by artificial neutral net （ANN） method was presented. It was found that the carbon-carbon composites＇ density, degree of graphitization and...A preliminary estimation of ablation property for carbon-carbon composites by artificial neutral net （ANN） method was presented. It was found that the carbon-carbon composites＇ density, degree of graphitization and the sort of matrix are the key controlling factors for its ablative performance. Then, a brief fuzzy mathematical relationship was established between these factors and ablative performance. Through experiments, the performance of the ANN was evaluated, which was used in the ablative performance prediction of C/C composites. When the training set, the structure and the training parameter of the net change, the best match ratio of these parameters was achieved. Based on the match ratio, this paper forecasts and evaluates the carbon-carbon ablation performance. Through experiences, the ablative performance prediction of carbon-carbon using ANN can achieve the line ablation rate, which satisfies the need of precision of practical engineering fields.展开更多
In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(...In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(FAHP) and artificial neural network(ANN) from the perspective of accuracy and quickness is proposed.An analytic hierarchy process model for the transformer risk assessment is built by analysis of the risk factors affecting the transformer risk level and the weight relation of each risk factor in transformer risk calculation is analyzed by application of fuzzy consistency judgment matrix;with utilization of adaptive ability and nonlinear mapping ability of the ANN,the risk factors with large weights are used as input of neutral network,and thus intelligent quantitative assessment of transformer risk is realized.The simulation result shows that the proposed method increases the speed and accuracy of the risk assessment and can provide feasible decision basis for the transformer risk management and maintenance decisions.展开更多
Using the artificial nerve network′s knowledge, establish the estimate′s mathematics model of the soybean′s yield, and by the model we can increase accuracy of the soybean yield forecast.
基金supported by the National Natural Science Foundation of China under Grant No.10572044.
文摘A preliminary estimation of ablation property for carbon-carbon composites by artificial neutral net （ANN） method was presented. It was found that the carbon-carbon composites＇ density, degree of graphitization and the sort of matrix are the key controlling factors for its ablative performance. Then, a brief fuzzy mathematical relationship was established between these factors and ablative performance. Through experiments, the performance of the ANN was evaluated, which was used in the ablative performance prediction of C/C composites. When the training set, the structure and the training parameter of the net change, the best match ratio of these parameters was achieved. Based on the match ratio, this paper forecasts and evaluates the carbon-carbon ablation performance. Through experiences, the ablative performance prediction of carbon-carbon using ANN can achieve the line ablation rate, which satisfies the need of precision of practical engineering fields.
基金Project(50977003) supported by the National Natural Science Foundation of China
文摘In operation,risk arising from power transformer faults is of much uncertainty and complicacy.To timely and objectively control the risks,a transformer risk assessment method based on fuzzy analytic hierarchy process(FAHP) and artificial neural network(ANN) from the perspective of accuracy and quickness is proposed.An analytic hierarchy process model for the transformer risk assessment is built by analysis of the risk factors affecting the transformer risk level and the weight relation of each risk factor in transformer risk calculation is analyzed by application of fuzzy consistency judgment matrix;with utilization of adaptive ability and nonlinear mapping ability of the ANN,the risk factors with large weights are used as input of neutral network,and thus intelligent quantitative assessment of transformer risk is realized.The simulation result shows that the proposed method increases the speed and accuracy of the risk assessment and can provide feasible decision basis for the transformer risk management and maintenance decisions.
文摘Using the artificial nerve network′s knowledge, establish the estimate′s mathematics model of the soybean′s yield, and by the model we can increase accuracy of the soybean yield forecast.
