[ Objective] The paper aimed to optimize cottonseed meal de-gossypol process by extrusion. [ Method ] The artificial neural network （ANN） was used to stimulate the degradation of free gossypol in cottonseed meal by ...[ Objective] The paper aimed to optimize cottonseed meal de-gossypol process by extrusion. [ Method ] The artificial neural network （ANN） was used to stimulate the degradation of free gossypol in cottonseed meal by extrusion process, and a three-layer back propagation neural network was established to predict the degradation of free gossypol. [ Result] The result of 10-fold cross validation showed that the ANN with the training function as traingdx at hidden layer with eight neurons gave the smallest mean square error （MSE）. ANN predicted results were very close to the experimental results with correlation coefficient （R2 ） of 0.994 1 and RMSE of 0.497 1. A genetic algorithm （GA） based on the established neural network model was also used for optimizing de-gossypol process. The re- sults of GA showed that the optimal conditions of de-gossypol were puffing temperature 131℃, water ratio 51% , rotational speed 158 r/rain, and feeding speed 136 kg/h, while under this condition the degradation rate of free gossypol was 90.50%, which was close to the predicted result of CA with the small average relative er- ror of 1.38%. [ Conclusion] These results suggested that the GA based on a neural network model might be an excellent tool for optimizing cottonseed meal de-gos- sypol process.展开更多
In the ultrasonic detection of defects in friction welded joints, it is difficult to exactly detect some weak bonding defects because of the noise pollution. This paper proposed an improved threshold function based on...In the ultrasonic detection of defects in friction welded joints, it is difficult to exactly detect some weak bonding defects because of the noise pollution. This paper proposed an improved threshold function based on the multi-resolution analysis wavelet threshold de-noising method which was put forward by Donoho and Johnstone, and applied this method in the de-noising of the defective signals. This threshold function overcomes the discontinuous shortcoming of the hard-threshold function and the disadvantage of soft threshold function which causes an invariable deviation between the estimated wavelet coeffwients and the decomposed wavelet coefficients. The improved threshold function is of simple expression and convenient for calculation. The actual test results of defect noise signal show that this improved method can get less mean square error （ MSE ） and higher signal-to-noise ratio of reconstructed signals than those calculated from hard threshold and soft threshold methods. The improved threshold function has excellent de-noising effect.展开更多
This article explains the imbalance in DES and introduces the operators in IDEA. At last it puts forward a Unsym-metrical Block Encryption Algorithm which is achieved by adding some operators to DES.
针对汽轮机变工况运行存在负荷偏差的问题,提出一种基于差分进化算法(differential evolution,DE)和多标签随机森林(multi-label random forest,MLRF)结合的汽轮机负荷偏差原因分类模型。通过斯皮尔曼(Spearman)相关性系数,分析影响汽...针对汽轮机变工况运行存在负荷偏差的问题,提出一种基于差分进化算法(differential evolution,DE)和多标签随机森林(multi-label random forest,MLRF)结合的汽轮机负荷偏差原因分类模型。通过斯皮尔曼(Spearman)相关性系数,分析影响汽轮机负荷出力的相关联变量;采用DE算法优化MLRF模型参数,建立基于DE-MLRF的汽轮机负荷偏差原因分类模型。结合某660 MW汽轮机实际运行数据进行实验验证,结果表明,与其他7种算法相比,DE算法优化的MLRF模型误报率(1.9024%)、漏报率(1.8541%)最低,可为汽轮机负荷偏差原因定位提供决策支持。展开更多
A computationally efficient soft-output detector with lattice-reduction （LR） for the multiple-input multiple-output （MIMO） systems is proposed. In the proposed scheme, the sorted QR de- composition is applied on t...A computationally efficient soft-output detector with lattice-reduction （LR） for the multiple-input multiple-output （MIMO） systems is proposed. In the proposed scheme, the sorted QR de- composition is applied on the lattice-reduced equivalent channel to obtain the tree structure. With the aid of the boundary control, the stack algorithm searches a small part of the whole search tree to generate a handful of candidate lists in the reduced lattice. The proposed soft-output algorithm achieves near-optimal perfor- mance in a coded MIMO system and the associated computational complexity is substantially lower than that of previously proposed methods.展开更多
为实现前沿阵地和地面防空两种典型应用约束条件下到达时间差(Time Difference of Arrival,TDOA)定位的自动布站优化,分析了这两种典型约束条件下的基站长度、站点间角度等对定位精度的影响。提出了基于自适应差分进化(Differential Evo...为实现前沿阵地和地面防空两种典型应用约束条件下到达时间差(Time Difference of Arrival,TDOA)定位的自动布站优化,分析了这两种典型约束条件下的基站长度、站点间角度等对定位精度的影响。提出了基于自适应差分进化(Differential Evolution,DE)算法的TDOA自动布站优化策略。采用该算法对这两种约束条件下的自动布站优化进行了仿真分析,并对自适应DE算法计算复杂度进行了分析。结果表明,自适应DE算法的自动布站复杂度低,收敛快速,与定位误差分析一致,具有较好的全局寻优能力。展开更多
Through a precise recursion of B-spline bases, this paper presents an efficient algorithm for the calculation of NURBS curves and all their derivatives. The algorithm requires less storage and is proved to be stable.
基金Supported by Guide Project of Xinjiang Academy of Agricultural and Reclamation Science(60YYD201308)
文摘[ Objective] The paper aimed to optimize cottonseed meal de-gossypol process by extrusion. [ Method ] The artificial neural network （ANN） was used to stimulate the degradation of free gossypol in cottonseed meal by extrusion process, and a three-layer back propagation neural network was established to predict the degradation of free gossypol. [ Result] The result of 10-fold cross validation showed that the ANN with the training function as traingdx at hidden layer with eight neurons gave the smallest mean square error （MSE）. ANN predicted results were very close to the experimental results with correlation coefficient （R2 ） of 0.994 1 and RMSE of 0.497 1. A genetic algorithm （GA） based on the established neural network model was also used for optimizing de-gossypol process. The re- sults of GA showed that the optimal conditions of de-gossypol were puffing temperature 131℃, water ratio 51% , rotational speed 158 r/rain, and feeding speed 136 kg/h, while under this condition the degradation rate of free gossypol was 90.50%, which was close to the predicted result of CA with the small average relative er- ror of 1.38%. [ Conclusion] These results suggested that the GA based on a neural network model might be an excellent tool for optimizing cottonseed meal de-gos- sypol process.
文摘In the ultrasonic detection of defects in friction welded joints, it is difficult to exactly detect some weak bonding defects because of the noise pollution. This paper proposed an improved threshold function based on the multi-resolution analysis wavelet threshold de-noising method which was put forward by Donoho and Johnstone, and applied this method in the de-noising of the defective signals. This threshold function overcomes the discontinuous shortcoming of the hard-threshold function and the disadvantage of soft threshold function which causes an invariable deviation between the estimated wavelet coeffwients and the decomposed wavelet coefficients. The improved threshold function is of simple expression and convenient for calculation. The actual test results of defect noise signal show that this improved method can get less mean square error （ MSE ） and higher signal-to-noise ratio of reconstructed signals than those calculated from hard threshold and soft threshold methods. The improved threshold function has excellent de-noising effect.
文摘This article explains the imbalance in DES and introduces the operators in IDEA. At last it puts forward a Unsym-metrical Block Encryption Algorithm which is achieved by adding some operators to DES.
文摘针对汽轮机变工况运行存在负荷偏差的问题,提出一种基于差分进化算法(differential evolution,DE)和多标签随机森林(multi-label random forest,MLRF)结合的汽轮机负荷偏差原因分类模型。通过斯皮尔曼(Spearman)相关性系数,分析影响汽轮机负荷出力的相关联变量;采用DE算法优化MLRF模型参数,建立基于DE-MLRF的汽轮机负荷偏差原因分类模型。结合某660 MW汽轮机实际运行数据进行实验验证,结果表明,与其他7种算法相比,DE算法优化的MLRF模型误报率(1.9024%)、漏报率(1.8541%)最低,可为汽轮机负荷偏差原因定位提供决策支持。
文摘A computationally efficient soft-output detector with lattice-reduction （LR） for the multiple-input multiple-output （MIMO） systems is proposed. In the proposed scheme, the sorted QR de- composition is applied on the lattice-reduced equivalent channel to obtain the tree structure. With the aid of the boundary control, the stack algorithm searches a small part of the whole search tree to generate a handful of candidate lists in the reduced lattice. The proposed soft-output algorithm achieves near-optimal perfor- mance in a coded MIMO system and the associated computational complexity is substantially lower than that of previously proposed methods.
文摘为实现前沿阵地和地面防空两种典型应用约束条件下到达时间差(Time Difference of Arrival,TDOA)定位的自动布站优化,分析了这两种典型约束条件下的基站长度、站点间角度等对定位精度的影响。提出了基于自适应差分进化(Differential Evolution,DE)算法的TDOA自动布站优化策略。采用该算法对这两种约束条件下的自动布站优化进行了仿真分析,并对自适应DE算法计算复杂度进行了分析。结果表明,自适应DE算法的自动布站复杂度低,收敛快速,与定位误差分析一致,具有较好的全局寻优能力。
文摘Through a precise recursion of B-spline bases, this paper presents an efficient algorithm for the calculation of NURBS curves and all their derivatives. The algorithm requires less storage and is proved to be stable.
