The robust parameter design method is a traditional approach to robust experimental design that seeks to obtain the optimal combination of factors/levels. To overcome some of the defects of the inflatable wing paramet...The robust parameter design method is a traditional approach to robust experimental design that seeks to obtain the optimal combination of factors/levels. To overcome some of the defects of the inflatable wing parameter design method, this paper proposes an optimization design scheme based on orthogonal testing and support vector machines （SVMs）. Orthogonal testing design is used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iterations and improve the identification accuracy and efficiency. Orthogonal tests consisting of three factors and three levels are designed to analyze the parameters of pressure, uniform applied load and the number of chambers that affect the bending response of inflatable wings. An SVM intelligent model is established and limited orthogonal test swatches are studied. Thus, the precise relationships between each parameter and product quality features, as well the signal-to-noise ratio （SNR）, can be obtained. This can guide general technological design optimization.展开更多
In recent times,the images and videos have emerged as one of the most important information source depicting the real time scenarios.Digital images nowadays serve as input for many applications and replacing the manua...In recent times,the images and videos have emerged as one of the most important information source depicting the real time scenarios.Digital images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D plane.The capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern recognition.One of the application fields pertains to detection of diseases occurring in the plants,which are destroying the widespread fields.Traditionally the disease detection process was done by a domain expert using manual examination and laboratory tests.This is a tedious and time consuming process and does not suffice the accuracy levels.This creates a room for the research in developing automation based methods where the images captured through sensors and cameras will be used for detection of disease and control its spreading.The digital images captured from the field’s forms the dataset which trains the machine learning models to predict the nature of the disease.The accuracy of these models is greatly affected by the amount of noise and ailments present in the input images,appropriate segmentation methodology,feature vector development and the choice of machine learning algorithm.To ensure the high rated performance of the designed system the research is moving in a direction to fine tune each and every stage separately considering their dependencies on subsequent stages.Therefore the most optimum solution can be obtained by considering the image processing methodologies for improving the quality of image and then applying statistical methods for feature extraction and selection.The training vector thus developed is capable of presenting the relationship between the feature values and the target class.In this article,a highly accurate system model for detecting the diseases occurring in citrus fruits using a hybrid feature development approach is proposed.The overall improvement in terms of accuracy is measured and depicted.展开更多
Use of multidisciplinary analysis in reliabilitybased design optimization(RBDO) results in the emergence of the important method of reliability-based multidisciplinary design optimization(RBMDO). To enhance the effici...Use of multidisciplinary analysis in reliabilitybased design optimization(RBDO) results in the emergence of the important method of reliability-based multidisciplinary design optimization(RBMDO). To enhance the efficiency and convergence of the overall solution process,a decoupling algorithm for RBMDO is proposed herein.Firstly, to decouple the multidisciplinary analysis using the individual disciplinary feasible(IDF) approach, the RBMDO is converted into a conventional form of RBDO. Secondly,the incremental shifting vector(ISV) strategy is adopted to decouple the nested optimization of RBDO into a sequential iteration process composed of design optimization and reliability analysis, thereby improving the efficiency significantly. Finally, the proposed RBMDO method is applied to the design of two actual electronic products: an aerial camera and a car pad. For these two applications, two RBMDO models are created, each containing several finite element models(FEMs) and relatively strong coupling between the involved disciplines. The computational results demonstrate the effectiveness of the proposed method.展开更多
The size and performance of a System LSI depend heavily on the architecture which is chosen. As a result, the architecture design phase is one of the most important steps in the System LSI development process and is c...The size and performance of a System LSI depend heavily on the architecture which is chosen. As a result, the architecture design phase is one of the most important steps in the System LSI development process and is critical to the commercial success of a device. In this paper, we propose a C-based variable length and vector pipeline (VVP) architecture design methodology and apply it to the design of the output probability computation circuit for a speech recognition system. VVP processing accelerated by loop optimization, memory access methods, and application-specific cir- cuit design was implemented to calculate the Hidden Markov Model (HMM) output probability at high speed and its performance is evaluated. It is shown that designers can explore a wide range of design choices and generate complex circuits in a short time by using a C-based pipeline architecture design method.展开更多
The application of some MVS operations (each dimension of which corresponds to a capability indicator) in system capability analysis and design, including capability indicator requirement analysis, effectiveness analy...The application of some MVS operations (each dimension of which corresponds to a capability indicator) in system capability analysis and design, including capability indicator requirement analysis, effectiveness analysis, sensibility analysis, fuzzy analysis, stability analysis, capability optimization design, etc., is discussed in the second paper of this series of papers. And some MVS-based models and algorithms for capability analysis and design are put forward. Finally, an example of capability analysis and optimization design is given for explaining the usages of related models and algorithms.展开更多
In order to deal with the issue of huge computational cost very well in direct numerical simulation, the traditional response surface method (RSM) as a classical regression algorithm is used to approximate a functiona...In order to deal with the issue of huge computational cost very well in direct numerical simulation, the traditional response surface method (RSM) as a classical regression algorithm is used to approximate a functional relationship between the state variable and basic variables in reliability design. The algorithm has treated successfully some problems of implicit performance function in reliability analysis. However, its theoretical basis of empirical risk minimization narrows its range of applications for...展开更多
This article describes the pack & unpack performance of the vector using YH-1 supercomputer as its platform, with its emphasis on the pack & unpack technique's unique application to vector computation, in ...This article describes the pack & unpack performance of the vector using YH-1 supercomputer as its platform, with its emphasis on the pack & unpack technique's unique application to vector computation, in the light of vector computer's characteristics and some practical cases. The practical numerical experiment proves that the pack & unpack techniques is a key method to the depth parallel development and vectorization research of large scale scientific computation project, and which is a highly effective method to vectorizing application programs.展开更多
In the paper, a new selection probability inspired by artificial bee colony algorithm is introduced into standard particle swarm optimization by improving the global extremum updating condition to enhance the capabili...In the paper, a new selection probability inspired by artificial bee colony algorithm is introduced into standard particle swarm optimization by improving the global extremum updating condition to enhance the capability of its overall situation search. The experiment result shows that the new scheme is more valuable and effective than other schemes in the convergence of codebook design and the performance of codebook, and it can avoid the premature phenomenon of the particles.展开更多
The optimum design method based on the reliability is presented to the stochastic structure systems （i. e., the sectional area, length, elastic module and strength of the structural member are random variables ） und...The optimum design method based on the reliability is presented to the stochastic structure systems （i. e., the sectional area, length, elastic module and strength of the structural member are random variables ） under the random loads. The sensitivity expression of system reliability index and the safety margins were presented in the stochastic structure systems. The optimum vector method was given. First, the expressions of the reliability index of the safety margins with the improved first-order second-moment and the stochastic finite element method were deduced, and then the expressions of the systemic failure probability by probabilistic network evaluation technique（PNET） method were obtained. After derivation calculus ,the expressions of the sensitivity analysis for the system reliability were obtained. Moreover, the optimum design with the optimum vector algorithm was undertaken. In the optimum iterative procedure, the gradient step and the optimum vector step were adopted to calculate. At the last, a numerical example was provided to illustrate that the method is efficient in the calculation, stably converges and fits the application in engineering.展开更多
The data topology structure of uniform experiment design (UD) is too complex to be reasonable regressed. In this paper, the principle and method of distinguish the training data and testing data were described to make...The data topology structure of uniform experiment design (UD) is too complex to be reasonable regressed. In this paper, the principle and method of distinguish the training data and testing data were described to make a reasonable regression when uniform experiment design combined with support vector regression (SVR). Two equivalent ways which were the smallest enclosing hypersphere perceptron (SEH) and the enclosing simplex perceptron (ES) were provided to discover the topology relationship of the process parameter datum. To give an application, a series of experiments about laser cladding layer quality were conducted by UD to get the relationship of load, velocity and wearing capacity. Results showed that only the testing datum recommended by the two perceptrons got a good forecasting by SVR. Therefore, the two perceptrons could guide experiments with process parameter data of complex topology structure. Further, the application could be extended over a much wider field of experiments.展开更多
文摘The robust parameter design method is a traditional approach to robust experimental design that seeks to obtain the optimal combination of factors/levels. To overcome some of the defects of the inflatable wing parameter design method, this paper proposes an optimization design scheme based on orthogonal testing and support vector machines （SVMs）. Orthogonal testing design is used to estimate the appropriate initial value and variation domain of each variable to decrease the number of iterations and improve the identification accuracy and efficiency. Orthogonal tests consisting of three factors and three levels are designed to analyze the parameters of pressure, uniform applied load and the number of chambers that affect the bending response of inflatable wings. An SVM intelligent model is established and limited orthogonal test swatches are studied. Thus, the precise relationships between each parameter and product quality features, as well the signal-to-noise ratio （SNR）, can be obtained. This can guide general technological design optimization.
基金This work was supported by Taif University Researchers Supporting Project(TURSP)under number(TURSP-2020/73)Taif University,Taif,Saudi Arabia。
文摘In recent times,the images and videos have emerged as one of the most important information source depicting the real time scenarios.Digital images nowadays serve as input for many applications and replacing the manual methods due to their capabilities of 3D scene representation in 2D plane.The capabilities of digital images along with utilization of machine learning methodologies are showing promising accuracies in many applications of prediction and pattern recognition.One of the application fields pertains to detection of diseases occurring in the plants,which are destroying the widespread fields.Traditionally the disease detection process was done by a domain expert using manual examination and laboratory tests.This is a tedious and time consuming process and does not suffice the accuracy levels.This creates a room for the research in developing automation based methods where the images captured through sensors and cameras will be used for detection of disease and control its spreading.The digital images captured from the field’s forms the dataset which trains the machine learning models to predict the nature of the disease.The accuracy of these models is greatly affected by the amount of noise and ailments present in the input images,appropriate segmentation methodology,feature vector development and the choice of machine learning algorithm.To ensure the high rated performance of the designed system the research is moving in a direction to fine tune each and every stage separately considering their dependencies on subsequent stages.Therefore the most optimum solution can be obtained by considering the image processing methodologies for improving the quality of image and then applying statistical methods for feature extraction and selection.The training vector thus developed is capable of presenting the relationship between the feature values and the target class.In this article,a highly accurate system model for detecting the diseases occurring in citrus fruits using a hybrid feature development approach is proposed.The overall improvement in terms of accuracy is measured and depicted.
基金supported by the Major Program of the National Natural Science Foundation of China (Grant 51490662)the Funds for Distinguished Young Scientists of Hunan Province (Grant 14JJ1016)+1 种基金the State Key Program of the National Science Foundation of China (11232004)the Heavy-duty Tractor Intelligent Manufacturing Technology Research and System Development (Grant 2016YFD0701105)
文摘Use of multidisciplinary analysis in reliabilitybased design optimization(RBDO) results in the emergence of the important method of reliability-based multidisciplinary design optimization(RBMDO). To enhance the efficiency and convergence of the overall solution process,a decoupling algorithm for RBMDO is proposed herein.Firstly, to decouple the multidisciplinary analysis using the individual disciplinary feasible(IDF) approach, the RBMDO is converted into a conventional form of RBDO. Secondly,the incremental shifting vector(ISV) strategy is adopted to decouple the nested optimization of RBDO into a sequential iteration process composed of design optimization and reliability analysis, thereby improving the efficiency significantly. Finally, the proposed RBMDO method is applied to the design of two actual electronic products: an aerial camera and a car pad. For these two applications, two RBMDO models are created, each containing several finite element models(FEMs) and relatively strong coupling between the involved disciplines. The computational results demonstrate the effectiveness of the proposed method.
文摘The size and performance of a System LSI depend heavily on the architecture which is chosen. As a result, the architecture design phase is one of the most important steps in the System LSI development process and is critical to the commercial success of a device. In this paper, we propose a C-based variable length and vector pipeline (VVP) architecture design methodology and apply it to the design of the output probability computation circuit for a speech recognition system. VVP processing accelerated by loop optimization, memory access methods, and application-specific cir- cuit design was implemented to calculate the Hidden Markov Model (HMM) output probability at high speed and its performance is evaluated. It is shown that designers can explore a wide range of design choices and generate complex circuits in a short time by using a C-based pipeline architecture design method.
文摘The application of some MVS operations (each dimension of which corresponds to a capability indicator) in system capability analysis and design, including capability indicator requirement analysis, effectiveness analysis, sensibility analysis, fuzzy analysis, stability analysis, capability optimization design, etc., is discussed in the second paper of this series of papers. And some MVS-based models and algorithms for capability analysis and design are put forward. Finally, an example of capability analysis and optimization design is given for explaining the usages of related models and algorithms.
基金National High-tech Research and Development Pro-gram (2006AA04Z405)
文摘In order to deal with the issue of huge computational cost very well in direct numerical simulation, the traditional response surface method (RSM) as a classical regression algorithm is used to approximate a functional relationship between the state variable and basic variables in reliability design. The algorithm has treated successfully some problems of implicit performance function in reliability analysis. However, its theoretical basis of empirical risk minimization narrows its range of applications for...
文摘This article describes the pack & unpack performance of the vector using YH-1 supercomputer as its platform, with its emphasis on the pack & unpack technique's unique application to vector computation, in the light of vector computer's characteristics and some practical cases. The practical numerical experiment proves that the pack & unpack techniques is a key method to the depth parallel development and vectorization research of large scale scientific computation project, and which is a highly effective method to vectorizing application programs.
基金Sponsored by the Qing Lan Project of Jiangsu Province
文摘In the paper, a new selection probability inspired by artificial bee colony algorithm is introduced into standard particle swarm optimization by improving the global extremum updating condition to enhance the capability of its overall situation search. The experiment result shows that the new scheme is more valuable and effective than other schemes in the convergence of codebook design and the performance of codebook, and it can avoid the premature phenomenon of the particles.
文摘The optimum design method based on the reliability is presented to the stochastic structure systems （i. e., the sectional area, length, elastic module and strength of the structural member are random variables ） under the random loads. The sensitivity expression of system reliability index and the safety margins were presented in the stochastic structure systems. The optimum vector method was given. First, the expressions of the reliability index of the safety margins with the improved first-order second-moment and the stochastic finite element method were deduced, and then the expressions of the systemic failure probability by probabilistic network evaluation technique（PNET） method were obtained. After derivation calculus ,the expressions of the sensitivity analysis for the system reliability were obtained. Moreover, the optimum design with the optimum vector algorithm was undertaken. In the optimum iterative procedure, the gradient step and the optimum vector step were adopted to calculate. At the last, a numerical example was provided to illustrate that the method is efficient in the calculation, stably converges and fits the application in engineering.
文摘The data topology structure of uniform experiment design (UD) is too complex to be reasonable regressed. In this paper, the principle and method of distinguish the training data and testing data were described to make a reasonable regression when uniform experiment design combined with support vector regression (SVR). Two equivalent ways which were the smallest enclosing hypersphere perceptron (SEH) and the enclosing simplex perceptron (ES) were provided to discover the topology relationship of the process parameter datum. To give an application, a series of experiments about laser cladding layer quality were conducted by UD to get the relationship of load, velocity and wearing capacity. Results showed that only the testing datum recommended by the two perceptrons got a good forecasting by SVR. Therefore, the two perceptrons could guide experiments with process parameter data of complex topology structure. Further, the application could be extended over a much wider field of experiments.
