Due to the increasing power consumption of whole society and widely using of new non-linear and asymmetric electrical equipment,power quality assessment problem in the new period has attracted more and more attention....Due to the increasing power consumption of whole society and widely using of new non-linear and asymmetric electrical equipment,power quality assessment problem in the new period has attracted more and more attention.The mathematical essence of comprehensive assessment of power quality is a multiattribute optimal decision-making problem.In order to solve the key problem of determining the indicator weight in the process of power quality assessment,a rough analytic hierarchy process(AHP)is proposed to aggregate the judgment opinions of multiple experts and eliminate the subjective effects of single expert judgment.Based on the advantage of extension analysis for solving the incompatibility problem,extension analysis method is adopted to assess the power quality.The assessment grades of both total power quality and each assessment indicator are obtained by correlation function.Through a case of 110 kV bus of a converting station in a wind farm of China,the feasibility and effectiveness of the propose method are demonstrated.The result shows that the proposed method can determine the overall power quality of power grid,as well as compare the differences among the performance of assessment indicators and provide the basis for further improving of power quality.展开更多
Nonlinear solution of reinforced concrete structures, particularly complete load-deflection response, requires tracing of the equilibrium path and proper treatment of the limit and bifurcation points. In this regard, ...Nonlinear solution of reinforced concrete structures, particularly complete load-deflection response, requires tracing of the equilibrium path and proper treatment of the limit and bifurcation points. In this regard, ordinary solution techniques lead to instability near the limit points and also have problems in case of snap-through and snap-back. Thus they fail to predict the complete load-displacement response. The arc-length method serves the purpose well in principle, received wide acceptance in finite element analysis, and has been used extensively. However modifications to the basic idea are vital to meet the particular needs of the analysis. This paper reviews some of the recent developments of the method in the last two decades, with particular emphasis on nonlinear finite element analysis of reinforced concrete structures.展开更多
In today’s growing modern world environment,as human food activities are changing,it is affecting human health,thus leading to diseases like cancer.Cancer is a complex disease with many subtypes that affect human hea...In today’s growing modern world environment,as human food activities are changing,it is affecting human health,thus leading to diseases like cancer.Cancer is a complex disease with many subtypes that affect human health without premature treatment and cause death.So the analysis of early diagnosis and prognosis of cancer studies can improve clinical management by analyzing various features of observa-tion,which has become necessary to classify the type in cancer research.The research needs importance to organize the risk of the cancer patients based on data analysis to predict the result of premature treatment.This paper introduces a Maximal Region-Based Candidate Feature Selection(MRCFS)for early risk diagnosing using Soft-Max Feed Forward Neural Classification(SMF2NC)to solve the above pro-blem.The predictive model is based on a different relational feature learning model,which is possessed to candidate selection to reduce the dimensionality.The redundant features are processed marginal weight rates for observing similar features’variants and the absolute value.Softmax neural hidden layers are trained using the Sigmoid Activation Function(SAF)to create the logical condition for feed-forward layers.Further,the maximal features are introduced to invite a deep neural network con-structed on the Feed Forward Recurrent Neural Network(FFRNN).The classifier produces higher classification accuracy than the previous methods and observes the cancer detection,which is recommended for early diagnosis.展开更多
文摘Due to the increasing power consumption of whole society and widely using of new non-linear and asymmetric electrical equipment,power quality assessment problem in the new period has attracted more and more attention.The mathematical essence of comprehensive assessment of power quality is a multiattribute optimal decision-making problem.In order to solve the key problem of determining the indicator weight in the process of power quality assessment,a rough analytic hierarchy process(AHP)is proposed to aggregate the judgment opinions of multiple experts and eliminate the subjective effects of single expert judgment.Based on the advantage of extension analysis for solving the incompatibility problem,extension analysis method is adopted to assess the power quality.The assessment grades of both total power quality and each assessment indicator are obtained by correlation function.Through a case of 110 kV bus of a converting station in a wind farm of China,the feasibility and effectiveness of the propose method are demonstrated.The result shows that the proposed method can determine the overall power quality of power grid,as well as compare the differences among the performance of assessment indicators and provide the basis for further improving of power quality.
文摘Nonlinear solution of reinforced concrete structures, particularly complete load-deflection response, requires tracing of the equilibrium path and proper treatment of the limit and bifurcation points. In this regard, ordinary solution techniques lead to instability near the limit points and also have problems in case of snap-through and snap-back. Thus they fail to predict the complete load-displacement response. The arc-length method serves the purpose well in principle, received wide acceptance in finite element analysis, and has been used extensively. However modifications to the basic idea are vital to meet the particular needs of the analysis. This paper reviews some of the recent developments of the method in the last two decades, with particular emphasis on nonlinear finite element analysis of reinforced concrete structures.
文摘In today’s growing modern world environment,as human food activities are changing,it is affecting human health,thus leading to diseases like cancer.Cancer is a complex disease with many subtypes that affect human health without premature treatment and cause death.So the analysis of early diagnosis and prognosis of cancer studies can improve clinical management by analyzing various features of observa-tion,which has become necessary to classify the type in cancer research.The research needs importance to organize the risk of the cancer patients based on data analysis to predict the result of premature treatment.This paper introduces a Maximal Region-Based Candidate Feature Selection(MRCFS)for early risk diagnosing using Soft-Max Feed Forward Neural Classification(SMF2NC)to solve the above pro-blem.The predictive model is based on a different relational feature learning model,which is possessed to candidate selection to reduce the dimensionality.The redundant features are processed marginal weight rates for observing similar features’variants and the absolute value.Softmax neural hidden layers are trained using the Sigmoid Activation Function(SAF)to create the logical condition for feed-forward layers.Further,the maximal features are introduced to invite a deep neural network con-structed on the Feed Forward Recurrent Neural Network(FFRNN).The classifier produces higher classification accuracy than the previous methods and observes the cancer detection,which is recommended for early diagnosis.
