To solve the problems of deformation,micro-cracks,and residual tensile stress in laser cladding coatings,the technique of laser cladding with Fe-based memory alloy can be considered.However,the process of in-situ synt...To solve the problems of deformation,micro-cracks,and residual tensile stress in laser cladding coatings,the technique of laser cladding with Fe-based memory alloy can be considered.However,the process of in-situ synthesis of Fe-based memory alloy coatings is extremely complex.At present,there is no clear guidance scheme for its preparation process,which limits its promotion and application to some extent.Therefore,in this study,response surface methodology(RSM)was used to model the response surface between the target values and the cladding process parameters.The NSGA-2 algorithm was employed to optimize the process parameters.The results indicate that the composite optimization method consisting of RSM and the NSGA-2 algorithm can establish a more accurate model,with an error of less than 4.5%between the predicted and actual values.Based on this established model,the optimal scheme for process parameters corresponding to different target results can be rapidly obtained.The prepared coating exhibits a uniform structure,with no defects such as pores,cracks,and deformation.The surface roughness and microhardness of the coating are enhanced,the shaping quality of the coating is effectively improved,and the electrochemical corrosion performance of the coating in 3.5%NaCl solution is obviously better than that of the substrate,providing an important guide for engineering applications.展开更多
Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is...Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is cumbersome and inefficient.Thus,this work develops a multi-objective optimization method to enhance the torsional resistance of asymmetric base-isolated structures.The primary objective is to simultaneously minimize the interstory rotation of the superstructure,the rotation of the isolation layer,and the interstory displacement of the superstructure without exceeding the isolator displacement limits.A fast non-dominated sorting genetic algorithm(NSGA-Ⅱ)is employed to satisfy this optimization objective.Subsequently,the isolator arrangement,encompassing both positions and categories,is optimized according to this multi-objective optimization method.Additionally,an optimization design platform is developed to streamline the design operation.This platform integrates the input of optimization parameters,the output of optimization results,the finite element analysis,and the multi-objective optimization method proposed herein.Finally,the application of this multi-objective optimization method and its associated platform are demonstrated on two asymmetric base-isolated structures of varying heights and plan configurations.The results indicate that the optimal isolator arrangement derived from the optimization method can further improve the control over the lateral and torsional responses of asymmetric base-isolated structures compared to conventional conceptual design methods.Notably,the interstory rotation of the optimal base-isolated structure is significantly reduced,constituting only approximately 33.7%of that observed in the original base-isolated structure.The proposed platform facilitates the automatic generation of the optimal design scheme for the isolators of asymmetric base-isolated structures,offering valuable insights and guidance for the burgeoning field of intelligent civil engineering design.展开更多
A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,...A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,6 receptors.This identifies their potential threat to public health.However,our understanding of the molecular basis for the switch of receptor preference is still limited.In this study,we employed the random forest algorithm to identify the potentially key amino acid sites within hemagglutinin(HA),which are associated with the receptor binding ability of H9N2 avian influenza virus(AIV).Subsequently,these sites were further verified by receptor binding assays.A total of 12 substitutions in the HA protein(N158D,N158S,A160 N,A160D,A160T,T163I,T163V,V190T,V190A,D193 N,D193G,and N231D)were predicted to prefer binding toα-2,6 receptors.Except for the V190T substitution,the other substitutions were demonstrated to display an affinity for preferential binding toα-2,6 receptors by receptor binding assays.Especially,the A160T substitution caused a significant upregulation of immune-response genes and an increased mortality rate in mice.Our findings provide novel insights into understanding the genetic basis of receptor preference of the H9N2 AIV.展开更多
For short-term PV power prediction,based on interval type-2 Takagi-Sugeno-Kang fuzzy logic systems(IT2 TSK FLS),combined with improved grey wolf optimizer(IGWO)algorithm,an IGWO-IT2 TSK FLS method was proposed.Compare...For short-term PV power prediction,based on interval type-2 Takagi-Sugeno-Kang fuzzy logic systems(IT2 TSK FLS),combined with improved grey wolf optimizer(IGWO)algorithm,an IGWO-IT2 TSK FLS method was proposed.Compared with the type-1 TSK fuzzy logic system method,interval type-2 fuzzy sets could simultaneously model both intra-personal uncertainty and inter-personal uncertainty based on the training of the existing error back propagation(BP)algorithm,and the IGWO algorithm was used for training the model premise and consequent parameters to further improve the predictive performance of the model.By improving the gray wolf optimization algorithm,the early convergence judgment mechanism,nonlinear cosine adjustment strategy,and Levy flight strategy were introduced to improve the convergence speed of the algorithm and avoid the problem of falling into local optimum.The interval type-2 TSK FLS method based on the IGWO algorithm was applied to the real-world photovoltaic power time series forecasting instance.Under the same conditions,it was also compared with different IT2 TSK FLS methods,such as type I TSK FLS method,BP algorithm,genetic algorithm,differential evolution,particle swarm optimization,biogeography optimization,gray wolf optimization,etc.Experimental results showed that the proposed method based on IGWO algorithm outperformed other methods in performance,showing its effectiveness and application potential.展开更多
An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measur...An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measurements can not be fully resolved due to finite resolution. The proposed method adopts an auction algorithm to compute the feasible measurement-to-target assignment with unresolved measurements for solving this 2-D assignment problem. Computer simulation results demonstrate the effectiveness and feasibility of this method.展开更多
A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the chara...A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.展开更多
基金financial supports from the National Natural Science Foundation of China-Youth Project(51801076)the Provincial Colleges and Universities Natural Science Research Project of Jiangsu Province(18KJB430009)+1 种基金the Postdoctoral Research Support Project of Jiangsu Province(1601055C)the Senior Talents Research Startup of Jiangsu University(14JDG126)。
文摘To solve the problems of deformation,micro-cracks,and residual tensile stress in laser cladding coatings,the technique of laser cladding with Fe-based memory alloy can be considered.However,the process of in-situ synthesis of Fe-based memory alloy coatings is extremely complex.At present,there is no clear guidance scheme for its preparation process,which limits its promotion and application to some extent.Therefore,in this study,response surface methodology(RSM)was used to model the response surface between the target values and the cladding process parameters.The NSGA-2 algorithm was employed to optimize the process parameters.The results indicate that the composite optimization method consisting of RSM and the NSGA-2 algorithm can establish a more accurate model,with an error of less than 4.5%between the predicted and actual values.Based on this established model,the optimal scheme for process parameters corresponding to different target results can be rapidly obtained.The prepared coating exhibits a uniform structure,with no defects such as pores,cracks,and deformation.The surface roughness and microhardness of the coating are enhanced,the shaping quality of the coating is effectively improved,and the electrochemical corrosion performance of the coating in 3.5%NaCl solution is obviously better than that of the substrate,providing an important guide for engineering applications.
基金National Natural Science Foundation of China under Grant No.52278490。
文摘Finding an optimal isolator arrangement for asymmetric structures using traditional conceptual design methods that can significantly minimize torsional response while ensuring efficient horizontal seismic isolation is cumbersome and inefficient.Thus,this work develops a multi-objective optimization method to enhance the torsional resistance of asymmetric base-isolated structures.The primary objective is to simultaneously minimize the interstory rotation of the superstructure,the rotation of the isolation layer,and the interstory displacement of the superstructure without exceeding the isolator displacement limits.A fast non-dominated sorting genetic algorithm(NSGA-Ⅱ)is employed to satisfy this optimization objective.Subsequently,the isolator arrangement,encompassing both positions and categories,is optimized according to this multi-objective optimization method.Additionally,an optimization design platform is developed to streamline the design operation.This platform integrates the input of optimization parameters,the output of optimization results,the finite element analysis,and the multi-objective optimization method proposed herein.Finally,the application of this multi-objective optimization method and its associated platform are demonstrated on two asymmetric base-isolated structures of varying heights and plan configurations.The results indicate that the optimal isolator arrangement derived from the optimization method can further improve the control over the lateral and torsional responses of asymmetric base-isolated structures compared to conventional conceptual design methods.Notably,the interstory rotation of the optimal base-isolated structure is significantly reduced,constituting only approximately 33.7%of that observed in the original base-isolated structure.The proposed platform facilitates the automatic generation of the optimal design scheme for the isolators of asymmetric base-isolated structures,offering valuable insights and guidance for the burgeoning field of intelligent civil engineering design.
基金supported by the National Natural Science Foundation of China(32273037 and 32102636)the Guangdong Major Project of Basic and Applied Basic Research(2020B0301030007)+4 种基金Laboratory of Lingnan Modern Agriculture Project(NT2021007)the Guangdong Science and Technology Innovation Leading Talent Program(2019TX05N098)the 111 Center(D20008)the double first-class discipline promotion project(2023B10564003)the Department of Education of Guangdong Province(2019KZDXM004 and 2019KCXTD001).
文摘A switch from avian-typeα-2,3 to human-typeα-2,6 receptors is an essential element for the initiation of a pandemic from an avian influenza virus.Some H9N2 viruses exhibit a preference for binding to human-typeα-2,6 receptors.This identifies their potential threat to public health.However,our understanding of the molecular basis for the switch of receptor preference is still limited.In this study,we employed the random forest algorithm to identify the potentially key amino acid sites within hemagglutinin(HA),which are associated with the receptor binding ability of H9N2 avian influenza virus(AIV).Subsequently,these sites were further verified by receptor binding assays.A total of 12 substitutions in the HA protein(N158D,N158S,A160 N,A160D,A160T,T163I,T163V,V190T,V190A,D193 N,D193G,and N231D)were predicted to prefer binding toα-2,6 receptors.Except for the V190T substitution,the other substitutions were demonstrated to display an affinity for preferential binding toα-2,6 receptors by receptor binding assays.Especially,the A160T substitution caused a significant upregulation of immune-response genes and an increased mortality rate in mice.Our findings provide novel insights into understanding the genetic basis of receptor preference of the H9N2 AIV.
基金supported by National Natural Science Foundation of China(No.12172157)Key Project of Natural Science Foundation of Gansu Province(No.25JRRA150)Key Research and Development Planning Project of Gansu Province(No.23YFWA0007).
文摘For short-term PV power prediction,based on interval type-2 Takagi-Sugeno-Kang fuzzy logic systems(IT2 TSK FLS),combined with improved grey wolf optimizer(IGWO)algorithm,an IGWO-IT2 TSK FLS method was proposed.Compared with the type-1 TSK fuzzy logic system method,interval type-2 fuzzy sets could simultaneously model both intra-personal uncertainty and inter-personal uncertainty based on the training of the existing error back propagation(BP)algorithm,and the IGWO algorithm was used for training the model premise and consequent parameters to further improve the predictive performance of the model.By improving the gray wolf optimization algorithm,the early convergence judgment mechanism,nonlinear cosine adjustment strategy,and Levy flight strategy were introduced to improve the convergence speed of the algorithm and avoid the problem of falling into local optimum.The interval type-2 TSK FLS method based on the IGWO algorithm was applied to the real-world photovoltaic power time series forecasting instance.Under the same conditions,it was also compared with different IT2 TSK FLS methods,such as type I TSK FLS method,BP algorithm,genetic algorithm,differential evolution,particle swarm optimization,biogeography optimization,gray wolf optimization,etc.Experimental results showed that the proposed method based on IGWO algorithm outperformed other methods in performance,showing its effectiveness and application potential.
文摘An extension of 2-D assignment approach is proposed for measurement-to-target association for improving multiple targets vector miss distance measurement accuracy. When the multiple targets move so closely, the measurements can not be fully resolved due to finite resolution. The proposed method adopts an auction algorithm to compute the feasible measurement-to-target assignment with unresolved measurements for solving this 2-D assignment problem. Computer simulation results demonstrate the effectiveness and feasibility of this method.
基金This project was supported by Science and Technology Research Emphasis Fund of Ministry of Education(204010) .
文摘A new image thresholding method is introduced, which is based on 2-D histgram and minimizing the measures of fuzziness of an input image. A new definition of fuzzy membership function is proposed, it denotes the characteristic relationship between the gray level of each pixel and the average value of its neighborhood. When the threshold is not located at the obvious and deep valley of the histgram, genetic algorithm is devoted to the problem of selecting the appropriate threshold value. The experimental results indicate that the proposed method has good performance.
