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Multi-objective particle swarm optimization by fusing multiple strategies
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作者 XU Zhenxing ZHU Shuiran 《Journal of Measurement Science and Instrumentation》 CAS CSCD 2022年第3期284-299,共16页
To improve the convergence and distributivity of multi-objective particle swarm optimization,we propose a method for multi-objective particle swarm optimization by fusing multiple strategies(MOPSO-MS),which includes t... To improve the convergence and distributivity of multi-objective particle swarm optimization,we propose a method for multi-objective particle swarm optimization by fusing multiple strategies(MOPSO-MS),which includes three strategies.Firstly,the average crowding distance method is proposed,which takes into account the influence of individuals on the crowding distance and reduces the algorithm’s time complexity and computational cost,ensuring efficient external archive maintenance and improving the algorithm’s distribution.Secondly,the algorithm utilizes particle difference to guide adaptive inertia weights.In this way,the degree of disparity between a particle’s historical optimum and the population’s global optimum is used to determine the value of w.With different degrees of disparity,the size of w is adjusted nonlinearly,improving the algorithm’s convergence.Finally,the algorithm is designed to control the search direction by hierarchically selecting the globally optimal policy,which can avoid a single search direction and eliminate the lack of a random search direction,making the selection of the global optimal position more objective and comprehensive,and further improving the convergence of the algorithm.The MOPSO-MS is tested against seven other algorithms on the ZDT and DTLZ test functions,and the results show that the MOPSO-MS has significant advantages in terms of convergence and distributivity. 展开更多
关键词 multi-objective particle swarm optimization(MOPSO) spatially crowding congestion distance differential guidance weight hierarchical selection of global optimum
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Isolation of hemoglobin with metal–organic frameworks Y(BTC)(H_2O)_6 被引量:1
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作者 Yang Shu Ying Meng +1 位作者 Ming-Li Chen Jian-Hua Wang 《Chinese Chemical Letters》 SCIE CAS CSCD 2015年第12期1460-1464,共5页
The hierarchical metal-organic frameworks(MOFs),such as Y(BTC)(H_2O)_6,are prepared with yttrium nitrate and benzene-1,3,5-tricarboxylic acid at room temperature.The product is characterized by Fourier transform... The hierarchical metal-organic frameworks(MOFs),such as Y(BTC)(H_2O)_6,are prepared with yttrium nitrate and benzene-1,3,5-tricarboxylic acid at room temperature.The product is characterized by Fourier transform infrared(FT-IR),X-ray diffraction(XRD),scanning electron microscopy(SEM)and thermogravimetric analysis(TGA).The Y(BTC)(H_2O)_6 particles are sufficiently rigid for performing solid phase extraction and they exhibit favorable selectivity toward the adsorption of hemoglobin.The adsorption behavior of hemoglobin onto the Y(BTC)(H_2O)_6 fits the Langmuir adsorption model with a theoretical adsorption capacity of 555.6 mg g 1.An adsorption efficiency of 87.7%for 100μg mL 1hemoglobin in 1 mL sample solution(at pH 6.0)is achieved with 0.40 mg Y(BTC)(H20)6.77.3%of the retained hemoglobin is readily recovered using a 0.5%(m/v)SDS solution as the stripping reagent.Circular dichroism spectra indicated that the conformation of hemoglobin is maintained during the adsorption-desorption process.The MOFs material is applied for the isolation of hemoglobin from human blood and the purity of the obtained hemoglobin is further verified by sodium dodecyl sulfate polyacrylamide gel electrophoresis(SDS-PAGE). 展开更多
关键词 hemoglobin BTC H2O hierarchical selectivity nitrate desorption verified dodecyl polyacrylamide
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