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Multiobjective Optimization of Simulated Moving Bed by Tissue P System 被引量:7
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作者 黄亮 孙磊 +1 位作者 王宁 金晓明 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2007年第5期683-690,共8页
The binaphthol enantiomers separation process using simulation moving bed technology is simulated with the true moving bed approach (TMB). In order to systematically optimize the process with multiple productive obj... The binaphthol enantiomers separation process using simulation moving bed technology is simulated with the true moving bed approach (TMB). In order to systematically optimize the process with multiple productive objectives, this article develops a variant of tissue P system (TPS). Inspired by general tissue P systems, the special TPS has a tissue-like structure with several membranes. The key rules of each membrane are the communication rule and mutation rule. These characteristics contribute to the diversity of the population, the conquest of the multimodal of objective function, and the convergence of algorithm. The results of comparison with a popular algorithm——the non-dominated sorting genetic algorithm 2(NSGA-2) illustrate that the new algorithm has satisfactory performance. Using the algorithm, this study maximizes synchronously several conflicting objectives, purities of different products, and productivity. 展开更多
关键词 simulated moving bed tissue p systems multiobjective optimization pareto optimality evolutionary algorithm binaphthol enantiomers separation process
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Hyperspectral Image Based Interpretable Feature Clustering Algorithm
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作者 Yaming Kang PeishunYe +1 位作者 Yuxiu Bai Shi Qiu 《Computers, Materials & Continua》 SCIE EI 2024年第5期2151-2168,共18页
Hyperspectral imagery encompasses spectral and spatial dimensions,reflecting the material properties of objects.Its application proves crucial in search and rescue,concealed target identification,and crop growth analy... Hyperspectral imagery encompasses spectral and spatial dimensions,reflecting the material properties of objects.Its application proves crucial in search and rescue,concealed target identification,and crop growth analysis.Clustering is an important method of hyperspectral analysis.The vast data volume of hyperspectral imagery,coupled with redundant information,poses significant challenges in swiftly and accurately extracting features for subsequent analysis.The current hyperspectral feature clustering methods,which are mostly studied from space or spectrum,do not have strong interpretability,resulting in poor comprehensibility of the algorithm.So,this research introduces a feature clustering algorithm for hyperspectral imagery from an interpretability perspective.It commences with a simulated perception process,proposing an interpretable band selection algorithm to reduce data dimensions.Following this,amulti-dimensional clustering algorithm,rooted in fuzzy and kernel clustering,is developed to highlight intra-class similarities and inter-class differences.An optimized P systemis then introduced to enhance computational efficiency.This system coordinates all cells within a mapping space to compute optimal cluster centers,facilitating parallel computation.This approach diminishes sensitivity to initial cluster centers and augments global search capabilities,thus preventing entrapment in local minima and enhancing clustering performance.Experiments conducted on 300 datasets,comprising both real and simulated data.The results show that the average accuracy(ACC)of the proposed algorithm is 0.86 and the combination measure(CM)is 0.81. 展开更多
关键词 HYpERSpECTRAL fuzzy clustering tissue p system band selection interpretable
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A uniform solution to the independent set problem through tissue P systems with cell separation
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作者 Xingyi ZHANG Xiangxiang ZENG +1 位作者 Bin LUO Zheng ZHANG 《Frontiers of Computer Science》 SCIE EI CSCD 2012年第4期477-488,共12页
Membrane computing is an emergent branch of natural computing, which is inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order st... Membrane computing is an emergent branch of natural computing, which is inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. Tissue P systems are a class of the most investigated computing mod- els in the framework of membrane computing, especially in the aspect of efficiency. To generate an exponential resource in a polynomial time, cell separation is incorporated into such systems, thus obtaining so called tissue P systems with cell separation. In this work, we exploit the computational efficiency of this model and construct a uniform family of such tissue P systems for solving the independent set problem, a well-known NP-complete problem, by which an efficient so- lution can be obtained in polynomial time. 展开更多
关键词 membrane computing tissue p system cell sep- aration independent set problem
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