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第2.届中国控制与决策会议

作者： chao zhao, aimin an college of chemistry and chemical engineering, {2. University,{2.,350108,p.r.china. qiaolin xu faculty of school of electrical engineering and information engineering, lanzhou University of technology, lanzhou,gansu 730050, china

The determination of the optimal model parameters for kinetic systems development of kinetic models is a time consuming, iterative process [1]. In this paper, we presented a novel hybrid Differential Evolution （DE） algorithm for solving kinetic parameter estimation problems based on the Differential Evolution technique together with a local search strategy. By combining the merits of DE with Gauss-Newton method, the proposed hybrid approach employs a DE algorithm for identifying promising regions of the solution space followed by use of Gauss-Newton method to determine the optimum in the identified regions. The computational results indicate that the global searching ability and the convergence speed of this hybrid algorithm are significantly improved. Additionally, study of kinetic model parameters for an irreversible, first-order reaction system was carried out to test the applicability of the proposed algorithm. The suggested method can be used to estimate suitable values for the model parameters of a complex mathematical model.

关键词： parameter estimation Kinetic models Hybrid Differential Evolution (HDE) Guass-Newton method

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A robust Adaptive Hybrid Genetic Simulated Annealing Algorithm for the global optimization of multimodal functions

A Robust Adaptive Hybrid Genetic Simulated Annealing Algorit...

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2.11 Chinese Control and Decision Conference（CCDC）

作者： qiaoling xu and chao zhao are with faculty of college of chemistry and chemical engineering,fuzhou University,fuzhou,350108,p.r.china.Gongwang Zhang is with postgraduate of college of chemistry and chemical engineering,fuzhou University,fuzhou,350108,p.r.china.aimin An is with faculty of school of electrical engineering and information engineering,lanzhou University of technology,lanzhou,gansu 730050,china.

In this paper we presented a novel hybrid genetic algorithm for solving NLp problems based on combining the Genetic algorithm and Simulated annealing,together with a local search *** proposed hybrid approach combines the merits of genetic algorithm （GA） with simulated annealing （SA） to construct a more effficient genetic simulated annealing （GSA） algorithm for global search,which could well maintain the population diversity in GA evolution without becoming easily trapped in local *** iterative hill climbing （IHC） method as a local search technique is incorporated into GSA loop to speed up the convergence of the *** addition,a self-adaptive hybrid mechanism is developed to maintain a tradeoff between the global and local optimizer searching then to efficiently locate quality solution to complex optimization *** computational results indicate that the global searching ability and the convergence speed of this hybrid algorithm are significantly *** well-known benchmark functions are utilized to test the applicability of the proposed algorithm.

关键词： genetic simulated annealing iterative hill climbing (IHC) method adaptive scheme global optimization

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A Novel Hybrid Genetic Algorithm for HEN Synthesis and its Industrial Application

A Novel Hybrid Genetic Algorithm for HEN Synthesis and its I...

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2.11 Chinese Control and Decision Conference（CCDC）

作者： qiaoling xu,chao zhao are with faculty of college of chemistry and chemical engineering,fuzhou University,fuzhou,350108,p.r.china.aimin An is with faculty of school of electrical engineering and information engineering,lanzhou University of technology,lanzhou gansu 730050,china.Defeng Zhang is with faculty of school of Mechanical engineering,Nanjing University of Science and technology,Nanjing,p.r.china.

In this paper we look at a new hybrid Genetic Algorithm （HGA） based on genetic simulated annealing （GSA） algorithm for solving heat exchanger network synthesis （HENS） problems with Mixed Integer Nonlinear programming （MINLp） *** order to efficiently locate quality solution to complex optimization problem,a self-adaptive mechanism is developed to maintain a tradeoff between the global and local *** computational results indicate that the global searching ability and the convergence speed of this hybrid algorithm are significantly ***,the proposed algorithm is tailored to find optimum solution to industrial HENS problem,The results show that the proposed approach could provide designers with a least-cost HEN with less computational cost comparing with other optimization methods.

关键词： genetic simulated annealing iterative hill climbing (IHC) method adaptive scheme Heat exchanger network synthesis

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Nucleic acids analysis

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Science china chemistry 2021年第2期64卷 171-203页

作者： Yongxi zhao Xiaolei Zuo Qian Li Feng Chen Yan-ru Chen Jinqi Deng Da Han Changlong Hao Fujian Huang Yanyi Huang Guoliang Ke Hua Kuang Fan Li Jiang Li Min Li Na Li Zhenyu Lin Dingbin Liu Juewen Liu Libing Liu Xiaoguo Liu Chunhua Lu Fang Luo Xiuhai Mao Jiashu Sun Bo Tang Fei Wang Jianbin Wang Lihua Wang Shu Wang Lingling Wu Zai-Sheng Wu Fan Xia Chuanlai xu Yang Yang Bi-Feng Yuan Quan Yuan chao Zhang Zhi Zhu chaoyong Yang Xiao-Bing Zhang Huanghao Yang Weihong Tan Chunhai Fan Institute of Analytical chemistry and Instrument for Life Science The Key Laboratory of Biomedical Information Engineering of Ministry of EducationSchool of Life Science and TechnologyXi’an Jiaotong UniversityXi’an 710049China Institute of Molecular Medicine Shanghai Key Laboratory for Nucleic Acid Chemistry and NanomedicineRenji HospitalSchool of MedicineShanghai Jiao Tong UniversityShanghai 200127China school of chemistry and {2. engineering Frontiers Science Center for Transformative MoleculesInstitute of Translational MedicineShanghai Jiao Tong UniversityShanghai 200240China Cancer Metastasis Alert and prevention Center Fujian Provincial Key Laboratory of Cancer Metastasis Chemoprevention and ChemotherapyState Key Laboratory of Photocatalysis on Energy and EnvironmentCollege of ChemistryFuzhou UniversityFuzhou 350108China CAS Key Laboratory of Standardization and Measurement for Nanotechnology CAS Center for Excellence in NanoscienceNational Center for Nanoscience and TechnologyBeijing 100190China State Key Lab of Food Science and technology International Joint Research Laboratory for Biointerface and BiodetectionSchool of Food Science and TechnologyJiangnan UniversityWuxi 214122China faculty of Materials Science and chemistry Engineering Research Center of Nano-Geomaterials of Ministry of EducationChina University of GeosciencesWuhan 430074China college of chemistry and Molecular {2. Biomedical Pioneering Innovation Center(BIOPIC)Beijing Advanced Innovation Center for Genomics(ICG)Peking-Tsinghua Center for Life SciencesPeking UniversityBeijing 100871China State Key Laboratory of Chemo/Biosensing and Chemometrics College of Chemistry and Chemical EngineeringHunan UniversityChangsha 410082China Division of physical Biology CAS Key Laboratory of Interfacial Physics and TechnologyShanghai Institute of Applied PhysicsChinese Academy of SciencesShanghai 201800China Bioimaging Center Shanghai Synchrotron Radiation FacilityZhangjiang LaboratoryShanghai Advanced

Nucleic acids are natural biopolymers of nucleotides that store, encode, transmit and express genetic information, which play central roles in diverse cellular events and diseases in living things. The analysis of nucleic acids and nucleic acids-based analysis have been widely applied in biological studies, clinical diagnosis, environmental analysis, food safety and forensic *** the past decades, the field of nucleic acids analysis has been rapidly advancing with many technological *** this review, we focus on the methods developed for analyzing nucleic acids, nucleic acids-based analysis, device for nucleic acids analysis, and applications of nucleic acids analysis. The representative strategies for the development of new nucleic acids analysis in this field are summarized, and key advantages and possible limitations are discussed. Finally, a brief perspective on existing challenges and further research development is provided.

关键词： nucleic acids analysis signal amplification DNA nanotechnology aptamer biosensing

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