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ASYMPTOTIC APPROXIMATION METHOD AND ITS CONVERGENCE ON SEMI-INFINITE PROGRAMMING 被引量:3
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作者 万仲平 王先甲 +1 位作者 何炬林 贾世会 《Acta Mathematica Scientia》 SCIE CSCD 2006年第1期17-24,共8页
The aim of this article is to discuss an asymptotic approximation model and its convergence for the minimax semi-infinite programming problem. An asymptotic surrogate constraints method for the minimax semi-infinite p... The aim of this article is to discuss an asymptotic approximation model and its convergence for the minimax semi-infinite programming problem. An asymptotic surrogate constraints method for the minimax semi-infinite programming problem is presented by making use of two general discrete approximation methods. Simultaneously, the consistence and the epi-convergence of the asymptotic approximation problem are discussed. 展开更多
关键词 semi-infinite programming asymptotic approximation CONVERGENCE
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The Optimality Conditions for Multiobjective Semi-infinite Programming Involving Generalized Unified (C, α, p, d)-convexity
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作者 ZHANG Qing-xiang ZHANG Yong-zhan 《Chinese Quarterly Journal of Mathematics》 CSCD 2013年第2期241-249,共9页
The definition of generalized unified (C, α, ρ, d)-convex function is given. The concepts of generalized unified (C, α, ρ, d)-quasiconvexity, generalized unified (C, α, ρ, d)-pseudoconvexity and generalized unif... The definition of generalized unified (C, α, ρ, d)-convex function is given. The concepts of generalized unified (C, α, ρ, d)-quasiconvexity, generalized unified (C, α, ρ, d)-pseudoconvexity and generalized unified (C, α, ρ, d)-strictly pseudoconvex functions are presented. The sufficient optimality conditions for multiobjective nonsmooth semi-infinite programming are obtained involving these generalized convexity lastly. 展开更多
关键词 generalized convexity multiobjective semi-infinite programming efficient solution optimality conditions
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ON SUFFICIENCY AND DUALITY OF SOLUTIONS FOR QUASI B_s-INVEX SEMI-INFINITE PROGRAMMING 被引量:1
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作者 张庆祥 《Numerical Mathematics A Journal of Chinese Universities(English Series)》 SCIE 2001年第1期37-44,共8页
A class of functions called quasi B s invex and pseudo B s invex functions are introduced by using the concept of symmetric gradient. The examples of quasi B s invex and pseudo B s invex functions are given. The suffi... A class of functions called quasi B s invex and pseudo B s invex functions are introduced by using the concept of symmetric gradient. The examples of quasi B s invex and pseudo B s invex functions are given. The sufficient optimality conditions and Mond Weir type duality results are obtained for a nondifferentiable nonlinear semi infinite programming problem involving quasi B s invex and pseudo B s invex functions. 展开更多
关键词 INVEX quasi B s invex and pseudo B s invex sufficient optimality DUALITY semi infinite programming.
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ASYMPTOTIC SURROGATE CONSTRAINT METHOD AND ITS CONVERGENCE FOR A CLASS OF SEMI-INFINITE PROGRAMMING 被引量:2
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作者 Wan Zhongping\ Wu Guoming 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 1999年第4期485-491,共7页
A class of constrained semi\|infinite minimax problem is transformed into a simple constrained problem, by means of discretization decomposition and maximum entropy method, making use of surrogate constraint. The pa... A class of constrained semi\|infinite minimax problem is transformed into a simple constrained problem, by means of discretization decomposition and maximum entropy method, making use of surrogate constraint. The paper deals with the convergence of this asymptotic approach method. 展开更多
关键词 Sem i-infinite m inim ax program m ing discretization decom position m ethod m axim um en-tropy m ethod surrogate constraint CONVERGENCE
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Optimality Conditions and Duality for Nondifferentiable Multiobjective Semi-Infinite Programming Problems with Generalized(C,α,ρ,d)-Convexity 被引量:6
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作者 MISHRA Shashi Kant JAISWAL Monika HOAI AN Le Thi 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2015年第1期47-59,共13页
This paper obtains sufficient optimality conditions for a nonlinear nondifferentiable multiobjective semi-infinite programming problem involving generalized(C,α,ρ,d)-convex functions.The authors formulate Mond-Weir-... This paper obtains sufficient optimality conditions for a nonlinear nondifferentiable multiobjective semi-infinite programming problem involving generalized(C,α,ρ,d)-convex functions.The authors formulate Mond-Weir-type dual model for the nonlinear nondifferentiable multiobjective semiinfinite programming problem and establish weak,strong and strict converse duality theorems relating the primal and the dual problems. 展开更多
关键词 DUALITY generalized convexity optimality conditions semi-infinite programming.
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Optimality Conditions of Approximate Solutions for Nonsmooth Semi-infinite Programming Problems 被引量:6
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作者 Xian-Jun Long Yi-Bin Xiao Nan-Jing Huang 《Journal of the Operations Research Society of China》 EI CSCD 2018年第2期289-299,共11页
In this paper,we study optimality conditions of approximate solutions for nonsmooth semi-infinite programming problems.Three new classes of functions,namelyε-pseudoconvex functions of type I and type II andε-quasico... In this paper,we study optimality conditions of approximate solutions for nonsmooth semi-infinite programming problems.Three new classes of functions,namelyε-pseudoconvex functions of type I and type II andε-quasiconvex functions are introduced,respectively.By utilizing these new concepts,sufficient optimality conditions of approximate solutions for the nonsmooth semi-infinite programming problem are established.Some examples are also presented.The results obtained in this paper improve the corresponding results of Son et al.(J Optim Theory Appl 141:389–409,2009). 展开更多
关键词 Nonsmooth semi-infinite programming problem Optimality condition Approximate solution Generalized pseudoconvexity
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An entropy based central cutting plane algorithm for convex min-max semi-infinite programming problems 被引量:2
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作者 ZHANG LiPing FANG Shu-Cherng WU Soon-Yi 《Science China Mathematics》 SCIE 2013年第1期201-211,共11页
In this paper,we present a central cutting plane algorithm for solving convex min-max semi-infinite programming problems.Because the objective function here is non-differentiable,we apply a smoothing technique to the ... In this paper,we present a central cutting plane algorithm for solving convex min-max semi-infinite programming problems.Because the objective function here is non-differentiable,we apply a smoothing technique to the considered problem and develop an algorithm based on the entropy function.It is shown that the global convergence of the proposed algorithm can be obtained under weaker conditions.Some numerical results are presented to show the potential of the proposed algorithm. 展开更多
关键词 semi-infinite programming min-max problem central cutting plane ENTROPY
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Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications 被引量:4
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作者 Ding Wang Ning Gao +2 位作者 Derong Liu Jinna Li Frank L.Lewis 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期18-36,共19页
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ... Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence. 展开更多
关键词 Adaptive dynamic programming(ADP) advanced control complex environment data-driven control event-triggered design intelligent control neural networks nonlinear systems optimal control reinforcement learning(RL)
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GLOBAL CONVERGENCE OF A CLASS OF SMOOTH PENALTY METHODS FOR SEMI-INFINITE PROGRAMMING
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作者 Changyu WANG Haiyan ZHANG Fang LIU 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2011年第4期769-783,共15页
For the semi-infinite programming (SIP) problem, the authors first convert it into an equivalent nonlinear programming problem with only one inequality constraint by using an integral function, and then propose a sm... For the semi-infinite programming (SIP) problem, the authors first convert it into an equivalent nonlinear programming problem with only one inequality constraint by using an integral function, and then propose a smooth penalty method based on a class of smooth functions. The main feature of this method is that the global solution of the penalty function is not necessarily solved at each iteration, and under mild assumptions, the method is always feasible and efficient when the evaluation of the integral function is not very expensive. The global convergence property is obtained in the absence of any constraint qualifications, that is, any accumulation point of the sequence generated by the algorithm is the solution of the SIP. Moreover, the authors show a perturbation theorem of the method and obtain several interesting results. Furthermore, the authors show that all iterative points remain feasible after a finite number of iterations under the Mangasarian-Fromovitz constraint qualification. Finally, numerical results are given. 展开更多
关键词 Global convergence semi-infinite programming smooth penalty function perturbation function.
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Adaptive Optimal Discrete-Time Output-Feedback Using an Internal Model Principle and Adaptive Dynamic Programming 被引量:1
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作者 Zhongyang Wang Youqing Wang Zdzisław Kowalczuk 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期131-140,共10页
In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed metho... In order to address the output feedback issue for linear discrete-time systems, this work suggests a brand-new adaptive dynamic programming(ADP) technique based on the internal model principle(IMP). The proposed method, termed as IMP-ADP, does not require complete state feedback-merely the measurement of input and output data. More specifically, based on the IMP, the output control problem can first be converted into a stabilization problem. We then design an observer to reproduce the full state of the system by measuring the inputs and outputs. Moreover, this technique includes both a policy iteration algorithm and a value iteration algorithm to determine the optimal feedback gain without using a dynamic system model. It is important that with this concept one does not need to solve the regulator equation. Finally, this control method was tested on an inverter system of grid-connected LCLs to demonstrate that the proposed method provides the desired performance in terms of both tracking and disturbance rejection. 展开更多
关键词 Adaptive dynamic programming(ADP) internal model principle(IMP) output feedback problem policy iteration(PI) value iteration(VI)
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Data-driven prediction of dimensionless quantities for semi-infinite target penetration by integrating machine-learning and feature selection methods
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作者 Qingqing Chen Xinyu Zhang +2 位作者 Zhiyong Wang Jie Zhang Zhihua Wang 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第10期105-124,共20页
This study employs a data-driven methodology that embeds the principle of dimensional invariance into an artificial neural network to automatically identify dominant dimensionless quantities in the penetration of rod ... This study employs a data-driven methodology that embeds the principle of dimensional invariance into an artificial neural network to automatically identify dominant dimensionless quantities in the penetration of rod projectiles into semi-infinite metal targets from experimental measurements.The derived mathematical expressions of dimensionless quantities are simplified by the examination of the exponent matrix and coupling relationships between feature variables.As a physics-based dimension reduction methodology,this way reduces high-dimensional parameter spaces to descriptions involving only a few physically interpretable dimensionless quantities in penetrating cases.Then the relative importance of various dimensionless feature variables on the penetration efficiencies for four impacting conditions is evaluated through feature selection engineering.The results indicate that the selected critical dimensionless feature variables by this synergistic method,without referring to the complex theoretical equations and aiding in the detailed knowledge of penetration mechanics,are in accordance with those reported in the reference.Lastly,the determined dimensionless quantities can be efficiently applied to conduct semi-empirical analysis for the specific penetrating case,and the reliability of regression functions is validated. 展开更多
关键词 Data-driven dimensional analysis PENETRATION semi-infinite metal target Dimensionless numbers Feature selection
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In vivo astrocyte reprogramming following spinal cord injury
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作者 Yannick N.Gerber Florence E.Perrin 《Neural Regeneration Research》 SCIE CAS CSCD 2024年第3期487-488,共2页
Harmful and helpful roles of astrocytes in spinal cord injury(SCI):SCI induce gradable sensory,motor and autonomic impairments that correlate with the lesion severity and the rostro-caudal location of the injury site.... Harmful and helpful roles of astrocytes in spinal cord injury(SCI):SCI induce gradable sensory,motor and autonomic impairments that correlate with the lesion severity and the rostro-caudal location of the injury site.The absence of spontaneous axonal regeneration after injury results from neuron-intrinsic and neuron-extrinsic parameters.Indeed,not only adult neurons display limited capability to regrow axons but also the injury environment contains inhibitors to axonal regeneration and a lack of growth-promoting factors.Amongst other cell populations that respond to the lesion,reactive astrocytes were first considered as only detrimental to spontaneous axonal regeneration.Indeed,astrocytes. 展开更多
关键词 INJURY IMPAIRMENT programming
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Transcriptional reprogramming during human osteoclast differentiation identifies regulators of osteoclast activity
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作者 Morten S.Hansen Kaja Madsen +6 位作者 Maria Price Kent Søe Yasunori Omata Mario M.Zaiss Caroline M.Gorvin Morten Frost Alexander Rauch 《Bone Research》 SCIE CAS CSCD 2024年第1期180-198,共19页
Enhanced osteoclastogenesis and osteoclast activity contribute to the development of osteoporosis,which is characterized by increased bone resorption and inadequate bone formation.As novel antiosteoporotic therapeutic... Enhanced osteoclastogenesis and osteoclast activity contribute to the development of osteoporosis,which is characterized by increased bone resorption and inadequate bone formation.As novel antiosteoporotic therapeutics are needed,understanding the genetic regulation of human osteoclastogenesis could help identify potential treatment targets.This study aimed to provide an overview of transcriptional reprogramming during human osteoclast differentiation.Osteoclasts were differentiated from CD14+monocytes from eight female donors.RNA sequencing during differentiation revealed 8980 differentially expressed genes grouped into eight temporal patterns conserved across donors.These patterns revealed distinct molecular functions associated with postmenopausal osteoporosis susceptibility genes based on RNA from iliac crest biopsies and bone mineral density SNPs.Network analyses revealed mutual dependencies between temporal expression patterns and provided insight into subtype-specific transcriptional networks.The donor-specific expression patterns revealed genes at the monocyte stage,such as filamin B(FLNB)and oxidized low-density lipoprotein receptor 1(OLR1,encoding LOX-1),that are predictive of the resorptive activity of mature osteoclasts.The expression of differentially expressed G-protein coupled receptors was strong during osteoclast differentiation,and these receptors are associated with bone mineral density SNPs,suggesting that they play a pivotal role in osteoclast differentiation and activity.The regulatory effects of three differentially expressed G-protein coupled receptors were exemplified by in vitro pharmacological modulation of complement 5 A receptor 1(C5AR1),somatostatin receptor 2(SSTR2),and free fatty acid receptor 4(FFAR4/GPR120).Activating C5AR1 enhanced osteoclast formation,while activating SSTR2 decreased the resorptive activity of mature osteoclasts,and activating FFAR4 decreased both the number and resorptive activity of mature osteoclasts.In conclusion,we report the occurrence of transcriptional reprogramming during human osteoclast differentiation and identified SSTR2 and FFAR4 as antiresorptive G-protein coupled receptors and FLNB and LOX-1 as potential molecular markers of osteoclast activity.These data can help future investigations identify molecular regulators of osteoclast differentiation and activity and provide the basis for novel antiosteoporotic targets. 展开更多
关键词 OSTEOCLAST programming identif
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Metabolic reprogramming in skeletal cell differentiation
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作者 Joshua C.Bertels Guangxu He Fanxin Long 《Bone Research》 SCIE CAS CSCD 2024年第3期539-554,共16页
The human skeleton is a multifunctional organ made up of multiple cell types working in concert to maintain bone and mineral homeostasis and to perform critical mechanical and endocrine functions.From the beginning st... The human skeleton is a multifunctional organ made up of multiple cell types working in concert to maintain bone and mineral homeostasis and to perform critical mechanical and endocrine functions.From the beginning steps of chondrogenesis that prefigures most of the skeleton,to the rapid bone accrual during skeletal growth,followed by bone remodeling of the mature skeleton,cell differentiation is integral to skeletal health. 展开更多
关键词 FUNCTIONS SKELETON programming
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Glia-to-neuron reprogramming to the rescue?
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作者 Jack W.Hickmott Cindi M.Morshead 《Neural Regeneration Research》 SCIE CAS 2025年第5期1395-1396,共2页
Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative medicine.The brea kth rough discovery that induced pluripotent stem cells c... Over the last two decades,the dogma that cell fate is immutable has been increasingly challenged,with important implications for regenerative medicine.The brea kth rough discovery that induced pluripotent stem cells could be generated from adult mouse fibroblasts is powerful proof that cell fate can be changed.An exciting extension of the discovery of cell fate impermanence is the direct cellular reprogram ming hypothesis-that terminally differentiated cells can be reprogrammed into other adult cell fates without first passing through a stem cell state. 展开更多
关键词 programming PASSING proof
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Neurocircuit regeneration by extracellular matrix reprogramming
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作者 Shengzhang Su Ian N.Levasseur Kimberly M.Alonge 《Neural Regeneration Research》 SCIE CAS 2025年第8期2300-2301,共2页
The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functio... The brain's extracellular matrix(ECM),which is comprised of protein and glycosaminoglycan(GAG)scaffolds,constitutes 20%-40% of the human brain and is considered one of the largest influencers on brain cell functioning(Soles et al.,2023).Synthesized by neural and glial cells,the brain's ECM regulates a myriad of homeostatic cellular processes,including neuronal plasticity and firing(Miyata et al.,2012),cation buffering(Moraws ki et al.,2015),and glia-neuron interactions(Anderson et al.,2016).Considering the diversity of functions,dynamic remodeling of the brain's ECM indicates that this understudied medium is an active participant in both normal physiology and neurological diseases. 展开更多
关键词 MATRIX programming
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Improved Unit Commitment with Accurate Dynamic Scenarios Clustering Based on Multi-Parametric Programming and Benders Decomposition
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作者 Zhang Zhi Haiyu Huang +6 位作者 Wei Xiong Yijia Zhou Mingyu Yan Shaolian Xia Baofeng Jiang Renbin Su Xichen Tian 《Energy Engineering》 EI 2024年第6期1557-1576,共20页
Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenario... Stochastic unit commitment is one of the most powerful methods to address uncertainty. However, the existingscenario clustering technique for stochastic unit commitment cannot accurately select representative scenarios,which threatens the robustness of stochastic unit commitment and hinders its application. This paper providesa stochastic unit commitment with dynamic scenario clustering based on multi-parametric programming andBenders decomposition. The stochastic unit commitment is solved via the Benders decomposition, which decouplesthe primal problem into the master problem and two types of subproblems. In the master problem, the committedgenerator is determined, while the feasibility and optimality of generator output are checked in these twosubproblems. Scenarios are dynamically clustered during the subproblem solution process through the multiparametric programming with respect to the solution of the master problem. In other words, multiple scenariosare clustered into several representative scenarios after the subproblem is solved, and the Benders cut obtainedby the representative scenario is generated for the master problem. Different from the conventional stochasticunit commitment, the proposed approach integrates scenario clustering into the Benders decomposition solutionprocess. Such a clustering approach could accurately cluster representative scenarios that have impacts on theunit commitment. The proposed method is tested on a 6-bus system and the modified IEEE 118-bus system.Numerical results illustrate the effectiveness of the proposed method in clustering scenarios. Compared withthe conventional clustering method, the proposed method can accurately select representative scenarios whilemitigating computational burden, thus guaranteeing the robustness of unit commitment. 展开更多
关键词 Stochastic programming unit commitment scenarios clustering Benders decomposition multi-parametric programming
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Combining reinforcement learning with mathematical programming:An approach for optimal design of heat exchanger networks
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作者 Hui Tan Xiaodong Hong +4 位作者 Zuwei Liao Jingyuan Sun Yao Yang Jingdai Wang Yongrong Yang 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2024年第5期63-71,共9页
Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinea... Heat integration is important for energy-saving in the process industry.It is linked to the persistently challenging task of optimal design of heat exchanger networks(HEN).Due to the inherent highly nonconvex nonlinear and combinatorial nature of the HEN problem,it is not easy to find solutions of high quality for large-scale problems.The reinforcement learning(RL)method,which learns strategies through ongoing exploration and exploitation,reveals advantages in such area.However,due to the complexity of the HEN design problem,the RL method for HEN should be dedicated and designed.A hybrid strategy combining RL with mathematical programming is proposed to take better advantage of both methods.An insightful state representation of the HEN structure as well as a customized reward function is introduced.A Q-learning algorithm is applied to update the HEN structure using theε-greedy strategy.Better results are obtained from three literature cases of different scales. 展开更多
关键词 Heat exchanger network Reinforcement learning Mathematical programming Process design
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Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming
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作者 Hongbo Zhao Shaojun Li +3 位作者 Xiaoyu Zang Xinyi Liu Lin Zhang Jiaolong Ren 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第3期895-908,共14页
Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conv... Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems. 展开更多
关键词 Geological engineering Geotechnical engineering Inverse analysis Uncertainty quantification Probabilistic programming
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Rapid Prototype Development Approach for Genetic Programming
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作者 Pei He Lei Zhang 《Journal of Computer and Communications》 2024年第2期67-79,共13页
Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of ... Genetic Programming (GP) is an important approach to deal with complex problem analysis and modeling, and has been applied in a wide range of areas. The development of GP involves various aspects, including design of genetic operators, evolutionary controls and implementations of heuristic strategy, evaluations and other mechanisms. When designing genetic operators, it is necessary to consider the possible limitations of encoding methods of individuals. And when selecting evolutionary control strategies, it is also necessary to balance search efficiency and diversity based on representation characteristics as well as the problem itself. More importantly, all of these matters, among others, have to be implemented through tedious coding work. Therefore, GP development is both complex and time-consuming. To overcome some of these difficulties that hinder the enhancement of GP development efficiency, we explore the feasibility of mutual assistance among GP variants, and then propose a rapid GP prototyping development method based on πGrammatical Evolution (πGE). It is demonstrated through regression analysis experiments that not only is this method beneficial for the GP developers to get rid of some tedious implementations, but also enables them to concentrate on the essence of the referred problem, such as individual representation, decoding means and evaluation. Additionally, it provides new insights into the roles of individual delineations in phenotypes and semantic research of individuals. 展开更多
关键词 Genetic programming Grammatical Evolution Gene Expression programming Regression Analysis Mathematical Modeling Rapid Prototype Development
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