- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Based on Spectrum Modeling and Optimization
摘要： Bistatic synthetic aperture radar (SAR) is able to break through the limitation of monostatic SAR on forward-looking area imaging with appropriate geometry configurations. Thanks to such an ability, bistatic forward-looking SAR (BFSAR) has extensive potential practical applications. For the focusing problem of conventional side-looking SAR, ω–k algorithm is accepted as the ideal solution. In this paper, the ω–k algorithm will be discussed in BFSAR geometry. As for the bistatic configuration, spatial domain linearization procedure should be carried out to extract a range variable from the point target reference spectrum (PTRS) in the existing ω–k algorithms. With respect to the BFSAR geometry, nevertheless, the linearization procedure reduces the accuracy of PTRS seriously. To cope with such a problem, a novel ω–k algorithm for BFSAR is proposed. In the proposed method, the range variable is modeled as a parameterized polynomial, and the corresponding PTRS with respect to two-dimensional frequencies is established. Then, the parameters are estimated by differential evolution to minimize the PTRS errors for each range coordinate and frequency point. Based on the estimated PTRS, the BFSAR data can be focused well by the proposed ω–k algorithm. Simulation results verify the effectiveness of the proposed method.
关键词： Bistatic forward-looking synthetic aperture radar (BFSAR),differential evolution (DE),ω–k,point target reference spectrum (PTRS)
更新于2025-09-23 15:23:52
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Understanding Measurement Artifacts Causing Inherent Cation Gradients in Depth Profiles of Perovskite Photovoltaics with TOF-SIMS
摘要： Utilizing cumulative correlation information already existing in an evolutionary process, this paper proposes a predictive approach to the reproduction mechanism of new individuals for differential evolution (DE) algorithms. DE uses a distributed model (DM) to generate new individuals, which is relatively explorative, whilst evolution strategy (ES) uses a centralized model (CM) to generate offspring, which through adaptation retains a convergence momentum. This paper adopts a key feature in the CM of a covariance matrix adaptation ES, the cumulatively learned evolution path (EP), to formulate a new evolutionary algorithm (EA) framework, termed DEEP, standing for DE with an EP. Without mechanistically combining two CM and DM based algorithms together, the DEEP framework offers advantages of both a DM and a CM and hence substantially enhances performance. Under this architecture, a self-adaptation mechanism can be built inherently in a DEEP algorithm, easing the task of predetermining algorithm control parameters. Two DEEP variants are developed and illustrated in the paper. Experiments on the CEC’13 test suites and two practical problems demonstrate that the DEEP algorithms offer promising results, compared with the original DEs and other relevant state-of-the-art EAs.
关键词： evolution path (EP),Cumulative learning,evolutionary computation,differential evolution (DE)
更新于2025-09-23 15:19:57
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[IEEE 2019 IEEE 21st Electronics Packaging Technology Conference (EPTC) - Singapore, Singapore (2019.12.4-2019.12.6)] 2019 IEEE 21st Electronics Packaging Technology Conference (EPTC) - Smart White LEDs with Tunable Correlated Color Temperatures through Single-Chip Packaging
摘要： This paper studies the optimization problem of topological active net (TAN), which is often seen in image segmentation and shape modeling. A TAN is a topological structure containing many nodes, whose positions must be optimized while a prede?ned topology needs to be maintained. TAN optimization is often time-consuming and even constructing a single solution is hard to do. Such a problem is usually approached by a “best improvement local search” (BILS) algorithm based on deterministic search (DS), which is inef?cient because it spends too much efforts in nonpromising probing. In this paper, we propose the use of micro-differential evolution (DE) to replace DS in BILS for improved directional guidance. The resultant algorithm is termed deBILS. Its micro-population ef?ciently utilizes historical information for potentially promising search directions and hence improves ef?ciency in probing. Results show that deBILS can probe promising neighborhoods for each node of a TAN. Experimental tests verify that deBILS offers substantially higher search speed and solution quality not only than ordinary BILS, but also the genetic algorithm and scatter search algorithm.
关键词： grid deformation,topological active net (TAN),structure optimization,Differential evolution (DE),topological optimization
更新于2025-09-23 15:19:57
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Type II Excitability with Quantum Dot Lasers: Canards, Bistabilities and More
摘要： This paper studies the optimization problem of topological active net (TAN), which is often seen in image segmentation and shape modeling. A TAN is a topological structure containing many nodes, whose positions must be optimized while a prede?ned topology needs to be maintained. TAN optimization is often time-consuming and even constructing a single solution is hard to do. Such a problem is usually approached by a “best improvement local search” (BILS) algorithm based on deterministic search (DS), which is inef?cient because it spends too much efforts in nonpromising probing. In this paper, we propose the use of micro-differential evolution (DE) to replace DS in BILS for improved directional guidance. The resultant algorithm is termed deBILS. Its micro-population ef?ciently utilizes historical information for potentially promising search directions and hence improves ef?ciency in probing. Results show that deBILS can probe promising neighborhoods for each node of a TAN. Experimental tests verify that deBILS offers substantially higher search speed and solution quality not only than ordinary BILS, but also the genetic algorithm and scatter search algorithm.
关键词： grid deformation,topological active net (TAN),structure optimization,Differential evolution (DE),topological optimization
更新于2025-09-23 15:19:57
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[IEEE 2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2) - Rajshahi, Bangladesh (2019.7.11-2019.7.12)] 2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2) - Low Loss Microstructure Optical Fiber Refractive Index Sensor based on Surface Plasmon Resonance
摘要： This paper studies the optimization problem of topological active net (TAN), which is often seen in image segmentation and shape modeling. A TAN is a topological structure containing many nodes, whose positions must be optimized while a prede?ned topology needs to be maintained. TAN optimization is often time-consuming and even constructing a single solution is hard to do. Such a problem is usually approached by a “best improvement local search” (BILS) algorithm based on deterministic search (DS), which is inef?cient because it spends too much efforts in nonpromising probing. In this paper, we propose the use of micro-differential evolution (DE) to replace DS in BILS for improved directional guidance. The resultant algorithm is termed deBILS. Its micro-population ef?ciently utilizes historical information for potentially promising search directions and hence improves ef?ciency in probing. Results show that deBILS can probe promising neighborhoods for each node of a TAN. Experimental tests verify that deBILS offers substantially higher search speed and solution quality not only than ordinary BILS, but also the genetic algorithm and scatter search algorithm.
关键词： grid deformation,topological active net (TAN),structure optimization,Differential evolution (DE),topological optimization
更新于2025-09-23 15:19:57
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[IEEE 2019 Compound Semiconductor Week (CSW) - Nara, Japan (2019.5.19-2019.5.23)] 2019 Compound Semiconductor Week (CSW) - Buried-ridge-waveguide Type GaInAsP/InP Membrane Distributed-Reflector Lasers for Reduction of Differential Resistance
摘要： Utilizing cumulative correlation information already existing in an evolutionary process, this paper proposes a predictive approach to the reproduction mechanism of new individuals for differential evolution (DE) algorithms. DE uses a distributed model (DM) to generate new individuals, which is relatively explorative, whilst evolution strategy (ES) uses a centralized model (CM) to generate offspring, which through adaptation retains a convergence momentum. This paper adopts a key feature in the CM of a covariance matrix adaptation ES, the cumulatively learned evolution path (EP), to formulate a new evolutionary algorithm (EA) framework, termed DEEP, standing for DE with an EP. Without mechanistically combining two CM and DM based algorithms together, the DEEP framework offers advantages of both a DM and a CM and hence substantially enhances performance. Under this architecture, a self-adaptation mechanism can be built inherently in a DEEP algorithm, easing the task of predetermining algorithm control parameters. Two DEEP variants are developed and illustrated in the paper. Experiments on the CEC’13 test suites and two practical problems demonstrate that the DEEP algorithms offer promising results, compared with the original DEs and other relevant state-of-the-art EAs.
关键词： evolutionary computation,differential evolution (DE),evolution path (EP),Cumulative learning
更新于2025-09-19 17:13:59
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Efficient Carrier Transport for AlGaN-Based Deep-UV LEDs With Graded Superlattice p-AlGaN
摘要： This paper studies the optimization problem of topological active net (TAN), which is often seen in image segmentation and shape modeling. A TAN is a topological structure containing many nodes, whose positions must be optimized while a prede?ned topology needs to be maintained. TAN optimization is often time-consuming and even constructing a single solution is hard to do. Such a problem is usually approached by a “best improvement local search” (BILS) algorithm based on deterministic search (DS), which is inef?cient because it spends too much efforts in nonpromising probing. In this paper, we propose the use of micro-differential evolution (DE) to replace DS in BILS for improved directional guidance. The resultant algorithm is termed deBILS. Its micro-population ef?ciently utilizes historical information for potentially promising search directions and hence improves ef?ciency in probing. Results show that deBILS can probe promising neighborhoods for each node of a TAN. Experimental tests verify that deBILS offers substantially higher search speed and solution quality not only than ordinary BILS, but also the genetic algorithm and scatter search algorithm.
关键词： grid deformation,topological active net (TAN),structure optimization,Differential evolution (DE),topological optimization
更新于2025-09-19 17:13:59
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Multiple Round-Trip Delay-Based Architecture for Si-Integrated Photonic Reservoir Computing
摘要： This paper presents a cooperative differential evolution (DE) with multiple populations for multiobjective optimization. The proposed algorithm has M single-objective optimization subpopulations and an archive population for an M-objective optimization problem. An adaptive DE is applied to each subpopulation to optimize the corresponding objective of the multiobjective optimization problem (MOP). The archive population is also optimized by an adaptive DE. The archive population is used not only to maintain all nondominated solutions found so far but also to guide each subpopulation to search along the whole Pareto front. These (M + 1) populations cooperate to optimize all objectives of the MOP by using adaptive DEs. Simulation results on benchmark problems with two, three, and many objectives show that the proposed algorithm is better than some state-of-the-art multiobjective DE algorithms and other popular multiobjective evolutionary algorithms. The online search behavior and parameter sensitivity of the proposed algorithm are also investigated.
关键词： Archive,differential evolution (DE),cooperative populations,search,multiobjective optimization,many-objective optimization
更新于2025-09-19 17:13:59
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Multi-Party Energy Management and Economics of Integrated Energy Microgrid with PV/T and CHP system
摘要： Focusing on electricity and thermal energy requirement of contemporary buildings, a joint operation of photovoltaic thermal (PV/T) based prosumers and a Microturbine based combined heat and power (CHP) system has been presented to analyse the economics of grid-connected microgrid (MG) system. Bidirectional flow of electricity and heat model is considered and is optimally managed using price-based demand response (DR) scheme. Thermal storage is exploited to ward off the substantial amount of heat wastages that enhance the system's reliability during any disruption of microturbine. The objective functions of both prosumer and microgrid operator (MGO) are formulated as a profit maximization problem where they interact with each other on the basis of DR activity. To establish this strategic decision-making process, the system is modelled as a Stackelberg Equilibrium (SE) game, where MGO acts as a leader while PV/T prosumers act as a follower. The interaction or contribution of two players in a game is a problem of non-linear optimization which is solved by Differential Evolution (DE) algorithm. In the end, in a case study, it has been proved that the results are quite lucrative for the proposed model.
关键词： photovoltaic thermal (PV/T),Differential Evolution (DE),demand response (DR),Stackelberg Equilibrium (SE),microgrid (MG),combined heat and power (CHP)
更新于2025-09-10 09:29:36
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[IEEE 2018 International Conference on Microwave and Millimeter Wave Technology (ICMMT) - Chengdu, China (2018.5.7-2018.5.11)] 2018 International Conference on Microwave and Millimeter Wave Technology (ICMMT) - Design of Wideband Circuit Analog Absorber with Improved Oblique Incidence Performance
摘要： Most of the previous circuit analog (CA) absorbers only consider the normal incidence. In this paper, a novel wideband absorber consisting of two dimensional array of conductive crossed dipoles with lumped resistors and a well-designed dielectric, working as the wide-angle impedance matching (WAIM) layer, is presented. Results show that the absorption under oblique transverse electrical (TE) incidence can be markedly improved due to the WAIM layer. Equivalent circuit (EC) and strict formula derivation are proposed to make the design more clear and straightforward. Evolutionary algorithm, to be specific, the differential evolution, is used to speed up the optimization process. The final results obtained by EC and simulation software show that the absorber offers the 10-dB reflection reduction bandwidth of at least 109.6%(2.6-8.9 GHz) when the angle of TE incidence is less than 60 degrees.
关键词： differential evolution (DE),microwave absorber,Circuit analog (CA) absorber,equivalent circuit
更新于2025-09-04 15:30:14