- 标题
- 摘要
- 关键词
- 实验方案
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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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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