简介:Inthispaper,weproposeanovelapproachtoachievespectrumprediction,parameterfitting,inversedesign,andperformanceoptimizationfortheplasmonicwaveguide-coupledwithcavitiesstructure(PWCCS)basedonartificialneuralnetworks(ANNs).TheFanoresonanceandplasmon-inducedtransparencyeffectoriginatedfromthePWCCShavebeenselectedasillustrationstoverifytheeffectivenessofANNs.WeusethegeneticalgorithmtodesignthenetworkarchitectureandselectthehyperparametersforANNs.OnceANNsaretrainedbyusingasmallsamplingofthedatageneratedbytheMonteCarlomethod,thetransmissionspectrapredictedbytheANNsarequiteapproximatetothesimulatedresults.Thephysicalmechanismsbehindthephenomenaarediscussedtheoretically,andtheuncertainparametersinthetheoreticalmodelsarefittedbyutilizingthetrainedANNs.Moreimportantly,ourresultsdemonstratethatthismodel-drivenmethodnotonlyrealizestheinversedesignofthePWCCSwithhighprecisionbutalsooptimizessomecriticalperformancemetricsforthetransmissionspectrum.Comparedwithpreviousworks,weconstructanovelmodel-drivenanalysismethodforthePWCCSthatisexpectedtohavesignificantapplicationsinthedevicedesign,performanceoptimization,variabilityanalysis,defectdetection,theoreticalmodeling,opticalinterconnects,andsoon.
简介:摘要随着社会经济的快速发展,电力设施所处的环境日益复杂多变,各类外破隐患层出不穷,对电力生产乃至社会公共安全构成了严重威胁。围绕输电线路通道属地化管理,坚持以“预防为主、防治结合、综合治理”的工作理念,按照“运维主体、内部联防、外部联动、群防群治、共保平安”的管理策略,建立群防群治的护线网络,形成人防、物防、技防综合防控的立体式内部联防体系;建立政府统一领导、企业依法保护、全社会大力支持的外部联动工作格局,形成输电线路防外破管理的常态机制。