The optical properties of CdBr2 were studied by first principle using the density functional theory. The dielectric functions and optical constants are calculated using the full potential-linearized augmented plane wa...The optical properties of CdBr2 were studied by first principle using the density functional theory. The dielectric functions and optical constants are calculated using the full potential-linearized augmented plane wave (FP-LAPW) method with the generalized gradient approximation (GGA). The theoretical calculated optical properties and energy Loss (EEL) spectrum yield a static refractive index of 2.1 and a plasmon energy of 13eV for hexagonal phase. The results, in comparison with the published data, are in good agreement with the experimental and previous theoretical results.展开更多
Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things(IoT).The IoT is the backbone of smart city applications such as smart grids and green ...Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things(IoT).The IoT is the backbone of smart city applications such as smart grids and green energy management.In smart cities,the IoT devices are used for linking power,price,energy,and demand information for smart homes and home energy management(HEM)in the smart grids.In complex smart gridconnected systems,power scheduling and secure dispatch of information are the main research challenge.These challenges can be resolved through various machine learning techniques and data analytics.In this paper,we have proposed a particle swarm optimization based machine learning algorithm known as a collaborative execute-before-after dependency-based requirement,for the smart grid.The proposed collaborative execute-before-after dependencybased requirement algorithm works in two phases,analysis and assessment of the requirements of end-users and power distribution companies.In the rst phases,a xed load is adjusted over a period of 24 h,and in the second phase,a randomly produced population load for 90 days is evaluated using particle swarm optimization.The simulation results demonstrate that the proposed algorithm performed better in terms of percentage cost reduction,peak to average ratio,and power variance mean ratio than particle swarm optimization and inclined block rate.展开更多
The optical properties of CdBr2 were studied by first principle using the density functional theory. The dielectric functions and optical constants are calculated using the full potential-linearized augmented plane wa...The optical properties of CdBr2 were studied by first principle using the density functional theory. The dielectric functions and optical constants are calculated using the full potential-linearized augmented plane wave (FP-LAPW) method with the generalized gradient approximation (GGA). The theoretical calculated optical properties and energy Loss (EEL) spectrum yield a static refractive index of 2.1 and a plasmon energy of 13eV for hexagonal phase. The results, in comparison with the published data, are in good agreement with the experimental and previous theoretical results.展开更多
文摘The optical properties of CdBr2 were studied by first principle using the density functional theory. The dielectric functions and optical constants are calculated using the full potential-linearized augmented plane wave (FP-LAPW) method with the generalized gradient approximation (GGA). The theoretical calculated optical properties and energy Loss (EEL) spectrum yield a static refractive index of 2.1 and a plasmon energy of 13eV for hexagonal phase. The results, in comparison with the published data, are in good agreement with the experimental and previous theoretical results.
文摘Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things(IoT).The IoT is the backbone of smart city applications such as smart grids and green energy management.In smart cities,the IoT devices are used for linking power,price,energy,and demand information for smart homes and home energy management(HEM)in the smart grids.In complex smart gridconnected systems,power scheduling and secure dispatch of information are the main research challenge.These challenges can be resolved through various machine learning techniques and data analytics.In this paper,we have proposed a particle swarm optimization based machine learning algorithm known as a collaborative execute-before-after dependency-based requirement,for the smart grid.The proposed collaborative execute-before-after dependencybased requirement algorithm works in two phases,analysis and assessment of the requirements of end-users and power distribution companies.In the rst phases,a xed load is adjusted over a period of 24 h,and in the second phase,a randomly produced population load for 90 days is evaluated using particle swarm optimization.The simulation results demonstrate that the proposed algorithm performed better in terms of percentage cost reduction,peak to average ratio,and power variance mean ratio than particle swarm optimization and inclined block rate.
文摘The optical properties of CdBr2 were studied by first principle using the density functional theory. The dielectric functions and optical constants are calculated using the full potential-linearized augmented plane wave (FP-LAPW) method with the generalized gradient approximation (GGA). The theoretical calculated optical properties and energy Loss (EEL) spectrum yield a static refractive index of 2.1 and a plasmon energy of 13eV for hexagonal phase. The results, in comparison with the published data, are in good agreement with the experimental and previous theoretical results.
