Defect recognition based on picture analysis is one of the most important means to detect key failure points or damages. However, the recognition rate is low due to the limited number of pictures collected on site, so...Defect recognition based on picture analysis is one of the most important means to detect key failure points or damages. However, the recognition rate is low due to the limited number of pictures collected on site, so the computer training set is limited, which leads to a lack of studying and training. Meanwhile, the internet provides a large number of related pictures which can be used as an important data source for training picture analyzing engines. By using an internet spider under certain rules, one can freely collect information on the internet. The internet spider described in this paper can automatically collect related images from the internet as well as search for similar images by leveraging on a local seed picture. This spider also has a parallel version, which can give significant performance boost when run.展开更多
In order to optimize the ladder-pricing scheme in Shanghai, we present a multi-objective optimization model (MOOM). To build this model, first we use price elasticity theory;divide the ladder pricing into peak electri...In order to optimize the ladder-pricing scheme in Shanghai, we present a multi-objective optimization model (MOOM). To build this model, first we use price elasticity theory;divide the ladder pricing into peak electricity bill and valley electricity bill in the time dimension to model the single-user demand response. Second based on the single-user demand response model, combined with the overall users’ electricity distribution density function, we build an all-users demand response model. The proposed model has two objectives: minimize energy consumption and maximize residents’ satisfaction. Simulation results confirm that the proposed model can optimize the ladder-pricing scheme.展开更多
文摘Defect recognition based on picture analysis is one of the most important means to detect key failure points or damages. However, the recognition rate is low due to the limited number of pictures collected on site, so the computer training set is limited, which leads to a lack of studying and training. Meanwhile, the internet provides a large number of related pictures which can be used as an important data source for training picture analyzing engines. By using an internet spider under certain rules, one can freely collect information on the internet. The internet spider described in this paper can automatically collect related images from the internet as well as search for similar images by leveraging on a local seed picture. This spider also has a parallel version, which can give significant performance boost when run.
文摘In order to optimize the ladder-pricing scheme in Shanghai, we present a multi-objective optimization model (MOOM). To build this model, first we use price elasticity theory;divide the ladder pricing into peak electricity bill and valley electricity bill in the time dimension to model the single-user demand response. Second based on the single-user demand response model, combined with the overall users’ electricity distribution density function, we build an all-users demand response model. The proposed model has two objectives: minimize energy consumption and maximize residents’ satisfaction. Simulation results confirm that the proposed model can optimize the ladder-pricing scheme.
