Boe Technology Group Co., Ltd.

Chengdu Boe Optoelectronics Technology Co., Ltd.

China Institute of Water Resources and Hydropower Research

China Three Gorges Corporation

Heng Yang

Hao Wang

Chao Wang

Huichao Dai

Zhao Zhang

Zhaohui Yang

Xiaohui Lei

Yongnan Zhu

Wei Li

Yinglong Huang

Biao Xu

Hungchieh Hu

Yanbo Zeng

Lingzhong Kong

A method for predicting and controlling a water level of a series water conveyance canal on the basis of a fuzzy neural network is disclosed. The method includes: performing the relationship between a sluice opening degree and an open canal control water level by means of a fuzzy neural network, and constructing an upstream water level controller of a coupled predictive control algorithm; solving an optimal control rate of the upstream water level controller using a gradient optimization algorithm on the basis of a control target of the upstream water level controller; and generating a control strategy by collecting actually measured water level change information and multiplying the actually measured water level change information by the optimal control rate on the basis of the solved optimal control rate, thereby fulfilling the object of predicting and controlling the water level.

Method for predicting and controlling awater level of a series water conveyance canal on a basis of a fuzzy neural network

A real-time abnormity-diagnosing and interpolation method for water regime-monitoring data relates to the technical field of monitoring water regime. This method includes the following steps: acquiring water regime-monitoring data, drawing a box plot, recognizing and diagnosing abnormal data in real time based on the box plot, performing grey correlation analysis on other variables related to a predictor variable, building a BP neural network model and making training, applying the BP neural network model to predict water regime-monitoring data in real time, and performing abnormity diagnosis and data interpolation. Adopting this method, we can effectively enhance predicting and monitoring the water regime-monitoring data in real time, and diagnose abnormal data and make interpolations in time, thereby improving the reliability of data, objectively reflecting water regime changes, and effectively guiding engineering scheduling.

Real-time abnormity-diagnosing and interpolation method for water regime-monitoring data

Provided is a pixel defining layer of an organic light-emitting diode display panel. The pixel defining layer includes: an insulating transparent cladding layer; and a reflecting layer in the transparent cladding layer, wherein the reflecting layer is configured to reflect light emitted from a light-emitting layer of the organic light-emitting diode display panel. Organic light-emitting diode display panels and methods for manufacturing an organic light-emitting diode display panel are also provided.

Pixel defining layer, organic light-emitting diode display panel, and manufacturing method thereof

A display panel, a manufacturing method and a display device are provided. The display panel includes a substrate having a display area and a non-display area; a planarization layer covering the display area and the non-display area of the substrate; an organic light emitting element located in the display area and located at a side of the planarization layer away from the substrate; an encapsulation structure including a first inorganic layer, an organic layer and a second inorganic layer which are sequentially stacked, where the first inorganic layer and the second inorganic layer extend into a non-display area, and the first inorganic layer is arranged close to the planarization layer; and/or, a part of the planarization layer located in the non-display area is provided with a groove, and the groove is filled with a flexible water-oxidation resistant material.

Display panel, manufacturing method thereof and display device

Growing community of inventors

Beijing, China

Heng Yang