scholarly journals I-WKNN: Fast-speed and high-accuracy WIFI positioning for intelligent sports stadiums

2022 ◽  
Vol 98 ◽  
pp. 107619
Author(s):  
Zhangzhi Zhao ◽  
Zhengying Lou ◽  
Ruibo Wang ◽  
Qingyao Li ◽  
Xing Xu
2013 ◽  
Vol 448-453 ◽  
pp. 1480-1485
Author(s):  
Li Jie Yin ◽  
Ya Zhen ◽  
Qi Li Fan

A modeling method of single-phase grid-connected photovoltaic micro-inverter is presented in this paper,which depends on the topology structure of fly-back converter. Simulation of the micro-inverter is performed using Matlab software, which has the virtues of high accuracy and fast speed. Prototype experiment results show that the simulation model can be a true reflection of the working process of a micro-inverter, and could be used to verify the control algorithm and select the control parameters.


2011 ◽  
Vol 230-232 ◽  
pp. 235-240
Author(s):  
Chuan De Zhou ◽  
Li Lai

This paper researchs the space vector change and machine vision recognition based on plane target cooperation identification.Then establishes plane target imaging model, space attitude measurement algorithm and software flow, which are utilized in the measurement of automobile four-wheel location. The results indicate that this method is feasible in the automobile four-wheel location technology with the advantages of good anti-interference, fast speed, wide range and high accuracy.


2013 ◽  
Vol 864-867 ◽  
pp. 903-907
Author(s):  
Qiao Su ◽  
Chang Sheng Peng ◽  
Hong Jun Yu ◽  
Xiong Yong Xu ◽  
Jing Yao

Based on the monitoring data in the coastal area of Laizhou bay, the paper presents the correlation between groundwater conductivity and chemical characteristics.The results showed that,compared with titration method,application of Diagometer has the advantages of high accuracy,fast speed and simple operation.When the seawater intrusion has not yet occurred or relatively weak,the effect of the application of diagometer is not very obvious.Only when seawater intrusion occurs serious,application of Diagometer can reflect the changes of mineralization degree and chloride ion concentration of groundwater accurately.


2011 ◽  
Vol 8 (12) ◽  
pp. 884-889
Author(s):  
Jin Wu ◽  
Ke Ma ◽  
Weidong Nie ◽  
Ning Qu

2014 ◽  
Vol 511-512 ◽  
pp. 193-196
Author(s):  
Shuo Ding ◽  
Xiao Heng Chang ◽  
Qing Hui Wu

Traditional sensor fault diagnosis is mainly based on statistical classification methods. The discriminant functions in these methods are extremely complex, and typical samples of reference modes are not easy to get, therefore it is difficult to meet the actual requirements of a project. In view of the deficiencies of conventional sensor fault diagnosis technologies, a fault diagnosis method based on self-organizing feature map (SOFM) neural network is presented in this paper. And it is applied to the fault diagnosis of pipeline flow sensor in a dynamic system. The simulation results show that the fault diagnosis method based on SOFM neural network has a fast speed, high accuracy and strong generalization ability, which verifies the practicality and effectiveness of the proposed method.


2012 ◽  
Vol 198-199 ◽  
pp. 137-140
Author(s):  
Yu Sheng Wang ◽  
Ming Ming Wang ◽  
Xiang Jun Zhu

Because of such merits of servo turret like fast speed of tool changing, high accuracy of first location, simple mechanical structure, high reliability and so on, servo turrets are widely used in turning processing and turning and milling complex processing center.Control mode of servo motor speed is one of the critical problems in the designing of servo turret.S curve acceleration and deceleration control is to make the derivative of acceleration as constant in this procession, and maximize to reduce the impact of mechanical system by controlling acceleration derivative. Otherwise, by setting parameter or programming acceleration and its derivative, flexible acceleration and deceleration will be controlled to fit for different kinds of situation of machines.


2020 ◽  
Vol 10 (3) ◽  
pp. 710-717
Author(s):  
Shupeng Zheng ◽  
Chenhui Peng ◽  
Fang Fang ◽  
Xiaochu Liu

Due to the diversity and complexity of emotional bioinformation, most emotion recognition studies relied to ponderous medical grade electroencephalography (EEG) measuring devices. The emotion recognition scenarios were limited to hospitals or laboratories. It is hard to directly apply these research achievements into the emotion monitoring in daily-life. In this paper, a novel emotion recognition approach based on multimodal wearable biosensor network is investigated. In order to facilitate emotion monitoring in daily-life, a multimodal wearable biosensor network is constructed. The multimodal bio-signals are acquired by wearable biosensor measuring nodes, and then transmitted to sink node through wireless communication technologies. According to the fuzzy and rough characteristics of human emotions, the fuzzy rough nearest neighbors (FRNN) algorithm is introduced to classify different emotions. By considering the fuzzy thresholds of EEG concentration, a novel FRNN emotion recognition approach is proposed. The proposed method narrows the classification range of samples with significant concentration and reduces the disturbance of noisy samples, so that the high accuracy (65.6%) and fast speed were achieved in wearable scenario. Experiments verified the effectiveness of the proposed approach.


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