Fen Wei

ORCID: 0000-0003-4180-8295
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About
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Research Areas
  • Optical Wireless Communication Technologies
  • Indoor and Outdoor Localization Technologies
  • Impact of Light on Environment and Health
  • Underwater Vehicles and Communication Systems
  • Image Enhancement Techniques
  • Advanced Wireless Communication Technologies
  • Bone health and osteoporosis research
  • Vitamin D Research Studies
  • Cardiovascular Function and Risk Factors
  • Biometric Identification and Security
  • Advanced MRI Techniques and Applications
  • Power Systems and Technologies
  • Remote Sensing and Land Use
  • Video Surveillance and Tracking Methods
  • Power Line Communications and Noise
  • Advanced Algorithms and Applications
  • Smart Parking Systems Research
  • UAV Applications and Optimization
  • Cardiomyopathy and Myosin Studies
  • Power Systems Fault Detection
  • Machine Learning and ELM
  • Advanced Measurement and Detection Methods
  • Advanced Chemical Sensor Technologies
  • Bone health and treatments

Lanzhou University
2024

First Hospital of Lanzhou University
2024

Fujian Normal University
2020-2024

Fujian Agriculture and Forestry University
2022

Shanghai Medical Information Center
2015

Jiangsu Provincial Posts & Telecommunications Planning & Design Institute (China)
2008

Indoor positioning system based on visible light communication and location fingerprinting can achieve cm-level accuracy, which has become an important candidate for high precision positioning. However, in the case of non-uniform low-density distribution, it will still lead to large errors poor robustness. To solve this problem, accurate (VLP) method meta-heuristic is proposed, all possible cases uneven distribution are considered by introducing random selection rate. The effectiveness...

10.1109/jlt.2023.3265171 article EN Journal of Lightwave Technology 2023-04-06

The weighted K-nearest neighbor (WKNN) algorithm is a commonly used fingerprint positioning, the difficulty of which lies in how to optimize value K obtain minimum positioning error. In this paper, we propose an adaptive residual (ARWKNN) based on visible light communication. Firstly, target matches fingerprints according received signal strength indication (RSSI) vector. Secondly, dynamic matched RSSI residual. Simulation results show ARWKNN presents reduced average error when compared with...

10.3390/s20164432 article EN cc-by Sensors 2020-08-08

Visible light positioning has become a new research hotspot in recent years. In this study, Gaussian model of hybrid noise and multipath reflection is established for interference line‐of‐sight (LOS) communication non‐LOS (NLOS) communication. First, the likelihood function ranging error according to model, analytical expression Cramer–Rao lower bound derived. Second, novel adaptive parameter particle swarm optimisation (AP‐PSO) algorithm proposed calculate three‐dimensional (3D) coordinates...

10.1049/iet-com.2019.1141 article EN IET Communications 2020-11-13

Although the fingerprint-based visible light positioning (VLP) method can achieve centimeter-level accuracy, it requires collecting received signal strength (RSS) values from a large number of training locations in offline stage, especially when considering rotation angle photodiode (PD). To enhance practicality VLP based on fingerprint method, this paper proposes novel database regeneration method. The proposed does not rely propagation model but only knowledge actual coordinates LEDs while...

10.1109/tim.2024.3378255 article EN IEEE Transactions on Instrumentation and Measurement 2024-01-01

This article proposes an indoor cooperative positioning system for a swarm of micro unmanned aerial vehicles (UAVs) based on visible light communication. The proposed is composed light-emitting diodes (LEDs) installed the ceiling and group UAVs. Each UAV single LED multiple photodiodes (PDs) with uniform distribution. UAVs achieved through LEDs interactive information shared among them. In order to solve nonconvex optimization function constructed by localization, improved bat algorithm...

10.1109/jsyst.2023.3312279 article EN IEEE Systems Journal 2023-09-22

Since input weights and hidden biases affect the overall performance of extreme learning machine (ELM) based on a single-hidden layer, in order to obtain higher classification accuracy, two meta-heuristic algorithms grey wolf optimizer (GWO) particle swarm optimization (PSO) are used optimize ELM, respectively, i.e., enhanced ELM ELM-GWO ELM-PSO. Compared with other existing techniques such as traditional adaptive boosting (AdaBoost), positioning is analyzed by simulation experimental...

10.2139/ssrn.4229996 article EN SSRN Electronic Journal 2022-01-01
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