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Zhenhong Du
Researcher at Zhejiang University
Publications - 65
Citations - 602
Zhenhong Du is an academic researcher from Zhejiang University. The author has contributed to research in topics: Computer science & Artificial neural network. The author has an hindex of 9, co-authored 46 publications receiving 267 citations.
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Geographically neural network weighted regression for the accurate estimation of spatial non-stationarity
TL;DR: A geographically neural network weighted regression model that combines ordinary least squares (OLS) and neural networks to estimate spatial non-stationarity based on a concept similar to GWR is proposed and achieved better fitting accuracy and more adequate prediction than OLS and GWR.
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Real-Time Spatial Queries for Moving Objects Using Storm Topology
TL;DR: This paper presents a distributed spatial index based on Apache Storm, an open-source distributed real-time computation system, and builds a secondary distributed index for spatial join queries based on the grid-partition index.
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Ecosystem health assessment in coastal waters by considering spatio-temporal variations with intense anthropogenic disturbance
TL;DR: In this research, factors that influence ecosystem health assessment (EHA) in coastal waters were grouped into three categories: natural causes, direct human causes, and indirect human causes to establish a holistic EHA framework.
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Geographically and temporally neural network weighted regression for modeling spatiotemporal non-stationary relationships
TL;DR: To address complex non-linear interactions between time and space, a spatiotemporal proximity neural network (STPNN) is proposed in this paper to accurately generate space-time distance and has the potential to handle complex spatiotmporal non-stationarity in various geographical processes and environmental phenomena.
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Multistep-ahead forecasting of chlorophyll a using a wavelet nonlinear autoregressive network
TL;DR: An effective multistep-ahead forecasting model wavelet nonlinear autoregressive network (WNARNet), which integrates the wavelet transform and a nonlinear Autoregressive neural network (NAR), is proposed for the forecast of chlorophyll a concentration.