World's Best Scientists 2026 revealed!
Li-Chiu Chang

Li-Chiu Chang

D-Index & Metrics

Engineering and Technology

D-Index
42
Citations
5888
World Ranking
6688
National Ranking
67

Overview

Li-Chiu Chang is affiliated with Tamkang University in Taiwan and specializes in Environmental Science, with a substantial focus on Environmental Engineering, Global and Planetary Change, Water Science and Technology, Atmospheric Science, and Health, Toxicology and Mutagenesis. Their research centers around areas such as hydrological forecasting using artificial intelligence, flood risk assessment and management, hydrology and watershed management studies, air quality monitoring and forecasting, air quality and health impacts, atmospheric chemistry and aerosols, as well as tropical and extratropical cyclones research.

Chang's publication record includes contributions to several journals, with frequent publications appearing in the Journal of Hydrology, The Science of The Total Environment, Journal of Environmental Management, Water, and Journal of Cleaner Production. These venues highlight the scientist's engagement with topics related to water resources, environmental management, and air quality.

Recent papers by Li-Chiu Chang include:

  • Exploring a Long Short-Term Memory based Encoder-Decoder framework for multi-step-ahead flood forecasting, 2020, Journal of Hydrology
  • Seamless integration of convolutional and back-propagation neural networks for regional multi-step-ahead PM2.5 forecasting, 2020, Journal of Cleaner Production
  • Explore spatio-temporal PM2.5 features in northern Taiwan using machine learning techniques, 2020, The Science of The Total Environment
  • An advanced complementary scheme of floating photovoltaic and hydropower generation flourishing water-food-energy nexus synergies, 2020, Applied Energy
  • Spatial-temporal flood inundation nowcasts by fusing machine learning methods and principal component analysis, 2022, Journal of Hydrology

Collaboration plays a notable role in Chang's research, with frequent co-authors including Fi-John Chang, Pu-Yun Kow, Yanlai Zhou, Jia-Yi Liou, and Wei Sun. These collaborations suggest active participation in interdisciplinary and multi-author projects within their areas of expertise.

Main research topics covered by Li-Chiu Chang are:

  • Hydrological Forecasting Using AI
  • Flood Risk Assessment and Management
  • Hydrology and Watershed Management Studies
  • Air Quality Monitoring and Forecasting
  • Air Quality and Health Impacts
  • Atmospheric chemistry and aerosols
  • Tropical and Extratropical Cyclones Research

Chang's body of work reflects an integration of machine learning methods and environmental science applications, particularly examining hydrological and atmospheric phenomena. The scientist's research bridges technical innovation in forecasting models with practical concerns in water resource management and air quality, supporting ongoing studies in environmental engineering and global change dynamics.

Best Publications

  • Optimizing the reservoir operating rule curves by genetic algorithms

    Fi-John Chang;Li Chen;Li-Chiu Chang

  • Exploring a Long Short-Term Memory based Encoder-Decoder framework for multi-step-ahead flood forecasting

    I-Feng Kao;Yanlai Zhou;Li-Chiu Chang;Fi-John Chang

  • Intelligent control for modelling of real‐time reservoir operation

    Li-Chiu Chang;Fi-John Chang

  • Comparison of static-feedforward and dynamic-feedback neural networks for rainfall -runoff modeling

    Yen-Ming Chiang;Li-Chiu Chang;Fi-John Chang

  • Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts

    Yanlai Zhou;Fi-John Chang;Li-Chiu Chang;I-Feng Kao

  • Multi-objective evolutionary algorithm for operating parallel reservoir system

    Li-Chiu Chang;Fi-John Chang

  • Constrained genetic algorithms for optimizing multi-use reservoir operation

    Li-Chiu Chang;Fi-John Chang;Kuo-Wei Wang;Shin-Yi Dai

  • The strategy of building a flood forecast model by neuro‐fuzzy network

    Shen-Hsien Chen;Yong-Huang Lin;Li-Chiu Chang;Fi-John Chang

  • Prediction of monthly regional groundwater levels through hybrid soft-computing techniques

    Fi-John Chang;Li-Chiu Chang;Chien-Wei Huang;I-Feng Kao

  • Real‐time recurrent learning neural network for stream‐flow forecasting

    F.-John Chang;Li-Chiu Chang;Hau-Lung Huang

  • Multi-step-ahead neural networks for flood forecasting

    Fi-John Chang;Yen-Ming Chiang;Li-Chiu Chang

  • Multi-output support vector machine for regional multi-step-ahead PM2.5 forecasting

    Yanlai Zhou;Fi-John Chang;Li-Chiu Chang;I-Feng Kao

  • Reinforced recurrent neural networks for multi-step-ahead flood forecasts

    Pin-An Chen;Li-Chiu Chang;Fi-John Chang

  • Assessing the effort of meteorological variables for evaporation estimation by self-organizing map neural network

    Fi-John Chang;Li-Chiu Chang;Huey-Shan Kao;Gwo-Ru Wu

  • Guiding rational reservoir flood operation using penalty-type genetic algorithm

    Li-Chiu Chang

  • Clustering-based hybrid inundation model for forecasting flood inundation depths

    Li-Chiu Chang;Hung-Yu Shen;Yi-Fung Wang;Jing-Yu Huang

  • Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves

    Ya-Ting Chang;Li-Chiu Chang;Fi-John Chang

  • Regional flood inundation nowcast using hybrid SOM and dynamic neural networks

    Li-Chiu Chang;Hung-Yu Shen;Fi-John Chang

  • A two-step-ahead recurrent neural network for stream-flow forecasting

    Li-Chiu Chang;Fi-John Chang;Yen-Ming Chiang

  • Seamless integration of convolutional and back-propagation neural networks for regional multi-step-ahead PM2.5 forecasting

    Pu-Yun Kow;Yi-Shin Wang;Yanlai Zhou;Yanlai Zhou;I-Feng Kao

  • AI techniques for optimizing multi-objective reservoir operation upon human and riverine ecosystem demands

    Wen Ping Tsai;Fi John Chang;Li Chiu Chang;Edwin E. Herricks

Frequent Co-Authors

Fi-John Chang
Fi-John Chang National Taiwan University
Shenglian Guo
Shenglian Guo Wuhan University
Ming-Jer Tsai
Ming-Jer Tsai Baylor College of Medicine

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