Parallel computing and swarm intelligence based artificial intelligence model for multi-step-ahead hydrological time series prediction
Bibliographic Data
| ID | 21232115 |
|---|---|
| Authors | Wenjing Niu (0000-0001-5351-2040, Changjiang Water Resources Commission), Wen-jing Niu, Zhong-kai Feng (0000-0002-0166-8956, Huazhong University of Science and Technology, corresponding author), Bao-fei Feng, Baofei Feng (Changjiang Water Resources Commission), Yin-shan Xu, Yinshan Xu (Changjiang Water Resources Commission), Yao-wu Min (Changjiang Water Resources Commission) |
| Year | 2021 |
| Volume | 66 |
| Pages | 102686 |
| Publication date | 2021-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Cities and Society (JOURNAL) |
| Journal identifiers | ISSN: 2210-6707 • E-ISSN: 2210-6715 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.scs.2020.102686 |
| OpenAlex | W3117645847 |
| Language | EN |
| Citations received | 5 |
| References cited | 67 |
Machine learning · Particle swarm optimization · Swarm intelligence · Time series · Computer Science · Energy Load and Power Forecasting · Hydrological Forecasting Using AI · Water Quality Monitoring Technologies · Artificial Intelligence · Geology
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| Unique citing works | 5 |
|---|---|
| Citations per year | 1 |
| Citation span | 2021 - 2023 (3) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 5 |