Gavin J. Bowden

1.3k total citations
8 papers, 1.1k citations indexed

About

Gavin J. Bowden is a scholar working on Environmental Engineering, Artificial Intelligence and Water Science and Technology. According to data from OpenAlex, Gavin J. Bowden has authored 8 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Environmental Engineering, 4 papers in Artificial Intelligence and 3 papers in Water Science and Technology. Recurrent topics in Gavin J. Bowden's work include Hydrological Forecasting Using AI (7 papers), Neural Networks and Applications (4 papers) and Energy Load and Power Forecasting (3 papers). Gavin J. Bowden is often cited by papers focused on Hydrological Forecasting Using AI (7 papers), Neural Networks and Applications (4 papers) and Energy Load and Power Forecasting (3 papers). Gavin J. Bowden collaborates with scholars based in Australia and United States. Gavin J. Bowden's co-authors include Graeme C. Dandy, Holger R. Maier, Ana P. Barros and John B. Nixon and has published in prestigious journals such as Water Resources Research, Journal of Hydrology and Mathematical and Computer Modelling.

In The Last Decade

Gavin J. Bowden

8 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Gavin J. Bowden Australia	7	704	521	371	165	152	8	1.1k
S. Srinivasulu India	11	892 1.3×	763 1.5×	546 1.5×	164 1.0×	90 0.6×	20	1.3k
Mohammad Taghi Aalami Iran	15	662 0.9×	582 1.1×	297 0.8×	123 0.7×	114 0.8×	42	1.1k
Yunjung Hyun South Korea	17	990 1.4×	602 1.2×	309 0.8×	147 0.9×	104 0.7×	32	1.4k
Mariush Kemblowski United States	14	812 1.2×	413 0.8×	286 0.8×	200 1.2×	113 0.7×	16	1.1k
Ali Aytek Türkiye	13	611 0.9×	429 0.8×	310 0.8×	191 1.2×	129 0.8×	15	985
Yazid Tikhamarine Algeria	13	601 0.9×	425 0.8×	452 1.2×	111 0.7×	194 1.3×	15	1.0k
Zekâi Şen Türkiye	17	508 0.7×	354 0.7×	489 1.3×	123 0.7×	113 0.7×	60	1.1k
Bogdan Ozga-Zieliński Poland	12	716 1.0×	544 1.0×	641 1.7×	116 0.7×	116 0.8×	22	1.3k
Majid Dehghani Iran	20	543 0.8×	527 1.0×	474 1.3×	108 0.7×	118 0.8×	27	1.2k
C. Sivapragasam India	14	585 0.8×	476 0.9×	357 1.0×	103 0.6×	100 0.7×	62	1.0k

Countries citing papers authored by Gavin J. Bowden

Since Specialization

Citations

This map shows the geographic impact of Gavin J. Bowden's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gavin J. Bowden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gavin J. Bowden more than expected).

Fields of papers citing papers by Gavin J. Bowden

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gavin J. Bowden. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gavin J. Bowden. The network helps show where Gavin J. Bowden may publish in the future.

Co-authorship network of co-authors of Gavin J. Bowden

This figure shows the co-authorship network connecting the top 25 collaborators of Gavin J. Bowden. A scholar is included among the top collaborators of Gavin J. Bowden based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gavin J. Bowden. Gavin J. Bowden is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Bowden, Gavin J., Holger R. Maier, & Graeme C. Dandy. (2012). Real‐time deployment of artificial neural network forecasting models: Understanding the range of applicability. Water Resources Research. 48(10). 55 indexed citations

2.

Barros, Ana P. & Gavin J. Bowden. (2008). Toward long-lead operational forecasts of drought: An experimental study in the Murray-Darling River Basin. Journal of Hydrology. 357(3-4). 349–367. 73 indexed citations

3.

Bowden, Gavin J., et al.. (2006). Forecasting chlorine residuals in a water distribution system using a general regression neural network. Mathematical and Computer Modelling. 44(5-6). 469–484. 78 indexed citations

4.

Bowden, Gavin J., Graeme C. Dandy, & Holger R. Maier. (2004). Input determination for neural network models in water resources applications. Part 1—background and methodology. Journal of Hydrology. 301(1-4). 75–92. 446 indexed citations

5.

Bowden, Gavin J., Holger R. Maier, & Graeme C. Dandy. (2004). Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river. Journal of Hydrology. 301(1-4). 93–107. 177 indexed citations

6.

Bowden, Gavin J., Graeme C. Dandy, & Holger R. Maier. (2003). Data transformation for neural network models in water resources applications. Journal of Hydroinformatics. 5(4). 245–258. 24 indexed citations

7.

Bowden, Gavin J., Holger R. Maier, & Graeme C. Dandy. (2002). Optimal division of data for neural network models in water resources applications. Water Resources Research. 38(2). 253 indexed citations

8.

Bowden, Gavin J.. (2000). A review of cyanobacteria. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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