Conceiçāo Amado

856 total citations
36 papers, 566 citations indexed

About

Conceiçāo Amado is a scholar working on Civil and Structural Engineering, Ocean Engineering and Soil Science. According to data from OpenAlex, Conceiçāo Amado has authored 36 papers receiving a total of 566 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Civil and Structural Engineering, 11 papers in Ocean Engineering and 5 papers in Soil Science. Recurrent topics in Conceiçāo Amado's work include Water Systems and Optimization (16 papers), Water resources management and optimization (11 papers) and Soil erosion and sediment transport (3 papers). Conceiçāo Amado is often cited by papers focused on Water Systems and Optimization (16 papers), Water resources management and optimization (11 papers) and Soil erosion and sediment transport (3 papers). Conceiçāo Amado collaborates with scholars based in Portugal, Switzerland and United Kingdom. Conceiçāo Amado's co-authors include João P. Dias, D. Loureiro, S. T. Coelho, Dídia Covas, Marta Cabral, João P. Leitão, Jorge Matos, Anton Schleiss, Michael Pfister and Ana M. Pires and has published in prestigious journals such as SHILAP Revista de lepidopterología, Water Resources Research and Expert Systems with Applications.

In The Last Decade

Conceiçāo Amado

34 papers receiving 540 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Conceiçāo Amado Portugal 13 284 127 103 103 83 36 566
Manh Duc Nguyen Vietnam 12 381 1.3× 150 1.2× 52 0.5× 57 0.6× 42 0.5× 22 742
Zhengjing Ma China 10 102 0.4× 152 1.2× 41 0.4× 84 0.8× 14 0.2× 15 723
Quang Hung Nguyen Vietnam 5 209 0.7× 32 0.3× 23 0.2× 73 0.7× 27 0.3× 10 574
Seunghee Park South Korea 19 269 0.9× 155 1.2× 84 0.8× 87 0.8× 7 0.1× 78 911
Nabeel Saleem Saad Al-Bdairi Iraq 12 65 0.2× 419 3.3× 43 0.4× 90 0.9× 101 1.2× 23 695
Shuhong Wang China 13 228 0.8× 97 0.8× 46 0.4× 45 0.4× 19 0.2× 54 524
I.U. Ekanayake Sri Lanka 12 254 0.9× 21 0.2× 29 0.3× 110 1.1× 80 1.0× 20 725
Xuan-Linh Tran Vietnam 16 352 1.2× 59 0.5× 36 0.3× 71 0.7× 35 0.4× 24 653
Peixi Yang China 9 209 0.7× 84 0.7× 77 0.7× 33 0.3× 13 0.2× 11 550
Reza Tarinejad Iran 18 782 2.8× 140 1.1× 196 1.9× 61 0.6× 26 0.3× 45 1.0k

Countries citing papers authored by Conceiçāo Amado

Since Specialization
Citations

This map shows the geographic impact of Conceiçāo Amado'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 Conceiçāo Amado with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Conceiçāo Amado more than expected).

Fields of papers citing papers by Conceiçāo Amado

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Conceiçāo Amado. 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 Conceiçāo Amado. The network helps show where Conceiçāo Amado may publish in the future.

Co-authorship network of co-authors of Conceiçāo Amado

This figure shows the co-authorship network connecting the top 25 collaborators of Conceiçāo Amado. A scholar is included among the top collaborators of Conceiçāo Amado 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 Conceiçāo Amado. Conceiçāo Amado is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Amado, Conceiçāo, et al.. (2025). Robust estimation of heteroscedastic regression models: a brief overview and new proposals. Statistical Papers. 66(3). 1 indexed citations
2.
Amado, Conceiçāo, et al.. (2024). Inferring Demand in Drinking Water Distribution Systems through Stratified Sampling of Billing Data for Smart Meter Installation. Journal of Water Resources Planning and Management. 150(8).
3.
Cabral, Marta, D. Loureiro, Conceiçāo Amado, & Dídia Covas. (2024). Deterioration Models and Service Life Prediction of Vertical Assets of Urban Water Systems. Water Resources Research. 60(4).
4.
Silva, Nuno, et al.. (2023). A methodology for crash investigation of motorcycle-cars collisions combining accident reconstruction, finite elements, and experimental tests. Engineering Failure Analysis. 152. 107505–107505. 11 indexed citations
5.
Falcão, Ana Paula, et al.. (2023). SARClust—A New Tool to Analyze InSAR Displacement Time Series for Structure Monitoring. Sustainability. 15(4). 3728–3728. 2 indexed citations
6.
Amado, Conceiçāo, et al.. (2022). Increased Excursions to Functional Networks in Schizophrenia in the Absence of Task. Frontiers in Neuroscience. 16. 821179–821179. 18 indexed citations
7.
Amado, Conceiçāo, et al.. (2022). Uncertainty evaluation in time-dependent measurements. Measurement. 196. 111196–111196. 12 indexed citations
8.
Pfister, Michael, et al.. (2021). Blockage Probability Modeling of Large Wood at Reservoir Spillways With Piers. Water Resources Research. 57(8). 12 indexed citations
9.
Dias, João P., et al.. (2021). A literature review of machine learning algorithms for crash injury severity prediction. Journal of Safety Research. 80. 254–269. 112 indexed citations
10.
Dias, João P., et al.. (2021). Risk factors associated with the increase of injury severity of powered two wheelers road accidents victims in Portugal. Traffic Injury Prevention. 22(8). 646–650. 8 indexed citations
11.
Pfister, Michael, et al.. (2019). Statistical accuracy for estimations of large wood blockage in a reservoir environment. Environmental Fluid Mechanics. 20(3). 579–592. 7 indexed citations
12.
Sutherland, L.S., Conceiçāo Amado, & C. Guedes Soares. (2019). Statistical analyses of the effects of bonding parameters and fabrication robustness on the strength of adhesive T-joints. Composites Part B Engineering. 175. 107063–107063. 5 indexed citations
13.
Cabral, Marta, et al.. (2019). Demand scenario planning approach using regression techniques and application to network sectors in Portugal. Water Policy. 21(2). 394–411. 4 indexed citations
14.
Pfister, Michael, et al.. (2018). Experimental repetitions and blockage of large stems at ogee crested spillways with piers. Journal of Hydraulic Research. 57(2). 250–262. 36 indexed citations
15.
Amado, Conceiçāo, et al.. (2018). Analysing the importance of variables for sewer failure prediction. Urban Water Journal. 15(4). 338–345. 8 indexed citations
16.
Amado, Conceiçāo, et al.. (2018). Image reconstruction based on circulant matrices. Signal Processing Image Communication. 63. 72–80. 7 indexed citations
17.
Cabral, Marta, et al.. (2016). Modeling the effect of weather conditions on urban water demand in multiple network areas: a practical approach to improve monthly and seasonal operation. Journal of Water Supply Research and Technology—AQUA. 65(8). 612–625. 5 indexed citations
18.
Amado, Conceiçāo, et al.. (2016). Data reconstruction of flow time series in water distribution systems – a new method that accommodates multiple seasonality. Journal of Hydroinformatics. 19(2). 238–250. 12 indexed citations
19.
Loureiro, D., et al.. (2014). Spatial and Temporal Forecasting of Water Consumption at the DMA Level Using Extensive Measurements. Procedia Engineering. 70. 1063–1073. 15 indexed citations
20.
Leitão, João P., et al.. (2013). Comparative Study of Three Stochastic Models for Prediction of Pipe Failures in Water Supply Systems. Journal of Infrastructure Systems. 19(4). 442–450. 18 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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