A review of techniques for parameter sensitivity analysis of environmental models
- Authors
- D.M. Hamby
In The Last Decade
doi.org/10.1007/bf00547132 →Countries where authors are citing A review of techniques for parameter sensitivity analysis of environmental models
This map shows the geographic impact of A review of techniques for parameter sensitivity analysis of environmental models. 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 A review of techniques for parameter sensitivity analysis of environmental models with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A review of techniques for parameter sensitivity analysis of environmental models more than expected).
Fields of papers citing A review of techniques for parameter sensitivity analysis of environmental models
This network shows the impact of A review of techniques for parameter sensitivity analysis of environmental models. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the A review of techniques for parameter sensitivity analysis of environmental models.
About A review of techniques for parameter sensitivity analysis of environmental models
This paper, published in 1994, received 1.4k indexed citations . Written by D.M. Hamby covering the research area of Environmental Engineering and Statistics, Probability and Uncertainty. It is primarily cited by scholars working on Environmental Engineering (264 citations), Global and Planetary Change (213 citations) and Civil and Structural Engineering (210 citations). Published in Environmental Monitoring and Assessment.
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.
This paper is also available at doi.org/10.1007/bf00547132.