A basic end-member model algorithm for grain-size data of marine sediments. (5th May 2020)
- Record Type:
- Journal Article
- Title:
- A basic end-member model algorithm for grain-size data of marine sediments. (5th May 2020)
- Main Title:
- A basic end-member model algorithm for grain-size data of marine sediments
- Authors:
- Zhang, Xiaodong
Wang, Hongmin
Xu, Shumei
Yang, Zuosheng - Abstract:
- Abstract: End-member (EM) unmixing algorithms are widely used in the earth sciences for unmixing compositional data such as grain-size data of sediments. However, many unmixing algorithms only use goodness-of-fit measures that justify the EMs in the absence of geological feasibility, and others tend to find EMs that enclose the sample points as tightly as possible, resulting in the calculated EMs are still mixed products, especially when unmixing highly mixed dataset. This paper proposes that EM unmixing algorithms should search for the Basic-EMs, i.e., the outermost points in the EM space. The EMs that can be unmixed by mathematics can also be purified by physical processes, i.e., the actual EMs are most likely the Basic-EMs. This paper also introduces a basic end-member model algorithm (BasEMMA) that uses genetic algorithms which mimic natural evolution processes, to seek the Basic-EMs. The evaluations by BasEMMA using both artificial and actual grain-size data show that BasEMMA can accurately find the Basic-EMs. This paper also introduces a procedure for determining the appropriate EM number, which has plagued previous researchers. In summary, this paper introduces a new way to determine geologically feasible EMs, a new EM unmixing algorithm and a new method to determine the appropriate EM number. Highlights: End-Member unmixing algorithms should search for the Basic-EMs. Most of the calculated EMs by previous algorithms are mixed products. Stability of calculated EMs canAbstract: End-member (EM) unmixing algorithms are widely used in the earth sciences for unmixing compositional data such as grain-size data of sediments. However, many unmixing algorithms only use goodness-of-fit measures that justify the EMs in the absence of geological feasibility, and others tend to find EMs that enclose the sample points as tightly as possible, resulting in the calculated EMs are still mixed products, especially when unmixing highly mixed dataset. This paper proposes that EM unmixing algorithms should search for the Basic-EMs, i.e., the outermost points in the EM space. The EMs that can be unmixed by mathematics can also be purified by physical processes, i.e., the actual EMs are most likely the Basic-EMs. This paper also introduces a basic end-member model algorithm (BasEMMA) that uses genetic algorithms which mimic natural evolution processes, to seek the Basic-EMs. The evaluations by BasEMMA using both artificial and actual grain-size data show that BasEMMA can accurately find the Basic-EMs. This paper also introduces a procedure for determining the appropriate EM number, which has plagued previous researchers. In summary, this paper introduces a new way to determine geologically feasible EMs, a new EM unmixing algorithm and a new method to determine the appropriate EM number. Highlights: End-Member unmixing algorithms should search for the Basic-EMs. Most of the calculated EMs by previous algorithms are mixed products. Stability of calculated EMs can be used to determine the appropriate EM number. … (more)
- Is Part Of:
- Estuarine, coastal and shelf science. Volume 236(2020)
- Journal:
- Estuarine, coastal and shelf science
- Issue:
- Volume 236(2020)
- Issue Display:
- Volume 236, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 236
- Issue:
- 2020
- Issue Sort Value:
- 2020-0236-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-05-05
- Subjects:
- End-member unmixing -- End-member space -- Basic end-members -- Genetic algorithm -- Grain size distribution
Estuarine oceanography -- Periodicals
Coasts -- Periodicals
Estuarine biology -- Periodicals
Seashore biology -- Periodicals
Coasts
Estuarine biology
Estuarine oceanography
Seashore biology
Periodicals
551.461805 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02727714 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ecss.2020.106656 ↗
- Languages:
- English
- ISSNs:
- 0272-7714
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3812.599200
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 13541.xml