Cited by 203Hydrology and Drought AnalysisHydrological Forecasting Using AIStock Market Forecasting Methods

Drought forecasting by ANN, ANFIS, and SVM and comparison of the models

Mokhtarzad, Maryam, Eskandari, Farzad, Jamshidi Vanjani, Nima, Arabasadi, Alireza·2017·Environmental Earth Sciences

Integrity signals

Registry

Crossref · 10.1007/s12665-017-7064-0

Cites

45 of 45 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Mokhtarzad, M., Eskandari, F., Jamshidi Vanjani, N., & Arabasadi, A.
Affiliations
  • Allameh Tabataba'i University (IR)
  • Shahid Beheshti University (IR)
Corresponding author
Mokhtarzad, Maryam
Venue
Environmental Earth Sciences
Published
2017-10-28
Volume
76
Issue
21
ISSN
  • 1866-6280 (ISSN-L)
  • 1866-6299
OpenAlex
W2765106898
Cited by
203
References
45
Citations by year
2026: 14 · 2025: 22 · 2024: 31 · 2023: 34 · 2022: 41 · 2021: 26 · 2020: 20 · 2019: 11 · 2018: 4
FWCI
6.64
Type
journal article
Language
en
Open access
closed
Locations
Environmental Earth Sciences (publishedVersion)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Hydrology and Drought Analysis
  • Physical Sciences › Environmental Science › Environmental Engineering › Hydrological Forecasting Using AI
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Stock Market Forecasting Methods
Keywords
drought forecasting, Standardized Precipitation Index, artificial neural networks, adaptive neuro-fuzzy inference system, support vector machine, model comparison, weather station data, precipitation, Bojnurd

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review