| |
Author |
Title |
Year  |
Publication |
Volume |
Pages |
Links |
|
|
Kisi, O.; Liepelt, K.; Kulls, C. |
Discussion of “Improving Prediction Accuracy of Hydrologic Time Series by Least-Squares Support Vector Machine Using Decomposition Reconstruction and Swarm Intelligence” |
2023 |
Journal of Hydrologic Engineering |
28 |
07023001 |
|
|
|
Kisi, O.; Ajri, S.; Jörgens, K.C.; Karande, A.; Kraus, S.; Naumann, B.; Nierman, K.; Seel, W.; Kulls, C. |
Comments on “Splitting tensile strength prediction of sustainable high-performance concrete using machine learning techniques” by Wu, Yangi et al., https://doi. org/10.1007/s11356-022-22048-2 |
2023 |
Environmental Science and Pollution Research |
30 |
109854-109855 |
|
|
|
Kisi, O.; Ardiçlio\uglu, M.; Hadi, A.M.W.; Kuriqi, A.; Kulls, C. |
Estimation of mean velocity upstream and downstream of a bridge model using metaheuristic regression methods |
2023 |
Water Resources Management |
37 |
5559-5580 |
|
|
|
Eliades, M.; Bruggeman, A.; Djuma, H.; Christofi, C.; Kuells, C. |
Quantifying evapotranspiration and drainage losses in a semi-arid nectarine (Prunus persica var. nucipersica) field with a dynamic crop coefficient (Kc) derived from leaf area index measurements |
2022 |
Water |
14 |
734 |
|
|
|
Külls, C.; Bassukas, D. |
Groundwater salinization dynamics-a conceptual modeling approach to prioritize water management plans in a changing environment |
2022 |
EGU General Assembly Conference Abstracts |
|
22 |
|
