| Review of the self-organizing map (SOM) approach in water resources: Analysis, modelling and application AM Kalteh, P Hjorth, R Berndtsson Environmental Modelling & Software 23 (7), 835-845, 2008 | 568 | 2008 |
| Monthly river flow forecasting using artificial neural network and support vector regression models coupled with wavelet transform AM Kalteh Computers & Geosciences 54, 1-8, 2013 | 234 | 2013 |
| Rainfall-runoff modelling using artificial neural networks (ANNs): modelling and understanding AM Kalteh Caspian Journal of Environmental Sciences 6 (1), 53-58, 2008 | 105 | 2008 |
| Soil erosion and sediment yield modeling using RS and GIS techniques: a case study, Iran S Arekhi, Y Niazi, AM Kalteh Arabian Journal of Geosciences 5 (2), 285-296, 2012 | 91 | 2012 |
| Imputation of missing values in a precipitation-runoff process database AM Kalteh, P Hjorth Hydrology Research 40 (4), 420-432, 2009 | 83 | 2009 |
| Interpolating monthly precipitation by self-organizing map (SOM) and multilayer perceptron (MLP) AM Kalteh, R Berndtsson Hydrological Sciences Journal 52 (2), 305-317, 2007 | 81 | 2007 |
| Wavelet genetic algorithm-support vector regression (wavelet GA-SVR) for monthly flow forecasting AM Kalteh Water Resources Management 29 (4), 1283-1293, 2015 | 71 | 2015 |
| Improving forecasting accuracy of streamflow time series using least squares support vector machine coupled with data-preprocessing techniques AM Kalteh Water Resources Management 30 (2), 747-766, 2016 | 48 | 2016 |
| Modeling sanitary boundaries of drinking water wells on the Caspian Sea southern coasts, Iran V Gholami, H Aghagoli, AM Kalteh Environmental Earth Sciences 74 (4), 2981-2990, 2015 | 28 | 2015 |
| Enhanced monthly precipitation forecasting using artificial neural network and singular spectrum analysis conjunction models AM Kalteh INAE Letters 2 (3), 73-81, 2017 | 21 | 2017 |
| Modular wavelet–extreme learning machine: a new approach for forecasting daily rainfall AM Kalteh Water Resources Management 33 (11), 3831-3849, 2019 | 14 | 2019 |
| Rainfall-runoff modelling using artificial neural networks (ANNs) AM Kalteh Lund University, 2007 | 10 | 2007 |
| Monthly runoff forecasting by means of artificial neural networks (ANNs) AM Kalteh, P Hjorth Desert 13 (2), 181-191, 2008 | 2 | 2008 |
| Estimation of lime (Tilia begonifolia Stev.) trees height using nonlinear models MR Nazari Sendi, I Hassanzad Navroodi, AM Kalteh, H Poorbabaei Iranian Journal of Forest and Poplar Research 27 (4), 436-450, 2020 | 1 | 2020 |
| Feature selection and modeling forest tree canopies using supervised and unsupervised neural network self-organizing maps (case study: District 2, Kacha, Rasht, Iran) SL Asl, IH Navroodi, AM Kalteh | | 2024 |
| Visualizati on and Clustering of Data Derived from Forest Inventory Using Self-Organizing Neural Network (Case Study: District Two Forests of Kacha, Gilan) SL Asl, IH Navroodi, AM Kalteh | | 2024 |
| Sensitivity analysis and performance evaluation of neural networks for predicting forest stand volume-A case study: District 2, Kacha, Guilan province, Iran S Lotfi Asl, I Hassanzad Navroodi, AM Kalteh Journal of Forest Science 70 (5), 209-222, 2024 | | 2024 |
| Estimation of Fagus orientalis Lipsky height using nonlinear models in Hyrcanian forests, Iran MR Nazari Sendi, I Hassanzad Navroodi, AM Kalteh Journal of Forest Science 69 (10), 415-426, 2023 | | 2023 |
| Comparison of the performance of artificial neural networks with regression analysis in estimating the density of forest stands in Saravan, Guilan province S Lotfi Asl, I Hassanzad Navroodi, AM Kalteh Iranian Journal of Forest 12 (4), 607-631, 2021 | | 2021 |
| A study on diameter and height models of Quercus castanefolia in Guilan forests (Case study: Nav-Asalem) B Kazemi Jirdehi, I Hassanzad Navroodi, AM Kalteh, MR Nazari Sendi 9th National Conference on Environment, Energy and Sustainable Natural Resources, 2019 | | 2019 |
Peder HjorthAssoc Prof; Water Resources; Lund UniversityVerified email at tvrl.lth.se