Investigation of empirical mode decomposition in forecasting of hydrological time series O Kisi, L Latifoğlu, F Latifoğlu Water resources management 28, 4045-4057, 2014 | 59 | 2014 |
Comparison of neural network, Gaussian regression, support vector machine, long short-term memory, multi-gene genetic programming, and M5 Trees methods for solving civil … E Uncuoglu, H Citakoglu, L Latifoglu, S Bayram, M Laman, M Ilkentapar, ... Applied Soft Computing 129, 109623, 2022 | 51 | 2022 |
Importance of hybrid models for forecasting of hydrological variable L Latifoğlu, Ö Kişi, F Latifoğlu Neural Computing and Applications 26, 1669-1680, 2015 | 19 | 2015 |
A novel combined model for prediction of daily precipitation data using instantaneous frequency feature and bidirectional long short time memory networks L Latifoğlu Environmental Science and Pollution Research 29 (28), 42899-42912, 2022 | 12 | 2022 |
The performance analysis of robust local mean mode decomposition method for forecasting of hydrological time series L Latifoğlu Iranian Journal of Science and Technology, Transactions of Civil Engineering …, 2022 | 9* | 2022 |
Modelling of lateral effective stress using the particle swarm optimization with machine learning models E Uncuoğlu, L Latifoğlu, AT Özer Arabian Journal of Geosciences 14, 1-18, 2021 | 5 | 2021 |
Tekil spektrum analizi ve uzun-kısa süreli bellek ağları ile nehir akım tahmini L Latifoğlu, KB Nuralan Avrupa Bilim ve Teknoloji Dergisi, 376-381, 2020 | 5 | 2020 |
Predicting liquefaction-induced lateral spreading by using the multigene genetic programming (MGGP), multilayer perceptron (MLP), and random forest (RF) techniques Z Kaya, L Latifoglu, E Uncuoglu, A Erol, MS Keskin Bulletin of Engineering Geology and the Environment 82 (3), 84, 2023 | 4 | 2023 |
Application of the novel circulant singular spectrum analysis ensemble model for forecasting of streamflow data L Latifoğlu Arabian Journal of Geosciences 15 (10), 982, 2022 | 3 | 2022 |
A novel approach for prediction of daily streamflow discharge data using correlation based feature selection and random forest method L Latifoğlu International Advanced Researches and Engineering Journal 6 (1), 1-7, 2022 | 3 | 2022 |
A Novel Approach for High-Performance Estimation of SPI Data in Drought Prediction L Latifoğlu, M Özger Sustainability 15 (19), 14046, 2023 | 2 | 2023 |
Evaluating Stream Flow Forecasting Performance Using Adaptive Network Based Fuzzy Logic Inference System, Artificial Neural Networks with Feature Selection L LATIFOGLU The Eurasia Proceedings of Science Technology Engineering and Mathematics 11 …, 2020 | 2 | 2020 |
Prediction of Daily Streamflow Data Using Ensemble Learning Models L Latifoğlu, Ü Canpolat The European Journal of Research and Development 2 (4), 356-371, 2022 | 1 | 2022 |
Deep Learning Approaches for Stream Flow and Peak Flow Prediction: A Comparative Study L Latifoğlu, E Altuntaş The European Journal of Research and Development 4 (1), 61-84, 2024 | | 2024 |
High-performance prediction model combining minimum redundancy maximum relevance, circulant spectrum analysis, and machine learning methods for daily and peak streamflow L Latifoğlu, E Kaya Theoretical and Applied Climatology 155 (1), 621-643, 2024 | | 2024 |
A hybrid approach to predict the bearing capacity of a square footing on a sand layer overlying clay E Uncuoglu, L Latifoglu, Z Kaya Geomechanics and Engineering 34 (5), 561-575, 2023 | | 2023 |
Investigation Of Lake Water Level Forecasting Performances Of Subband Decomposition Techniques L Latifoğlu, T HAKTANİR Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 38 (3 …, 2022 | | 2022 |
Derin sinir ağları modeli ile standardize yağış indeksi tahmini L Latifoğlu Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 1-1, 2022 | | 2022 |
The Performance Analysis of Robust Local Mean Mode Decomposition Method for Forecasting of Hydrological Time Series (Jan, 10.1007/s40996-021-00809-2, 2022) L Latifoglu IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING …, 2022 | | 2022 |