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ORCIDHossein Abbasimehr
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2020 – today
- 2024
[j17]Hossein Abbasimehr
, Ali Noshad, Reza Paki:
A novel featurization methodology using JaGen algorithm for time series forecasting with deep learning techniques. Expert Syst. Appl. 235: 121279 (2024)- [j16]Hossein Abbasimehr, Amirreza Behboodi, Aram Bahrini:
A novel hybrid model to forecast seasonal and chaotic time series. Expert Syst. Appl. 239: 122461 (2024) - [j15]Hossein Abbasimehr, Aram Bahrini:
Improving churn prediction using imperialist competitive algorithm for feature selection in telecom. Int. J. Bus. Inf. Syst. 45(4): 490-502 (2024) - 2023
- [j14]Hosein Fanai, Hossein Abbasimehr:
A novel combined approach based on deep Autoencoder and deep classifiers for credit card fraud detection. Expert Syst. Appl. 217: 119562 (2023) - [j13]Hossein Abbasimehr, Reza Paki, Aram Bahrini:
A novel XGBoost-based featurization approach to forecast renewable energy consumption with deep learning models. Sustain. Comput. Informatics Syst. 38: 100863 (2023) - [i1]Aram Bahrini, Mohammadsadra Khamoshifar, Hossein Abbasimehr, Robert J. Riggs, Maryam Esmaeili, Rastin Mastali Majdabadkohne, Morteza Pasehvar:
ChatGPT: Applications, Opportunities, and Threats. CoRR abs/2304.09103 (2023) - 2022
- [j12]Hossein Abbasimehr, Aram Bahrini:
An analytical framework based on the recency, frequency, and monetary model and time series clustering techniques for dynamic segmentation. Expert Syst. Appl. 192: 116373 (2022) - [j11]Hossein Abbasimehr, Farzam Sheikh Baghery:
A novel time series clustering method with fine-tuned support vector regression for customer behavior analysis. Expert Syst. Appl. 204: 117584 (2022) - [j10]Hossein Abbasimehr, Reza Paki:
Improving time series forecasting using LSTM and attention models. J. Ambient Intell. Humaniz. Comput. 13(1): 673-691 (2022) - [j9]Hossein Abbasimehr, Reza Paki, Aram Bahrini:
A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting. Neural Comput. Appl. 34(4): 3135-3149 (2022) - 2021
- [j8]Hossein Abbasimehr, Mostafa Shabani:
A new framework for predicting customer behavior in terms of RFM by considering the temporal aspect based on time series techniques. J. Ambient Intell. Humaniz. Comput. 12(1): 515-531 (2021) - [j7]Hossein Abbasimehr, Mostafa Shabani:
A new methodology for customer behavior analysis using time series clustering: A case study on a bank's customers. Kybernetes 50(2): 221-242 (2021) - 2020
- [j6]Hossein Abbasimehr, Mostafa Shabani, Mohsen Yousefi:
An optimized model using LSTM network for demand forecasting. Comput. Ind. Eng. 143: 106435 (2020) - [j5]Hossein Abbasimehr, Esmaeil Nourani, Mostafa Shabani:
A hybrid framework for ranking reviewers based on interval type-2 fuzzy AHP and VIKOR. Int. J. Intell. Eng. Informatics 8(2): 95-116 (2020)
2010 – 2019
- 2017
- [j4]Hossein Abbasimehr, Mohammad Jafar Tarokh:
A combined approach based on fuzzy AHP and fuzzy inference system to rank reviewers in online communities. Turkish J. Electr. Eng. Comput. Sci. 25: 862-876 (2017) - 2015
- [j3]Hossein Abbasimehr, Mohammad Jafar Tarokh:
Trust Prediction in Online Communities Employing Neurofuzzy Approach. Appl. Artif. Intell. 29(7): 733-751 (2015) - 2014
- [j2]Hossein Abbasimehr, Mostafa Setak, Mohammad Jafar Tarokh:
A comparative assessment of the performance of ensemble learning in customer churn prediction. Int. Arab J. Inf. Technol. 11(6): 599-606 (2014) - 2011
- [j1]Hossein Abbasimehr, Mohammad Jafar Tarokh, Mostafa Setak:
Determination of Algorithms Making Balance Between Accuracy and Comprehensibility in Churn Prediction Setting. Int. J. Inf. Retr. Res. 1(2): 39-54 (2011)
Coauthor Index
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