Determination of Algorithms Making Balance Between Accuracy and Comprehensibility in Churn Prediction Setting. - Hossein Abbasimehr; Mohammad Jafar Tarokh; Mostafa Setak (Int. J. Inf. Retr. Res., 2011)

A comparative assessment of the performance of ensemble learning in customer churn prediction. - Hossein Abbasimehr; Mostafa Setak; Mohammad Jafar Tarokh (Int. Arab J. Inf. Technol., 2014)

Trust Prediction in Online Communities Employing Neurofuzzy Approach. - Hossein Abbasimehr; Mohammad Jafar Tarokh (Appl. Artif. Intell., 2015)

A combined approach based on fuzzy AHP and fuzzy inference system to rank reviewers in online communities. - Hossein Abbasimehr; Mohammad Jafar Tarokh (Turkish J. Electr. Eng. Comput. Sci., 2017)

An optimized model using LSTM network for demand forecasting. - Hossein Abbasimehr; Mostafa Shabani; Mohsen Yousefi (Comput. Ind. Eng., 2020)

A hybrid framework for ranking reviewers based on interval type-2 fuzzy AHP and VIKOR. - Hossein Abbasimehr; Esmaeil Nourani; Mostafa Shabani (Int. J. Intell. Eng. Informatics, 2020)

A new framework for predicting customer behavior in terms of RFM by considering the temporal aspect based on time series techniques. - Hossein Abbasimehr; Mostafa Shabani (J. Ambient Intell. Humaniz. Comput., 2021)

A new methodology for customer behavior analysis using time series clustering: A case study on a bank's customers. - Hossein Abbasimehr; Mostafa Shabani (Kybernetes, 2021)

An analytical framework based on the recency, frequency, and monetary model and time series clustering techniques for dynamic segmentation. - Hossein Abbasimehr; Aram Bahrini (Expert Syst. Appl., 2022)

A novel time series clustering method with fine-tuned support vector regression for customer behavior analysis. - Hossein Abbasimehr; Farzam Sheikh Baghery (Expert Syst. Appl., 2022)

Improving time series forecasting using LSTM and attention models. - Hossein Abbasimehr; Reza Paki (J. Ambient Intell. Humaniz. Comput., 2022)

A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting. - Hossein Abbasimehr; Reza Paki; Aram Bahrini (Neural Comput. Appl., 2022)

ChatGPT: Applications, Opportunities, and Threats. - Aram Bahrini; Mohammadsadra Khamoshifar; Hossein Abbasimehr; Robert J. Riggs; Maryam Esmaeili; Rastin Mastali Majdabadkohne; Morteza Pasehvar (CoRR, 2023)

A novel XGBoost-based featurization approach to forecast renewable energy consumption with deep learning models. - Hossein Abbasimehr; Reza Paki; Aram Bahrini (Sustain. Comput. Informatics Syst., 2023)

A novel combined approach based on deep Autoencoder and deep classifiers for credit card fraud detection. - Hosein Fanai; Hossein Abbasimehr (Expert Syst. Appl., 2023)

A novel hybrid model to forecast seasonal and chaotic time series. - Hossein Abbasimehr; Amirreza Behboodi; Aram Bahrini (Expert Syst. Appl., 2024)

Improving churn prediction using imperialist competitive algorithm for feature selection in telecom. - Hossein Abbasimehr; Aram Bahrini (Int. J. Bus. Inf. Syst., 2024)

A novel featurization methodology using JaGen algorithm for time series forecasting with deep learning techniques. - Hossein Abbasimehr; Ali Noshad; Reza Paki (Expert Syst. Appl., 2024)

Big time series data forecasting based on deep autoencoding and clustering. - Hossein Abbasimehr; Ali Noshad (Clust. Comput., 2025)