سامانه پژوهشی دانشگاه شهید مدنی آذربایجان | حسين عباسي مهر

نام و نام خانوادگی	حسین عباسی مهر
شغل	عضو هیئت علمی دانشگاه شهید مدنی آذربایجان / دانشکده فناوری اطلاعات و مهندسی کامپیوتر / گروه فناوری اطلاعات و ارتباطات
تحصیلات	دکترای تخصصی / مهندسی فناوری اطلاعات
مرتبه علمی	دانشیار
صفحه شخصی	[Google Scholar] [Scopus] [ResearchGate] [Web Of Science] [وب‌سایت شخصی]
پست الکترونیک	abbasimehr [at] azaruniv [dot] ac [dot] ir

	عنوان	مجله
1	Deep time-series clustering via evolutionary learning and graph-based manifold learning	INFORMATION PROCESSING & MANAGEMENT - (2025) 1-22
2	محلی سازی مدل های پیش بینی سراسری با یک رویکرد خوشه بندی	مدیریت مهندسی و رایانش نرم 11 (1404) 155-134
3	Localized Global Time Series Forecasting Models Using Evolutionary Neighbor-Aided Deep Clustering Method	JOURNAL OF FORECASTING - (2025) 1-18
4	Big time series data forecasting based on deep autoencoding and clustering	Cluster Computing-The Journal of Networks Software Tools and Applications - (2025) 1-26
5	Localized global models using autoencoder-based clustering to forecast related time series	International Journal of Data Science and Analytics - (2025) 1-22
6	A novel hybrid model to forecast seasonal and chaotic time series	EXPERT SYSTEMS WITH APPLICATIONS 239 (2024) 1-19
7	ارائه مدلی جهت پیش بینی ارتباط بین واحدهای دانشی در وب سایت های پرسش و پاسخ برنامه نویسی با استفاده از تکنیک های یادگیری عمیق: مطالعه موردی Stack Overflow	مهندسی برق دانشگاه تبریز - (1402) 1-10
8	A novel featurization methodology using JaGen algorithm for time series forecasting with deep learning techniques	EXPERT SYSTEMS WITH APPLICATIONS - (2023) 1-14
9	Social Media Value Creation Practices and Interactivity of Electronic Word of Mouth Systems	journal of information technology management 15 (2023) 73-91
10	A novel combined approach based on deep Autoencoder and deep classifiers for credit card fraud detection	EXPERT SYSTEMS WITH APPLICATIONS 217 (2023) 1-11
11	A novel XGBoost-based featurization approach to forecast renewable energy consumption with deep learning models	Sustainable Computing-Informatics & Systems 38 (2023) 1-11
12	مدل جدید پیش بینی چند گامی تقاضا با استفاده از روش های یادگیری عمیق و تکنیک های داده افزایی سری زمانی	فناوری اطلاعات و ارتباطات ایران 14 (1401) 1-11
13	A novel time series clustering method with fne-tuned support vector regression for customer behavior analysis	EXPERT SYSTEMS WITH APPLICATIONS 204 (2022) 1-12
14	پیش بینی شباهت متن با استفاده از یک شبکه عصبی سیامی مبتنی بر شبکه عمیق و ویژگی های شباهت لغوی	علوم رایانش و فناوری اطلاعات 20 (1401) 11-19
15	An analytical framework based on the recency, frequency, and monetary model and time series clustering techniques for dynamic segmentation	EXPERT SYSTEMS WITH APPLICATIONS 192 (2022) 1-11
16	A novel approach based on combining deep learning models with statistical methods for COVID-19 time series forecasting	NEURAL COMPUTING & APPLICATIONS - (2021) 1-15
17	Improving Churn Prediction using Imperialist Competitive Algorithm for Feature Selection in Telecom	International Journal of Business Information Systems - (2021) 1-13
18	Improving the performance of deep learning models using statistical features: The case study of COVID-19 forecasting	MATHEMATICAL METHODS IN THE APPLIED SCIENCES DOI (2021) 1-15
19	Improving time series forecasting using LSTM and attention models	Journal of Ambient Intelligence and Humanized Computing vol-ahead (2021) 1-19
20	Prediction of COVID-19 confirmed cases combining deep learning methods and Bayesian optimization	CHAOS SOLITONS & FRACTALS vol-ahead (2020) 1-14
21	A hybrid framework for ranking reviewers based on interval type-2 fuzzy AHP and VIKOR	International Journal Of Intelligent Engineering Informatics 8 (2020) 95 - 116
22	Improving demand forecasting with LSTM by taking into account the seasonality of data	Journal of Applied Research on Industrial Engineering 7 (2020) 177-189
23	A new framework for predicting customer behavior in terms of RFM by considering the temporal aspect based on time series techniques	Journal of Ambient Intelligence and Humanized Computing vol-ahead (2020) 1-19
24	An optimized model using LSTM network for demand forecasting	COMPUTERS & INDUSTRIAL ENGINEERING 143 (2020) 1-13
25	A new methodology for customer behavior analysis using time series clustering A case study on a bank’s customers	KYBERNETES vol-ahead (2019) --
26	A combined approach based on fuzzy AHP and fuzzy inference system to rank reviewers in online communities	Turkish Journal of Electrical Engineering and Computer Sciences 25 (2017) 862-876
27	A novel interval type-2 fuzzy AHP-TOPSIS approach for ranking reviewers in online communities	Scientia Iranica 23 (2016) 2355-2373
28	Trust Prediction in Online Communities Employing Neurofuzzy Approach	APPLIED ARTIFICIAL INTELLIGENCE 29 (2015) 733-751
29	New Approach to Compute a Realistic Credibility Rank for Reviewers Using Fuzzy Inference	International Journal of Information and Communication Technology Research (IJICTR) پژوهشگاه فضای مجازی 7 (1393) 63-74
30	A Comparative Assessment of the Performance of Ensemble Learning in Customer Churn Prediction	International Arab Journal of Information Technolo 11 (2014) 599-606
31	Combining Data Mining and Group Decision Making in Retailer Segmentation Based on LRFMP Variables	بینالمللی مهندسی صنایع و مدیریت تولید (بین المللی علوم مهندسی سابق) ـ دانشگاه علم و صنعت International Journal of Industrial Engineering and Productional Research 25 (1393) 197-206
32	A framework for identification of high-value customers by including social network based variables for churn prediction using neuro-fuzzy techniques	INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 51 (2013) 1279-1294
33	Integrating AHP and Data Mining for Effective Retailer Segmentation Based on Retailer Lifetime Value	دانشگاه آزاد اسلامی واحد قزوین Journal of optimization in Industrial Engineering 11 (1391) 25-31
34	determination of Algorithms Making Balance Between Accuracy and comprehensibility in churn Prediction Setting	International Journal of Information Retrieval Research (IJIRR) 1 (2011) 39-54

حسین عباسی مهر