Saima HassanAamir FareedSaima HassanSamir Brahim BelhaouariZahid HalimElevating recommender systems: Cutting-edge transfer learning and embedding solutions.1121402024166Appl. Soft Comput.https://doi.org/10.1016/j.asoc.2024.112140db/journals/asc/asc166.html#FareedHBH24streams/journals/ascNazar K. HusseinMohammed QaraadSouad AmjadM. A. FaragSaima HassanSeyedali MirjaliliMostafa A. El-HosseiniEnhancing feature selection with GMSMFO: A global optimization algorithm for machine learning with application to intrusion detection.1363-13892023July10J. Comput. Des. Eng.4https://doi.org/10.1093/jcde/qwad053db/journals/jcde/jcde10.html#HusseinQAFHME23Muhammad Asim 0002Wali Khan MashwaniSamir Brahim BelhaouariSaima HassanA Novel Genetic Trajectory Planning Algorithm With Variable Population Size for Multi-UAV-Assisted Mobile Edge Computing System.125569-12557920219IEEE Accesshttps://doi.org/10.1109/ACCESS.2021.3111318db/journals/access/access9.html#AsimMBH21Muhammad Hamza AzamMohd Hilmi HasanSaima HassanSaid Jadid AbdulkadirA Novel Approach to Generate Type-1 Fuzzy Triangular and Trapezoidal Membership Functions to Improve the Classification Accuracy.1932202113Symmetry10https://doi.org/10.3390/sym13101932db/journals/symmetry/symmetry13.html#AzamHHA21Samina AminMuhammad Irfan UddinSaima HassanAtif Khan 0002Nidal NasserAbdullah AlharbiHashem AlyamiRecurrent Neural Networks With TF-IDF Embedding Technique for Detection and Classification in Tweets of Dengue Disease.131522-13153320208IEEE Accesshttps://doi.org/10.1109/ACCESS.2020.3009058https://www.wikidata.org/entity/Q114857316db/journals/access/access8.html#AminUHKNAA20Muhammad Shuaib QureshiMuhammad Bilal QureshiMuhammad FayazWali Khan MashwaniSamir Brahim BelhaouariSaima HassanAsadullah ShahA comparative analysis of resource allocation schemes for real-time services in high-performance computing systems.155014772093275202016Int. J. Distributed Sens. Networks8https://doi.org/10.1177/1550147720932750db/journals/ijdsn/ijdsn16.html#QureshiQFMBHS20Mojtaba Ahmadieh KhanesarSaima HassanErik CambriaErdal KayacanA Novel Non-Iterative Parameter Estimation Method for Interval Type-2 Fuzzy Neural Networks Based on a Dynamic Cost Function.1-62019FUZZ-IEEEhttps://doi.org/10.1109/FUZZ-IEEE.2019.8858985conf/fuzzIEEE/2019db/conf/fuzzIEEE/fuzzIEEE2019.html#KhanesarHCK19Saima HassanMojtaba Ahmadieh KhanesarJafreezal JaafarAbbas KhosraviOptimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm.1001-1014201829Neural Comput. Appl.4https://doi.org/10.1007/s00521-016-2503-5db/journals/nca/nca29.html#HassanKJK18Saima HassanMojtaba Ahmadieh KhanesarJafreezal JaafarAbbas KhosraviComparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS.130-144201751Appl. Soft Comput.https://doi.org/10.1016/j.asoc.2016.11.015db/journals/asc/asc51.html#HassanKJK17Saima HassanMojtaba Ahmadieh KhanesarAmin HajizadehAbbas KhosraviHybrid multi-objective forecasting of solar photovoltaic output using Kalman filter based interval type-2 fuzzy logic system.1-62017FUZZ-IEEEhttps://doi.org/10.1109/FUZZ-IEEE.2017.8015733conf/fuzzIEEE/2017db/conf/fuzzIEEE/fuzzIEEE2017.html#HassanKHK17Saima HassanMojtaba Ahmadieh KhanesarErdal KayacanJafreezal JaafarAbbas KhosraviOptimal design of adaptive type-2 neuro-fuzzy systems: A review.134-143201644Appl. Soft Comput.https://doi.org/10.1016/j.asoc.2016.03.023db/journals/asc/asc44.html#HassanKKJK16Saima HassanMojtaba Ahmadieh KhanesarJafreezal JaafarAbbas KhosraviA multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems.155-1602016SMChttps://doi.org/10.1109/SMC.2016.7844235conf/smc/2016db/conf/smc/smc2016.html#HassanKJK16Saima HassanAbbas KhosraviJafreezal JaafarMojtaba Ahmadieh KhanesarHybrid Model for the Training of Interval Type-2 Fuzzy Logic System.644-6532015ICONIP (1)https://doi.org/10.1007/978-3-319-26532-2_71conf/iconip/2015-1db/conf/iconip/iconip2015-1.html#HassanKJK15Saima HassanAbbas KhosraviJafreezal JaafarTraining of interval type-2 fuzzy logic system using extreme learning machine for load forecasting.87:1-87:52015IMCOMhttps://doi.org/10.1145/2701126.2701177conf/icuimc/2015db/conf/icuimc/imcom2015.html#HassanKJ14Saima HassanAbbas KhosraviJafreezal JaafarMuhammad Qamar RazaElectricity load and price forecasting with influential factors in a deregulated power industry.79-842014SoSEhttps://doi.org/10.1109/SYSOSE.2014.6892467conf/sysose/2014db/conf/sysose/sysose2014.html#HassanKJR14Saima HassanAbbas KhosraviJafreezal JaafarNeural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting.1-62013IJCNNhttps://doi.org/10.1109/IJCNN.2013.6707005conf/ijcnn/2013db/conf/ijcnn/ijcnn2013.html#HassanKJ13Saima HassanAbbas KhosraviJafreezal JaafarBayesian Model Averaging of Load Demand Forecasts from Neural Network Models.3192-31972013SMChttps://doi.org/10.1109/SMC.2013.544conf/smc/2013db/conf/smc/smc2013.html#HassanKJ13Saima HassanAbbas KhosraviJafreezal JaafarVariance-Covariance Based Weighing for Neural Network Ensembles.3214-32192013SMChttps://doi.org/10.1109/SMC.2013.548conf/smc/2013db/conf/smc/smc2013.html#HassanKJ13aSaima HassanAbbas KhosraviJafreezal JaafarSamir B. BelhaouariLoad Forecasting Accuracy through Combination of Trimmed Forecasts.152-1592012ICONIP (1)https://doi.org/10.1007/978-3-642-34475-6_19conf/iconip/2012-1db/conf/iconip/iconip2012-1.html#HassanKJB12Said Jadid AbdulkadirAbdullah AlharbiHashem AlyamiSamina AminSouad AmjadMuhammad Asim 0002Muhammad Hamza AzamSamir Brahim BelhaouariSamir B. BelhaouariErik CambriaMostafa A. El-HosseiniM. A. FaragAamir FareedMuhammad FayazAmin HajizadehZahid HalimMohd Hilmi HasanNazar K. HusseinJafreezal JaafarErdal KayacanAtif Khan 0002Mojtaba Ahmadieh KhanesarAbbas KhosraviWali Khan MashwaniSeyedali MirjaliliNidal NasserMohammed QaraadMuhammad Bilal QureshiMuhammad Shuaib QureshiMuhammad Qamar RazaAsadullah ShahMuhammad Irfan Uddin
