Mehdi Neshat

Mehdi Neshat

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology

I received my bachelor and master degrees from Yazd Univesity (Software Engineering,2005) and IAUM (Mashhad,2008) in Artificial Intelligence. I have been awarded a PhD scholarship (ASI) in the University of Adelaide (Australia) from 2017 to 2020. My main research interests are in investigating and optimizing the real engineering problems such as Wave Energy Converters placement optimization and Water Distribution Systems by bio-inspired optimization techniques like Evolutionary Algorithms and Swarm optimization methods.

1. Optimizing the Wave Energy Converters Positions, Control and Shape parameters

2. Optimizing the Water Distribution Systems design

3. Forecasting the wind speed in wind farms

4. Forecasting and modelling the power output of the wind turbines

  • Language Competencies
    Language Competency
    English Can read, write, speak, understand spoken and peer review
    Persian Can read, write, speak, understand spoken and peer review

  • Education
    Date Institution name Country Title
    2005 - 2008 Islamic Azad University, Mashhad(IAUM) Iran Master
    2001 - 2005 Yazd University Iran Bachelor

  • Journals
    Year Citation
    2024 Majidi Nezhad, M., Neshat, M., Sylaios, G., & Astiaso Garcia, D. (2024). Marine energy digitalization digital twin's approaches. Renewable and Sustainable Energy Reviews, 191, 18 pages.
    DOI Scopus26
    2024 Ghasemi, Z., Neshat, M., Aldrich, C., Karageorgos, J., Zanin, M., Neumann, F., & Chen, L. (2024). An integrated intelligent framework for maximising SAG mill throughput: Incorporating expert knowledge, machine learning and evolutionary algorithms for parameter optimisation. Minerals Engineering, 212, 108733-1-108733-16.
    DOI Scopus4
    2023 Hajam, M. A., Arif, T., Khanday, A. M. U. D., & Neshat, M. (2023). An Effective Ensemble Convolutional Learning Model with Fine-Tuning for Medicinal Plant Leaf Identification. Information (Switzerland), 14(11), 20 pages.
    DOI Scopus13
    2023 Neshat, M., Lee, S., Momin, M. M., Truong, B., van der Werf, J. H. J., & Lee, S. H. (2023). An effective hyper-parameter can increase the prediction accuracy in a single-step genetic evaluation. Frontiers in Genetics, 14, 1-12.
    DOI Scopus4 Europe PMC1
    2023 Majidi Nezhad, M., Neshat, M., Azaza, M., Avelin, A., Piras, G., & Astiaso Garcia, D. (2023). Offshore wind farm layouts designer software's. e-Prime - Advances in Electrical Engineering, Electronics and Energy, 4, 100169.
    DOI Scopus6
    2023 Dehkordi, A. A., Etaati, B., Neshat, M., & Mirjalili, S. (2023). Adaptive Chaotic Marine Predators Hill Climbing Algorithm for Large-Scale Design Optimizations. IEEE Access, 11, 39269-39294.
    DOI Scopus8
    2023 Neshat, M., Nezhad, M. M., Mirjalili, S., Garcia, D. A., Dahlquist, E., & Gandomi, A. H. (2023). Short-term solar radiation forecasting using hybrid deep residual learning and gated LSTM recurrent network with differential covariance matrix adaptation evolution strategy. Energy, 278, 1-21.
    DOI Scopus37 WoS2
    2023 Amini, E., Nasiri, M., Pargoo, N. S., Mozhgani, Z., Golbaz, D., Baniesmaeil, M., . . . Sylaios, G. (2023). Design optimization of ocean renewable energy converter using a combined Bi-level metaheuristic approach. Energy Conversion and Management: X, 19, 1-13.
    DOI Scopus15 WoS3
    2022 Radfar, S., Kianoush, B., Majidi Nezhad, M., & Neshat, M. (2022). Developing an Extended Virtual Blade Model for Efficient Numerical Modeling of Wind and Tidal Farms. Sustainability (Switzerland), 14(21), 17 pages.
    DOI Scopus4
    2022 Dadgar, S., & Neshat, M. (2022). A Novel Hybrid Multi-Modal Deep Learning for Detecting Hashtag Incongruity on Social Media. Sensors, 22(24), 31 pages.
    DOI Scopus8 WoS1 Europe PMC1
    2022 Eslami, M., Neshat, M., & Khalid, S. A. (2022). A Novel Hybrid Sine Cosine Algorithm and Pattern Search for Optimal Coordination of Power System Damping Controllers. Sustainability (Switzerland), 14(1), 1-27.
    DOI Scopus48 WoS33
    2022 Neshat, M., Nezhad, M. M., Sergiienko, N. Y., Mirjalili, S., Piras, G., & Garcia, D. A. (2022). Wave power forecasting using an effective decomposition-based convolutional Bi-directional model with equilibrium Nelder-Mead optimiser. Energy, 256, 1-16.
    DOI Scopus32 WoS2
    2022 Golbaz, D., Asadi, R., Amini, E., Mehdipour, H., Nasiri, M., Etaati, B., . . . Gandomi, A. H. (2022). Layout and design optimization of ocean wave energy converters: A scoping review of state-of-the-art canonical, hybrid, cooperative, and combinatorial optimization methods. Energy Reports, 8, 15446-15479.
    DOI Scopus23 WoS3
    2022 Agostinelli, S., Neshat, M., Majidi Nezhad, M., Piras, G., & Astiaso Garcia, D. (2022). Integrating Renewable Energy Sources in Italian Port Areas towards Renewable Energy Communities. Sustainability (Switzerland), 14(21), 18 pages.
    DOI Scopus18
    2022 Majidi Nezhad, M., Neshat, M., Piras, G., & Astiaso Garcia, D. (2022). Sites exploring prioritisation of offshore wind energy potential and mapping for wind farms installation: Iranian islands case studies. Renewable and Sustainable Energy Reviews, 168, 1-16.
    DOI Scopus30 WoS10
    2022 Amini, E., Mehdipour, H., Faraggiana, E., Golbaz, D., Mozaffari, S., Bracco, G., & Neshat, M. (2022). Optimization of hydraulic power take-off system settings for point absorber wave energy converter. Renewable Energy, 194, 938-954.
    DOI Scopus41 WoS7
    2022 Neshat, M., Majidi Nezhad, M., Mirjalili, S., Piras, G., & Garcia, D. A. (2022). Quaternion convolutional long short-term memory neural model with an adaptive decomposition method for wind speed forecasting: North aegean islands case studies. Energy Conversion and Management, 259, 1-24.
    DOI Scopus50 WoS18
    2022 Majidi Nezhad, M., Heydari, A., Neshat, M., Keynia, F., Piras, G., & Garcia, D. A. (2022). A Mediterranean Sea Offshore Wind classification using MERRA-2 and machine learning models. Renewable Energy, 190, 156-166.
    DOI Scopus28 WoS8
    2022 Mozaffari, S., Amini, E., Mehdipour, H., & Neshat, M. (2022). Flow Discharge Prediction Study Using a CFD-Based Numerical Model and Gene Expression Programming. Water (Switzerland), 14(4), 15 pages.
    DOI Scopus8 WoS2
    2022 Radfar, S., Panahi, R., Nezhad, M. M., & Neshat, M. (2022). A Numerical Methodology to Predict the Maximum Power Output of Tidal Stream Arrays. Sustainability (Switzerland), 14(3), 13 pages.
    DOI Scopus5 WoS4
    2022 Nezhad, M. M., Neshat, M., Piras, G., Garcia, D. A., & Sylaios, G. (2022). Marine Online Platforms of Services to Public End-Users—The Innovation of the ODYSSEA Project. Remote Sensing, 14(3), 20 pages.
    DOI Scopus4 WoS2
    2022 Etaati, B., Dehkordi, A. A., Sadollah, A., El-Abd, M., & Neshat, M. (2022). A Comparative State-of- the-Art Constrained Metaheuristics Framework for TRUSS Optimisation on Shape and Sizing. MATHEMATICAL PROBLEMS IN ENGINEERING, 2022, 13 pages.
    DOI WoS2
    2022 Neshat, M., Mirjalili, S., Sergiienko, N. Y., Esmaeilzadeh, S., Amini, E., Heydari, A., & Garcia, D. A. (2022). Layout optimisation of offshore wave energy converters using a novel multi-swarm cooperative algorithm with backtracking strategy: A case study from coasts of Australia. Energy, 239, 1-29.
    DOI Scopus43 WoS18
    2021 Syah, R., Davarpanah, A., Nasution, M. K. M., Tanjung, F. A., Nezhad, M. M., & Nesaht, M. (2021). A comprehensive thermoeconomic evaluation and multi-criteria optimization of a combined MCFC/TEG system. Sustainability (Switzerland), 13(23), 29 pages.
    DOI Scopus3
    2021 Amini, E., Mehdipour, H., Faraggiana, E., Golbaz, D., Mozaffari, S., Bracco, G., & Neshat, M. (2021). Optimization Study of Hydraulic Power Take-off System for an Ocean Wave Energy Converter.. CoRR, abs/2112.09803.
    2021 Golbaz, D., Asadi, R., Amini, E., Mehdipour, H., Nasiri, M., Nezhad, M. M., . . . Neshat, M. (2021). Ocean Wave Energy Converters Optimization: A Comprehensive Review on
    Research Directions.
    2021 Ceylan, O., Neshat, M., & Mirjalili, S. (2021). Cascaded H-bridge multilevel inverters optimization using adaptive grey wolf optimizer with local search. Electrical Engineering, 106(2), 15 pages.
    DOI Scopus9 WoS5
    2021 Schlueter, M., Neshat, M., Wahib, M., Munetomo, M., & Wagner, M. (2021). GTOPX space mission benchmarks. SoftwareX, 14, 1-10.
    DOI Scopus7 WoS2
    2021 Neshat, M., Nezhad, M. M., Abbasnejad, E., Mirjalili, S., Tjernberg, L. B., Astiaso Garcia, D., . . . Wagner, M. (2021). A deep learning-based evolutionary model for short-term wind speed forecasting: A case study of the Lillgrund offshore wind farm. Energy Conversion and Management, 236, 1-25.
    DOI Scopus161 WoS83
    2021 Neshat, M., Nezhad, M. M., Abbasnejad, E., Mirjalili, S., Groppi, D., Heydari, A., . . . Wagner, M. (2021). Wind turbine power output prediction using a new hybrid neuro-evolutionary method. Energy, 229, 120617-1-120617-24.
    DOI Scopus85 WoS51
    2021 Neshat, M., Sergiienko, N. Y., Mirjalili, S., Nezhad, M. M., Piras, G., & Garcia, D. A. (2021). Multi-mode wave energy converter design optimisation using an improved moth flame optimisation algorithm. Energies, 14(13), 1-17.
    DOI Scopus18 WoS9
    2021 Amini, E., Asadi, R., Golbaz, D., Nasiri, M., Naeeni, S. T. O., Nezhad, M. M., . . . Neshat, M. (2021). Comparative study of oscillating surge wave energy converter performance: a case study for southern coasts of the Caspian Sea. Sustainability (Switzerland), 13(19), 1-21.
    DOI Scopus13 WoS7
    2021 Filom, S., Radfar, S., Panahi, R., Amini, E., & Neshat, M. (2021). Exploring wind energy potential as a driver of sustainable development in the southern coasts of Iran: The importance of wind speed statistical distribution model. Sustainability (Switzerland), 13(14), 1-24.
    DOI Scopus22 WoS7
    2021 Heydari, A., Nezhad, M. M., Neshat, M., Garcia, D. A., Keynia, F., De Santoli, L., & Tjernberg, L. B. (2021). A combined fuzzy gmdh neural network and grey wolf optimization application for wind turbine power production forecasting considering scada data. Energies, 14(12), 1-13.
    DOI Scopus20 WoS13
    2021 Ghobadzadeh, F., & Neshat, M. (2021). A Low-Cost Bandpass Filter Based on Hybrid Spoof Plasmonic Waveguides. IEEE Microwave and Wireless Components Letters, 31(7), 837-840.
    DOI Scopus2 WoS1
    2021 Syah, R., Rezaei, M., Elveny, M., Majidi Nezhad, M., Ramdan, D., Nesaht, M., & Davarpanah, A. (2021). Day-ahead electricity price forecasting using WPT, VMI, LSSVM-based self adaptive fuzzy kernel and modified HBMO algorithm. Scientific Reports, 11(1), 17375.
    DOI Scopus3
    2021 Amini, E., Golbaz, D., Asadi, R., Nasiri, M., Ceylan, O., Nezhad, M. M., & Neshat, M. (2021). A comparative study of metaheuristic algorithms for wave energy converter power take-off optimisation: a case study for Eastern Australia. Journal of Marine Science and Engineering, 9(5), 1-12.
    DOI Scopus22 WoS13
    2021 Nezhad, M. M., Neshat, M., Heydari, A., Razmjoo, A., Piras, G., & Garcia, D. A. (2021). A new methodology for offshore wind speed assessment integrating Sentinel-1, ERA-Interim and in-situ measurement. Renewable Energy, 172, 1301-1313.
    DOI Scopus21 WoS17
    2021 Nezhad, M. M., Neshat, M., Groppi, D., Marzialetti, P., Heydari, A., Sylaios, G., & Garcia, D. A. (2021). A primary offshore wind farm site assessment using reanalysis data: a case study for Samothraki island. Renewable Energy, 172, 667-679.
    DOI Scopus43 WoS27
    2020 Amini, E., Golbaz, D., Amini, F., Nezhad, M. M., Neshat, M., & Garcia, D. A. (2020). A parametric study of wave energy converter layouts in real wave models. Energies, 13(22), 6095.
    DOI Scopus23 WoS14
    2020 Neshat, M., Alexander, B., & Wagner, M. (2020). A hybrid cooperative co-evolution algorithm framework for optimising power take offand placements of wave energy converters. Information Sciences, 534, 218-244.
    DOI Scopus51 WoS32
    2020 Neshat, M., Alexander, B., Sergiienko, N. Y., & Wagner, M. (2020). New insights into position optimization of wave energy converters using hybrid local search. Swarm and Evolutionary Computation, 59, 100744-1-100744-18.
    DOI Scopus24 WoS14
    2020 Neshat, M., Nezhad, M. M., Abbasnejad, E., Groppi, D., Heydari, A., Tjernberg, L. B., . . . Wagner, M. (2020). Hybrid Neuro-Evolutionary Method for Predicting Wind Turbine Power Output.. CoRR, abs/2004.12794.
    2020 Neshat, M., Sergiienko, N. Y., Amini, E., Nezhad, M. M., Garcia, D. A., Alexander, B., & Wagner, M. (2020). A new bi-level optimisation framework for optimising a multi-modewave energy converter design: A case study for the marettimo island, mediterranean sea. Energies, 13(20), 5498.
    DOI Scopus23 WoS16
    2020 Neshat, M., Nezhad, M. M., Abbasnejad, E., Tjernberg, L. B., Garcia, D. A., Alexander, B., & Wagner, M. (2020). An Evolutionary Deep Learning Method for Short-term Wind Speed Prediction: A Case Study of the Lillgrund Offshore Wind Farm.. CoRR, abs/2002.09106.
    2019 Neshat, M., Alexander, B., & Simpson, A. R. (2019). Covariance Matrix Adaptation Greedy Search Applied to Water Distribution System Optimization.. CoRR, abs/1909.04846.
    2016 Neshat, M., Tabatabi, M., Zahmati, E., & Shirdel, M. (2016). A hybrid fuzzy knowledge-based system for forest fire risk forecasting. International Journal of Reasoning-based Intelligent Systems, 8(3-4), 132-154.
    DOI Scopus2
    2016 Neshat, M., & Ahmadi, M. (2016). Recognising the kind of cloud using a new fuzzy knowledge-based system. International Journal of Reasoning-based Intelligent Systems, 8(3-4), 168-180.
    DOI Scopus1
    2016 Pourahmad, A., Neshat, M., & Hasani, M. (2016). Using LibQUAL model for improving the level of students' satisfaction from quality of services in academic libraries: a case study in North Khorasan Province, Iran. Journal of Information and Knowledge Management, 15(1), 1650011-1-1650011-12.
    DOI Scopus9 WoS3
    2016 Neshat, M., Pourahmad, A. A., & Hasani, M. R. (2016). Designing an adaptive neuro fuzzy inference system for prediction of customers satisfaction. Journal of Information and Knowledge Management, 15(4), 21 pages.
    DOI Scopus1
    2016 Neshat, M., Sepidname, G., Mehri, E., & Zalimoghadam, A. (2016). The review of soft computing applications in humanitarian demining robots design. Indian Journal of Science and Technology, 9(4), 1-13.
    DOI Scopus3
    2015 Neshat, M., Sepidname, G., Eizi, A., & Amani, A. (2015). A new skin color detection approach based on fuzzy expert system. Indian Journal of Science and Technology, 8(21).
    DOI Scopus12
    2015 Neshat, M., & Sepidname, G. (2015). A new hybrid optimization method inspired from swarm intelligence: Fuzzy adaptive swallow swarm optimization algorithm (FASSO). Egyptian Informatics Journal, 16(3), 339-350.
    DOI Scopus20 WoS10
    2014 Neshat, M., Sepidnam, G., Sargolzaei, M., & Toosi, A. N. (2014). Artificial fish swarm algorithm: a survey of the state-of-the-art, hybridization, combinatorial and indicative applications. Artificial Intelligence Review, 42(4), 965-997.
    DOI Scopus372 WoS246
    2013 Neshat, M. (2013). FAIPSO: Fuzzy adaptive informed particle swarm optimization. Neural Computing and Applications, 23(SUPPL1), 95-116.
    DOI Scopus23 WoS18
    2013 Neshat, M., Sepidnam, G., & Sargolzaei, M. (2013). Swallow swarm optimization algorithm: A new method to optimization. Neural Computing and Applications, 23(2), 429-454.
    DOI Scopus86 WoS52
    2012 Neshat, M., Adeli, A., Sepidnam, G., & Sargolzaei, M. (2012). Predication of concrete mix design using adaptive neural fuzzy inference systems and fuzzy inference systems. International Journal of Advanced Manufacturing Technology, 63(1-4), 373-390.
    DOI Scopus15 WoS12
    2012 Neshat, M., Sargolzaei, M., Masoumi, A., & Najaran, A. (2012). A New kind of PSO: Predator particle swarm optimization. International Journal on Smart Sensing and Intelligent Systems, 5(2), 521-539.
    DOI Scopus8 WoS5
    2012 Neshat, M., Adeli, A., Sepidnam, G., Sargolzaei, M., & Toosi, A. N. (2012). A review of Artificial Fish Swarm Optimization methods and applications. International Journal on Smart Sensing and Intelligent Systems, 5(1), 107-148.
    DOI Scopus52 WoS32
    2012 Neshat, M., Sargolzaei, M., Najaran, A., & Adeli, A. (2012). The new method of adaptive CPU scheduling using Fonseca and Fleming's Genetic Algorithm. Journal of Theoretical and Applied Information Technology, 37(1), 1-16.
    Scopus10
    2012 Neshat, M., Yazdi, S. F., Yazdani, D., & Sargolzaei, M. (2012). A new cooperative algorithm based on PSO and K-means for data clustering. Journal of Computer Science, 8(2), 188-194.
    DOI Scopus28

  • Conference Papers
    Year Citation
    2024 Ghasemi, Z., Neshat, M., Aldrich, C., Karageorgos, J., Zanin, M., Neumann, F., & Chen, L. (2024). Enhanced Genetic Programming Models with Multiple Equations for Accurate Semi-Autogenous Grinding Mill Throughput Prediction. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2024) (pp. 1-9). Yokohama, Japan: IEEE.
    DOI
    2023 Zrubka, Z., Holgyesi, A., Neshat, M., Nezhad, H. M., Mirjalili, S., Kovacs, L., . . . Gulacsi, L. (2023). Towards a single goodness metric of clinically relevant, accurate, fair and unbiased machine learning predictions of health-related quality of life. In INES 2023 - 27th IEEE International Conference on Intelligent Engineering Systems 2023, Proceedings (pp. 285-290). Online: IEEE.
    DOI Scopus1
    2023 Dadgar, S., & Neshat, M. (2023). Comparative Hybrid Deep Convolutional Learning Framework with Transfer Learning for Diagnosis of Lung Cancer. In A. Abraham, T. Hanne, N. Gandhi, P. Manghirmalani Mishra, A. Bajaj, & P. Siarry (Eds.), Proceedings of the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022) Vol. 648 (pp. 296-305). Online: Springer Nature Switzerland.
    DOI Scopus3
    2022 Agostinelli, S., Neshat, M., Nezhad, M. M., Piras, G., & Garcia, D. A. (2022). METHODOLOGY FRAMEWORK FOR PRIORITISATION OF RENEWABLE ENERGY SOURCES IN PORT AREAS. In WIT Transactions on the Built Environment Vol. 212 (pp. 113-121). Online: WIT Press.
    DOI
    2021 Burramukku, B., Ceylan, O., & Neshat, M. (2021). Power output prediction of wave farms using fully connected networks. In 2021 56th International Universities Power Engineering Conference: Powering Net Zero Emissions, UPEC 2021 - Proceedings (pp. 6 pages). Middlesbrough, United Kingdom: IEEE.
    DOI Scopus1
    2021 Ceylan, O., Neshat, M., & Mirjalili, S. (2021). Optimization of multilevel inverters using novelty-driven Multi-verse Optimization algorithm. In 2021 56th International Universities Power Engineering Conference: Powering Net Zero Emissions, UPEC 2021 - Proceedings (pp. 1-6). online: IEEE.
    DOI
    2020 Sergiienko, N. Y., Neshat, M., Silva, L. S. P. D., Alexander, B., & Wagner, M. (2020). Design optimisation of a multi-mode wave energy converter. In Proceedings of the 39th International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2020) Vol. 9 (pp. 1-11). Online: American Society of Mechanical Engineers (ASME).
    DOI Scopus16
    2020 Neshat, M., Alexander, B., Sergiienko, N. Y., & Wagner, M. (2020). Optimisation of large wave farms using a multi-strategy evolutionary framework. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO'20) Vol. abs/2003.09594 (pp. 1150-1158). New York: Association for Computing Machinery.
    DOI Scopus17 WoS10
    2019 Neshat, M., Abbasnejad, E., Shi, Q., Alexander, B., & Wagner, M. (2019). Adaptive neuro-surrogate-based optimisation method for wave energy converters placement optimisation. In T. Gedeon, K. W. Wong, & M. Lee (Eds.), Proceedings of the 26th International Conference on Neural Information Processing (ICONIP 2019), as published in Lecture Notes in Computer Science (Neural Information Processing Proceedings, Part II) Vol. 11954 (pp. 353-366). Switzerland: Springer Nature.
    DOI Scopus25 WoS16
    2019 Neshat, M., Alexander, B., Sergiienko, N., & Wagner, M. (2019). A hybrid evolutionary algorithm framework for optimising power take off and placements of wave energy converters. In GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference Vol. abs/1904.07043 (pp. 1293-1301). New York: ACM.
    DOI Scopus19 WoS14
    2018 Neshat, M., Alexander, B., Wagner, M., & Xia, Y. (2018). A detailed comparison of meta-heuristic methods for optimising wave energy converter placements. In H. E. Aguirre, & K. Takadama (Eds.), Proceedings of the 2018 Genetic and Evolutionary Computation Conference as published in GECCO 2018 (pp. 1318-1325). online: ACM.
    DOI Scopus37 WoS26
    2012 Adeli, A., Ghorbani-Rad, A., Zomorodian, M. J., Neshat, M., & Mozaffari, S. (2012). Improving nearest neighbor classification using particle swarm optimization with novel fitness function. In N. T. Nguyen, K. Hoang, & P. Jedrzejowicz (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 7654 LNAI (pp. 365-372). Ho Chi Minh City, VIETNAM: SPRINGER-VERLAG BERLIN.
    DOI Scopus4 WoS3
    2012 Adeli, A., Sinaee, M., Zomorodian, J., & Neshat, M. (2012). Harmony-based feature selection to improve the nearest neighbor classification. In N. Meghanathan, & M. Wozniak (Eds.), ACM International Conference Proceeding Series (pp. 12-18). ACM.
    DOI
    2011 Neshat, M., & Adeli, A. (2011). Designing a fuzzy expert system to predict the concrete mix design. In IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings (pp. 80-85). Univ Ottawa, Ottawa, CANADA: IEEE.
    DOI Scopus9 WoS1
    2010 Neshat, M. (2010). A hybrid method in informed search: Fuzzy simplified memory-bounded a* approach. In Proceedings - 2010 International Conference on Computational Intelligence and Communication Networks, CICN 2010 (pp. 105-109). IEEE.
    DOI
    2010 Rezaei, M., Neshat, M., & Yazdi, H. S. (2010). A new frequency dependent resistor for modeling skin effect of wire and echo cancellation by PSO. In V. Mahadevan, & Z. Jianhong (Eds.), 2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010 Vol. 1 (pp. 573-577). Singapore, SINGAPORE: IEEE.
    DOI Scopus2 WoS1
    2010 Neshat, M., & Zadeh, A. E. (2010). Hopfield neural network and fuzzy hopfield neural network for diagnosis of liver disorders. In 2010 IEEE International Conference on Intelligent Systems, IS 2010 - Proceedings (pp. 162-167). IEEE.
    DOI Scopus14
    2010 Neshat, M., & Rezaei, M. (2010). AIPSO: Adaptive informed particle swarm optimization. In 2010 IEEE International Conference on Intelligent Systems, IS 2010 - Proceedings (pp. 438-443). IEEE.
    DOI Scopus4
    2010 Adeli, A., & Neshat, M. (2010). A Fuzzy Expert System for heart disease diagnosis. In S. I. Ao, O. Castillo, C. Douglas, D. D. Feng, & J. A. Lee (Eds.), Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, IMECS 2010 (pp. 134-139). Hong Kong, PEOPLES R CHINA: INT ASSOC ENGINEERS-IAENG.
    Scopus141 WoS27
    2009 Neshat, M., & Yaghobi, M. (2009). Designing a Fuzzy Expert System of Diagnosing the Hepatitis B Intensity Rate and Comparing it with Adaptive Neural Network Fuzzy System. In S. I. Ao, C. Douglas, W. S. Grundfest, & J. Burgstone (Eds.), WCECS 2009: WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE, VOLS I AND II (pp. 797-+). San Francisco, CA: INT ASSOC ENGINEERS-IAENG.
    WoS6
    2009 Neshat, M., & Yaghobi, M. (2009). FESHDD: Fuzzy expert system for hepatitis B diseases diagnosis. In ICSCCW 2009 - 5th International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control (pp. 1-4). IEEE.
    DOI Scopus3
    2008 Neshat, M., Yaghobi, M., Naghibi, M. B., & Esmaelzadeh, A. (2008). Fuzzy expert system design for diagnosis of liver disorders. In C. Zhao, C. Wu, Y. Wang, & Q. Liu (Eds.), Proceedings - 2008 International Symposium on Knowledge Acquisition and Modeling, KAM 2008 (pp. 252-256). Wuhan, PEOPLES R CHINA: IEEE COMPUTER SOC.
    DOI Scopus50 WoS27
    2008 Neshat, M., Yaghobi, M., & Naghibi, M. (2008). Designing an expert system of liver disorders by using neural network and comparing it with parametric and nonparametric system. In 2008 5th International Multi-Conference on Systems, Signals and Devices, SSD'08 (pp. 202-208). Amman, JORDAN: IEEE.
    DOI Scopus6
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