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 | Competency |
|---|---|
| English | Can read, write, speak, understand spoken and peer review |
| Persian | Can read, write, speak, understand spoken and peer review |
| Date | Institution name | Country | Title |
|---|---|---|---|
| 2005 - 2008 | Islamic Azad University, Mashhad(IAUM) | Iran | Master |
| 2001 - 2005 | Yazd University | Iran | Bachelor |
| 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. Scopus33 |
| 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. 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, 14(11), 20 pages. Scopus18 |
| 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. Scopus7 Europe PMC2 |
| 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. 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. Scopus10 |
| 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. Scopus47 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. Scopus17 WoS3 |
| 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. Scopus46 WoS18 |
| 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. Scopus50 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. Scopus34 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. Scopus29 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. Scopus23 |
| 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. Scopus33 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. Scopus46 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. Scopus60 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. Scopus31 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. Scopus10 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. Scopus7 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. 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. WoS2 |
| 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. 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. Scopus10 WoS1 Europe PMC2 |
| 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. Scopus4 |
| 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. Scopus12 WoS5 |
| 2021 | Schlueter, M., Neshat, M., Wahib, M., Munetomo, M., & Wagner, M. (2021). GTOPX space mission benchmarks. SoftwareX, 14, 1-10. Scopus9 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. Scopus175 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. Scopus94 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. Scopus19 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. Scopus16 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. Scopus25 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. Scopus23 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. 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. 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. Scopus23 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. Scopus24 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. Scopus45 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. Scopus23 WoS14 |
| 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. Scopus24 WoS16 |
| 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. Scopus55 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. Scopus29 WoS14 |
| 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. |
| 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. 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. 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. 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. 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. 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). 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. 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. Scopus384 WoS246 |
| 2013 | Neshat, M. (2013). FAIPSO: Fuzzy adaptive informed particle swarm optimization. Neural Computing and Applications, 23(SUPPL1), 95-116. 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. Scopus88 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. Scopus16 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. 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. Scopus55 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. Scopus11 |
| 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. Scopus28 |
| 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 | 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 Scopus5 |
| 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 |
| 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 Scopus1 |
| 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 Scopus18 |
| 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 Scopus24 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 Scopus26 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 Scopus41 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 Scopus16 |
| 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. Scopus143 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 Scopus51 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 |
| Year | Citation |
|---|---|
| 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.. |
| 2019 | Neshat, M., Alexander, B., & Simpson, A. R. (2019). Covariance Matrix Adaptation Greedy Search Applied to Water Distribution System Optimization.. |
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