Short-term electricity demand forecasting using a hybrid ANFIS–ELM network optimised by an improved parasitism–predation algorithm
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[1] N. Ghadimi,et al. An innovative technique for optimization and sensitivity analysis of a PV/DG/BESS based on converged Henry gas solubility optimizer: A case study , 2023, IET Generation, Transmission & Distribution.
[2] M. Dehghani,et al. A comprehensive review of cyber-attacks and defense mechanisms for improving security in smart grid energy systems: Past, present and future , 2023, Electric Power Systems Research.
[3] M. Mehrandezh,et al. Evolution of smart grids towards the Internet of energy: Concept and essential components for deep decarbonisation , 2022, IET Smart Grid.
[4] Wei Jiang,et al. Optimal economic scheduling of microgrids considering renewable energy sources based on energy hub model using demand response and improved water wave optimization algorithm , 2022, Journal of Energy Storage.
[5] N. Ghadimi,et al. Optimum structure of a combined wind/photovoltaic/fuel cell-based on amended Dragon Fly optimization algorithm: a case study , 2022, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects.
[6] N. Ghadimi,et al. Optimal modeling of combined cooling, heating, and power systems using developed African Vulture Optimization: a case study in watersport complex , 2022, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects.
[7] Navid Razmjooy,et al. Distributed Deep CNN-LSTM Model for Intrusion Detection Method in IoT-Based Vehicles , 2022, Mathematical Problems in Engineering.
[8] Xiaoqing Bai,et al. Multi-Step Short-Term Building Energy Consumption Forecasting Based on Singular Spectrum Analysis and Hybrid Neural Network , 2022, Energies.
[9] E. Amaldi,et al. A Shallow Neural Network Approach for the Short-Term Forcast of Hourly Energy Consumption , 2022, Energies.
[10] G. Wang,et al. A Hybrid Model for Power Consumption Forecasting Using VMD-Based the Long Short-Term Memory Neural Network , 2022, Frontiers in Energy Research.
[11] N. Ghadimi,et al. Breast Cancer Diagnosis by Convolutional Neural Network and Advanced Thermal Exchange Optimization Algorithm , 2021, Computational and mathematical methods in medicine.
[12] Navid Razmjooy. Exergy Analysis of a Fuel Cell Power System and Optimizing it with Fractional-Order Coyote Optimization Algorithm , 2021, SSRN Electronic Journal.
[13] Noradin Ghadimi,et al. Robust multi-objective optimal design of islanded hybrid system with renewable and diesel sources/stationary and mobile energy storage systems , 2021 .
[14] Navid Razmjooy,et al. Interval linear quadratic regulator and its application for speed control of DC motor in the presence of uncertainties. , 2021, ISA transactions.
[15] Navid Razmjooy,et al. New approaches for regulation of solid oxide fuel cell using dynamic condition approximation and STATCOM , 2021 .
[16] M. Dehghani,et al. Blockchain-Based Securing of Data Exchange in a Power Transmission System Considering Congestion Management and Social Welfare , 2020, Sustainability.
[17] K. Jermsittiparsert,et al. An optimal configuration for a battery and PEM fuel cell-based hybrid energy system using developed Krill herd optimization algorithm for locomotive application , 2020 .
[18] Weiqing Wang,et al. Probabilistic decomposition‐based security constrained transmission expansion planning incorporating distributed series reactor , 2020 .
[19] Salem Alkhalaf,et al. Parasitism – Predation algorithm (PPA): A novel approach for feature selection , 2020, Ain Shams Engineering Journal.
[20] K. Jermsittiparsert,et al. New optimal design for a hybrid solar chimney, solid oxide electrolysis and fuel cell based on improved deer hunting optimization algorithm , 2020 .
[21] Karzan Wakil,et al. Optimal bidding and offering strategies of compressed air energy storage: A hybrid robust-stochastic approach , 2019 .
[22] Dongmin Yu,et al. Reliability constraint stochastic UC by considering the correlation of random variables with Copula theory , 2019, IET Renewable Power Generation.
[23] Zhenxing Zhang,et al. Supply-Demand-Based Optimization: A Novel Economics-Inspired Algorithm for Global Optimization , 2019, IEEE Access.
[24] Vijander Singh,et al. A novel nature-inspired algorithm for optimization: Squirrel search algorithm , 2019, Swarm Evol. Comput..
[25] Noradin Ghadimi,et al. Multi-objective energy management in a micro-grid , 2018, Energy Reports.
[26] Alireza Nouri,et al. Planning in Microgrids With Conservation of Voltage Reduction , 2018, IEEE Systems Journal.
[27] Ayda Darvishan,et al. Fuzzy-based heat and power hub models for cost-emission operation of an industrial consumer using compromise programming , 2018, Applied Thermal Engineering.
[28] Haiguo Tang,et al. A new wind power prediction method based on ridgelet transforms, hybrid feature selection and closed-loop forecasting , 2018, Adv. Eng. Informatics.
[29] Muralitharan Krishnan,et al. Neural network based optimization approach for energy demand prediction in smart grid , 2018, Neurocomputing.
[30] Noradin Ghadimi,et al. The price prediction for the energy market based on a new method , 2018 .
[31] Wei Wang,et al. Electricity load forecasting by an improved forecast engine for building level consumers , 2017 .
[32] Yi Yang,et al. Modelling a combined method based on ANFIS and neural network improved by DE algorithm: A case study for short-term electricity demand forecasting , 2016, Appl. Soft Comput..
[33] Noradin Ghadimi,et al. An adaptive neuro-fuzzy inference system for islanding detection in wind turbine as distributed generation , 2015, Complex..
[34] Dan Simon,et al. Biogeography-Based Optimization , 2022 .
[35] Jyh-Shing Roger Jang,et al. ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..
[36] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[37] N. Ghadimi,et al. Model identification of proton-exchange membrane fuel cells based on a hybrid convolutional neural network and extreme learning machine optimized by improved honey badger algorithm , 2022, Sustainable Energy Technologies and Assessments.
[38] M. Zolfaghari,et al. The Electricity Consumption Forecast: Adopting a Hybrid Approach by Deep Learning and Arimax-Garch Models , 2022, SSRN Electronic Journal.
[39] Limin Wang,et al. An improved OIF Elman neural network based on CSO algorithm and its applications , 2021, Comput. Commun..
[40] Noradin Ghadimi,et al. A new prediction model of battery and wind-solar output in hybrid power system , 2019, J. Ambient Intell. Humaniz. Comput..
[41] Mohammad Ghiasi,et al. Extracting Appropriate Nodal Marginal Prices for All Types of Committed Reserve , 2019 .
[42] Wei Gao,et al. Different states of multi-block based forecast engine for price and load prediction , 2019, International Journal of Electrical Power & Energy Systems.
[43] Noradin Ghadimi,et al. Concordant controllers based on FACTS and FPSS for solving wide-area in multi-machine power system , 2016, Journal of Intelligent & Fuzzy Systems.
[44] Robert LIN,et al. NOTE ON FUZZY SETS , 2014 .
[45] S. I. : EFFECTIVE AND EFFICIENT DEEP LEARNING A deep LSTM network for the Spanish electricity consumption forecasting , 2022 .