JCSIS
019928311823 info@jcsis.org
JCSIS

Smart Cities Energy Consumption Forecasting Using Deep Learning and Optimization Algorithms

Narcisa ZlatanLima HongouSofia Arkhstan
Volume 4

Abstract

The integration of deep learning and optimization algorithms is revolutionizing energy consumption forecasting in smart cities, enabling more accurate predictions and efficient energy management. Advanced models such as Long Short-Term Memory (LSTM) networks, Transformer-based architectures, and hybrid approaches combining Seasonal Autoregressive Integrated Moving Average (SARIMA) with Grey Wolf Optimization (GWO) have demonstrated superior performance in capturing complex temporal patterns and seasonal fluctuations in energy usage. For instance, a study employing a GWO-SARIMA-LSTM model achieved a 15% reduction in prediction error, highlighting the effectiveness of hybrid models in enhancing forecasting accuracy citeturn academia19. These methodologies not only improve the reliability of energy demand predictions but also support the development of sustainable and resilient urban infrastructures by facilitating proactive energy management strategies.

Keywords

Smart Cities, Energy Consumption Forecasting, Deep Learning, LSTM, Optimization Algorithms, Sustainable Urban Infrastructure

References

  • [1] El-Kenawy, E. S. M., Ibrahim, A., Mirjalili, S., Eid, M. M., & Hussein, S. E. (2020). Novel feature selection and voting classifier algorithms for COVID-19 classification in CT images. IEEE access, 8, 179317-179335.
  • [2] El-Kenawy, E. S. M., Eid, M. M., Saber, M., & Ibrahim, A. (2020). MbGWO-SFS: Modified binary grey wolf optimizer based on stochastic fractal search for feature selection. IEEE Access, 8, 107635-107649.
  • [3] El-Kenawy, E. S., & Eid, M. (2020). Hybrid gray wolf and particle swarm optimization for feature selection. Int. J. Innov. Comput. Inf. Control, 16(3), 831-844.
  • [4] El-Kenawy, E. S. M., Khodadadi, N., Mirjalili, S., Abdelhamid, A. A., Eid, M. M., & Ibrahim, A. (2024). Greylag goose optimization: nature-inspired optimization algorithm. Expert Systems with Applications, 238, 122147.
  • [5] El-Kenawy, E. S. M., Mirjalili, S., Ibrahim, A., Alrahmawy, M., El-Said, M., Zaki, R. M., & Eid, M. M. (2021). Advanced meta-heuristics, convolutional neural networks, and feature selectors for efficient COVID-19 X-ray chest image classification. Ieee Access, 9, 36019 36037.
  • [6] Abdelhamid, A. A., El-Kenawy, E. S. M., Khodadadi, N., Mirjalili, S., Khafaga, D. S., Alharbi, A. H., ... & Saber, M. (2022). Classification of monkeypox images based on transfer learning and the Al-Biruni Earth Radius Optimization algorithm. Mathematics, 10(19), 3614.
  • [7] Ibrahim, A., Mirjalili, S., El-Said, M., Ghoneim, S. S., Al-Harthi, M. M., Ibrahim, T. F., & El-Kenawy, E. S. M. (2021). Wind speed ensemble forecasting based on deep learning using adaptive dynamic optimization algorithm. IEEE Access, 9, 125787-125804.
  • [8] El-Kenawy, E. S. M., Mirjalili, S., Alassery, F., Zhang, Y. D., Eid, M. M., El-Mashad, S. Y., ... & Abdelhamid, A. A. (2022). Novel meta heuristic algorithm for feature selection, unconstrained functions and engineering problems. IEEE Access, 10, 40536-40555.
  • [9] Abdelhamid, A. A., El-Kenawy, E. S. M., Alotaibi, B., Amer, G. M., Abdelkader, M. Y., Ibrahim, A., & Eid, M. M. (2022). Robust speech emotion recognition using CNN+ LSTM based on stochastic fractal search optimization algorithm. Ieee Access, 10, 49265-49284.
  • [10] Abdollahzadeh, B., Khodadadi, N., Barshandeh, S., Trojovský, P., Gharehchopogh, F. S., El-kenawy, E. S. M., ... & Mirjalili, S. (2024). Puma optimizer (PO): a novel metaheuristic optimization algorithm and its application in machine learning. Cluster Computing, 27(4), 5235-5283.
  • [11] Eid, M. M., El-kenawy, E. S. M., & Ibrahim, A. (2021, March). A binary sine cosine-modified whale optimization algorithm for feature selection. In 2021 National Computing Colleges Conference (NCCC) (pp. 1-6). IEEE.
  • [12] El-Kenawy, E. S. M., Mirjalili, S., Abdelhamid, A. A., Ibrahim, A., Khodadadi, N., & Eid, M. M. (2022). Meta-heuristic optimization and keystroke dynamics for authentication of smartphone users. Mathematics, 10(16), 2912.
  • [13] Abdelhamid, A. A., Towfek, S. K., Khodadadi, N., Alhussan, A. A., Khafaga, D. S., Eid, M. M., & Ibrahim, A. (2023). Waterwheel plant algorithm: a novel metaheuristic optimization method. Processes, 11(5), 1502.
  • [14] Alhussan, A. A., Abdelhamid, A. A., El-Kenawy, E. S. M., Ibrahim, A., Eid, M. M., Khafaga, D. S., & Ahmed, A. E. (2023). A binary waterwheel plant optimization algorithm for feature selection. IEEE Access, 11, 94227-94251.
  • [15] Hassib, E. M., El-Desouky, A. I., Labib, L. M., & El-Kenawy, E. S. M. (2020). WOA+ BRNN: An imbalanced big data classification framework using Whale optimization and deep neural network. soft computing, 24(8), 5573-5592.
  • [16] El-Kenawy, E. S. M., Abdelhamid, A. A., Ibrahim, A., Mirjalili, S., Khodadad, N., Alduailij, M. A., ... & Khafaga, D. S. (2023). Al-Biruni Earth Radius (BER) Metaheuristic Search Optimization Algorithm. Comput. Syst. Sci. Eng., 45(2), 1917-1934.
  • [17] Alharbi, A. H., Towfek, S. K., Abdelhamid, A. A., Ibrahim, A., Eid, M. M., & Khafaga, D. S. & Saber, M.(2023). Diagnosis of Monkeypox Disease Using Transfer Learning and Binary Advanced Dipper Throated Optimization Algorithm. Biomimetics, 8(3), 313.
  • [18] El-Kenawy, E. S. M., Mirjalili, S., Khodadadi, N., Abdelhamid, A. A., Eid, M. M., El-Said, M., & Ibrahim, A. (2023). Feature selection in wind speed forecasting systems based on meta-heuristic optimization. Plos one, 18(2), e0278491.
  • [19] Khodadadi, N., Abualigah, L., El-Kenawy, E. S. M., Snasel, V., & Mirjalili, S. (2022). An archive-based multi-objective arithmetic optimization algorithm for solving industrial engineering problems. IEEE Access, 10, 106673-106698.
  • [20] Eid, M. M., El-Kenawy, E. S. M., Khodadadi, N., Mirjalili, S., Khodadadi, E., Abotaleb, M., ... & Khafaga, D. S. (2022). Meta-heuristic optimization of LSTM-based deep network for boosting the prediction of monkeypox cases. Mathematics, 10(20), 3845.
  • [21] Khodadadi, N., Khodadadi, E., Al-Tashi, Q., El-Kenawy, E. S. M., Abualigah, L., Abdulkadir, S. J., ... & Mirjalili, S. (2023). BAOA: binary arithmetic optimization algorithm with K-nearest neighbor classifier for feature selection. IEEE Access, 11, 94094-94115.
  • [22] Salamai, A. A., El-kenawy, E. S. M., & Abdelhameed, I. (2021). Dynamic voting classifier for risk identification in supply chain 4.0. Computers, Materials & Continua, 69(3).
  • [23] Djaafari, A., Ibrahim, A., Bailek, N., Bouchouicha, K., Hassan, M. A., Kuriqi, A., ... & El-Kenawy, E. S. M. (2022). Hourly predictions of direct normal irradiation using an innovative hybrid LSTM model for concentrating solar power projects in hyper-arid regions. Energy Reports, 8, 15548-15562.
Download