Yazar "Senjyu, Tomonobu" seçeneğine göre listele

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    Data-driven pathways to sustainable energy solutions
    (Springer Nature, 2024) Danish, Mir Sayed Shah; Ahmadi, Mikaeel; Ibrahimi, Abdul Matin; Dinçer, Hasan; Zahra, Shirmohammadi; Khosravy, Mahdi; Senjyu, Tomonobu
    In the rapidly evolving world of the energy sector, harnessing the power of neural networks and machine learning becomes crucial. This chapter deals with the intricate dimensions of datasets, delineating their types, structures, and classifications that are particularly relevant to energy-related applications. A meticulous exploration of data processing techniques, emphasizing preparation, transformation, labeling, and augmentation, is presented. Additionally, a comparative analysis of optimization algorithms clarifies their role in refining energy-focused models. The complexities, computation times, and accuracies of these optimizers are highlighted. Furthermore, the importance of hyperparameters, their optimal configurations, and the significance of adept tuning are underscored. Serving as a comprehensive guide, this chapter aims to bridge the knowledge gap of stakeholders in the energy domain, providing actionable insights into best practices for data-driven decision-making processes.
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    Introduction of biofuels as a way of solving ecological problems
    (Econjournals, 2021) Burkhardt, Thomas; Stepanova, Diana I.; Ratkin, Leonid S.; Ismailov, Ismail; Lavrushin, Oleg Ivanovich; Sokolinskaya, Natalia Ewaldovna; Danish, Mir Sayed Shah; Senjyu, Tomonobu; Yüksel, Serhat; Dinçer, Hasan
    Since environmental issues have become a priority for everyone on the planet, and the fact that growing demand for fossil fuels will soon lead to a reduction in world reserves, except for climate change due to their use and greenhouse gas emissions. The aim of this work was to assess the potential for the introduction of biofuels and find the optimal conditions for the enzymatic hydrolysis of Japonica Rice husk. In addition, evaluate the positive and negative consequences because of the use and implementation of this technology. The methodology used variables: substrate FPU, pH, time, temperature and concentration surfactants using the screening construct obtained statistically, all variables are significant. Then an optimization plan was applied for the variables: pH, FPU and time, dropping those with a lower level of significance. Finally, the best conditions found in previous projects were (pH 5.0, 13 h, and 30 FPU/g of substrate); later, these conditions were applied in experiments to assess the effect of an increase in hydrolyzed cellulose. They use 6%; 8% and 10% of pulp is available with a recycling yield of 74%, 42% and 16%. The community has its own interests in the use of biofuels; therefore, this study provides an opportunity for biofuel producers to reduce environmental, economic, and social costs.