Zobrazeno 1 - 10
of 718
pro vyhledávání: '"Honey badger"'
Publikováno v:
Alexandria Engineering Journal, Vol 109, Iss , Pp 71-82 (2024)
Leveraging deep learning (DL) to inverse problems has proven transformative in predicting financial futures, mainly in stock price prediction. In terms of financial markets, where predicting stock price is a challenging inverse problem, DL methods li
Externí odkaz:
https://doaj.org/article/9f6328ce9f314f8aa389787d9d548726
Autor:
Sameera P, Abhay A Deshpande
Publikováno v:
International Journal of Food Properties, Vol 27, Iss 1, Pp 815-837 (2024)
Fruit cultivation plays a pivotal role in improvement of the agricultural economy. Pomegranate is a nutritionally rich fruit that is highly valuable because of its excellent antioxidant properties, richness in vitamins and fiber. Pomegranate is affec
Externí odkaz:
https://doaj.org/article/69fa950d4213411b9f9f0f4192bd9cc0
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-24 (2024)
Abstract This study introduces three soft computing (SC) optimization algorithms aimed at enhancing the efficiency of photovoltaic water pumping systems (PVWPS). These algorithms include the Gorilla Troop Algorithm (GTO), Honey Badger Algorithm (HBA)
Externí odkaz:
https://doaj.org/article/c15d1eb3aa864e9892c4815f18a72e91
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract Permanent magnet synchronous motor (PMSM) drive systems are receiving increasing attention due to their superior control quality and efficiency. Optimizing the control parameters are key to achieve the high-performance operation of PMSMs. Al
Externí odkaz:
https://doaj.org/article/716399da669d4b7d8379deb7182e17e5
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-34 (2024)
Abstract The global surge in electric vehicle (EV) adoption has driven significant research into electric vehicle charging stations (EVCS) due to their environmentally friendly attributes, including low CO₂ emissions. However, integrating EVCS into
Externí odkaz:
https://doaj.org/article/30e32dc583d94e7eb1af3e3e496db8a6
Publikováno v:
Underground Space, Vol 18, Iss , Pp 273-294 (2024)
This study aims to predict the migration time of toxic fumes induced by excavation blasting in underground mines. To reduce numerical simulation time and optimize ventilation design, several back propagation neural network (BPNN) models optimized by
Externí odkaz:
https://doaj.org/article/b263a44d21b8451a956ec7fad73ee218
