A scheduling method for multi-robot assembly of aircraft structures with soft task precedence constraints

Analyzing recent trends in deep-learning approaches: a review on urban environmental hazards and disaster studies for monitoring, management, and mitigation toward sustainability

“…Deeplearning methods are used by renewable energy sources to maximise renewable energy efficiency and to optimise the performance of solar panels, wind turbines, and other renewable infrastructure. Recent advancements have proven the techniques of deep learning to be very successful since they can surpass human capability and also solve highly computational tasks (Alzubaidi et al 2021;Tereshchuk et al 2021). However, there are some restrictions on using deep learning and these are explained below: Deep-learning approaches serve as catalysts in the pursuit of environmental sustainability, offering transformative solutions that enable data-driven decision-making, resource optimization, and proactive measures to safeguard our planet for future generations.…”