In this paper, we examine for the first time in the literature the implications of energy policy alternatives for Germany considering the aftermath of coronavirus as well as Electricity and Gas energy supply shortages. ...

This study proposes Q -learning -based iterated greedy (IGQ) algorithms to solve the blocking flowshop scheduling problem with the makespan criterion. Q learning is a model -free machine intelligence technique, which is ...

This article presents a literature review of the past five years of studies using Deep Reinforcement Learning (DRL) and Inverse Reinforcement Learning (IRL) in robotic manipulation tasks. The reviewed articles are examined ...

The population of the world is increasing, and product demand is increasing, making a linear economy ineffective, and therefore, this situation makes the circular economy (CE) a requirement. Economic, social, and environmental ...

This early-stage study explores Gen Z's travel intentions and virtual museum visits in the metaverse by experiencing Egypt, Scotland, and Turkey. The subjective perception and judgment of Gen Z users are investigated in ...

This research aims to investigate the simultaneous effect of smartness and sustainability in port cities. For this purpose, this study introduces the Smart Port Sustainability Index (SPSI) as a key metric for measuring the ...

This study addressed the intricate interplay between meteorological droughts and groundwater level fluctuations in the vicinity of Mount Uludag in Bursa, Turkey. To achieve this, an exhaustive analysis encompassing monthly ...

Uncontrolled sediment deposition in drainage and sewer systems raises unexpected maintenance expenditures. To this end, implementation of an accurate model relying on effective parameters involved is a reliable benchmark. ...

Public transportation usage prediction is valuable for the sustainable development of transportation systems, particularly in crowded megacities. Machine learning technologies are of great interest for predicting public ...