Being declared a global emergency, the COVID-19 pandemic has taken many lives, threatened livelihoods and businesses around the world. The energy industry, in particular, has experienced tremendous pressure resulting from the pandemic. In response to such a challenge, the development of sustainable resources and renewable energy infrastructure has demonstrated its potential as a promising and effective strategy. To sufficiently address the effect of COVID-19 on renewable energy development strategies, short-term policy priorities should be identified, while mid-term and long-term action plans should be formulated in achieving the well-defined renewable energy targets and progress towards a more sustainable energy future. In this review, opportunities, challenges, and significant impacts of the COVID-19 pandemic on current and future sustainable energy strategies were analyzed in detail; while drawing from experiences in identifying reasonable behaviors, orientating appropriate actions, and policy implications on the sustainable energy trajectory were also mentioned. Indeed, the question is that whether the COVID-19 pandemic will kill us or provide us with a precious lesson on future sustainable energy development.

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Abstract. In this paper, we apply the ideas from [2] to investigate the effect of some semantic based guidance to the crossover operator of GP. We conduct a series of experiments on a family of real-valued symbolic regression problems, examining four different semantic aware crossover operators. One operator considers the semantics of the exchanged subtrees, while the other compares the semantics of the child trees to their parents. Two control operators are adopted which reverse the logic of the semantic equivalence test. The results show that on the family of test problems examined, the (approximate) semantic aware crossover operators can provide performance advantages over the standard subtree crossover adopted in Genetic Programming.

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