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Environment

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Explainable AI and optimized solar power generation forecasting model based on environmental conditions.

PloS one
This paper proposes a model called X-LSTM-EO, which integrates explainable artificial intelligence (XAI), long short-term memory (LSTM), and equilibrium optimizer (EO) to reliably forecast solar power generation. The LSTM component forecasts power ge...

The environmental impact of AI in the lab: a double-edged sword?

BioTechniques
Computational tools, particularly AI, are becoming more ubiquitous in scientific research; but what impact do they have on the environment?[Formula: see text].

Analyzing intelligent tourism development and public services based on a fuzzy genetic hybrid system to promote environmental and cultural values.

PloS one
Environmental, cultural, and public service-dependent factors encourage the development of a country's tourism. In recent years, automated tourism development using statistical and accumulated data has been exploited to recommend attractive tourist f...

[The environmental impact of digital technology and artificial intelligence, in the era of digital pathology].

Annales de pathologie
While digitization and artificial intelligence represent the future of our specialty, future is also constrained by global warming and overstepping of planetary limits, threatening human health and the functioning of the healthcare system. The report...

Using machine learning to combine genetic and environmental data for maize grain yield predictions across multi-environment trials.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Incorporating feature-engineered environmental data into machine learning-based genomic prediction models is an efficient approach to indirectly model genotype-by-environment interactions. Complementing phenotypic traits and molecular markers with hi...

Artificial intelligence detects awareness of functional relation with the environment in 3 month old babies.

Scientific reports
A recent experiment probed how purposeful action emerges in early life by manipulating infants' functional connection to an object in the environment (i.e., tethering an infant's foot to a colorful mobile). Vicon motion capture data from multiple inf...

Leaf rolling detection in maize under complex environments using an improved deep learning method.

Plant molecular biology
Leaf rolling is a common adaptive response that plants have evolved to counteract the detrimental effects of various environmental stresses. Gaining insight into the mechanisms underlying leaf rolling alterations presents researchers with a unique op...

Coping with the tale of natural resources and environmental inequality: an application of the machine learning tools.

Environmental science and pollution research international
With the rising momentum according to the environmentalist voices seeking climate justice for more equity and the importance of encouraging environmental justice mechanisms and tools, in this perspective, the objective of this study is to analyze in ...

Can artificial intelligence improve enterprise environmental performance: Evidence from China.

Journal of environmental management
Artificial intelligence needs to be embraced urgently by enterprises as a means to achieve green development and address the efficiency quagmire in the context of green, low-carbon and sustainable development. To estimate a corporation's pioneering p...

Barley Grain Proteome Assessment Using Multi-Environment Trial Data and Machine Learning.

Journal of agricultural and food chemistry
Proteomics can be used to assess individual protein abundances, which could reflect genotypic and environmental effects and potentially predict grain/malt quality. In this study, 79 barley grain samples (genotype-location-year combinations) from Cali...