AIMC Topic: Conservation of Natural Resources

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Sustainable development with Artificial Intelligence: Examining the absorptive capacity pathways to green innovation.

Journal of environmental management
Artificial intelligence holds a lot of promise in tackling global societal challenges. However, there is still no consensus on how companies can effectively harness AI to promote green innovation (GI). We develop a moderated mediation model grounded ...

A novel deep learning-based floating garbage detection approach and its effectiveness evaluation in environmentally sustainable development.

Journal of environmental management
Floating garbage removal is an essential environmental strategy to reduce water pollution and achieve environmental sustainability, and it is a pressing issue for global ecological restoration. Under the interference of complex environments, floating...

Understanding and predicting animal movements and distributions in the Anthropocene.

The Journal of animal ecology
Predicting animal movements and spatial distributions is crucial for our comprehension of ecological processes and provides key evidence for conserving and managing populations, species and ecosystems. Notwithstanding considerable progress in movemen...

Optimization of Decision Support Technology for Offshore Oil Condition Monitoring with Carbon Neutrality as the Goal in the Enterprise Development Process.

PloS one
This study aims to explore the integration of the Faster R-CNN (Region-based Convolutional Neural Network) algorithm from deep learning into the MobileNet v2 architecture, within the context of enterprises aiming for carbon neutrality in their develo...

Evaluating the change and trend of construction land in Changsha City based GeoSOS-FLUS model and machine learning methods.

Scientific reports
This study systematically analyzes the land use changes in Changsha City from 2000 to 2023. Three classification models-Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and Artificial Neural Network (ANN) were employed to evaluate the accu...

Optimizing deep neural networks for high-resolution land cover classification through data augmentation.

Environmental monitoring and assessment
This study presents an innovative approach to high-resolution land cover classification using deep learning, tackling the challenge of working with an exceptionally small dataset. Manual annotation of land cover data is both time-consuming and labor-...

Forecasting deforestation and carbon loss across New Guinea using machine learning and cellular automata.

The Science of the total environment
The island of New Guinea harbors some of the world's most biologically diverse and highly endemic tropical ecosystems. Nevertheless, progressing land-use change in the region threatens their integrity, which will adversely affect their biodiversity a...

The nexus of artificial intelligence and sustainability performance: Unveiling the impact of supply chain transparency and customer pressure on ethical conduct.

Journal of environmental management
Drawing on the Resource-Based View (RBV) and Stakeholder Theory, this study tests construct relationships that bring about means of improving corporate sustainability performance (CSP) via artificial intelligence (AI) technology and accountable socio...

An optimized machine learning framework for predicting and interpreting corporate ESG greenwashing behavior.

PloS one
The accurate prediction and interpretation of corporate Environmental, Social, and Governance (ESG) greenwashing behavior is crucial for enhancing information transparency and improving regulatory effectiveness. This paper addresses the limitations i...

Reducing food waste in the HORECA sector using AI-based waste-tracking devices.

Waste management (New York, N.Y.)
This study assesses the effectiveness of an intervention employing an AI-based, fully automatic waste-tracking system for food waste reduction in HORECA establishments. Waste-tracking devices were installed in a restaurant within a holiday resort and...