AIMC Topic: Biomass

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Unravelling barriers associated with dissemination of large-scale biogas plant with analytical hierarchical process and fuzzy analytical hierarchical process approach: Case study of India.

Bioresource technology
This study explores why large-scale biogas plants are not widely installed in India despite the wealth of biomass resources. The methodology includes an extensive literature review and surveyed biogas experts in different sectors, such as private, pu...

Machine learning-assisted optimization of food-grade spirulina cultivation in seawater-based media: From laboratory to large-scale production.

Journal of environmental management
The shortage of food and freshwater sources threatens human health and environmental sustainability. Spirulina grown in seawater-based media as a healthy food is promising and environmentally friendly. This study used three machine learning technique...

Deep learning artificial neural network framework to optimize the adsorption capacity of 3-nitrophenol using carbonaceous material obtained from biomass waste.

Scientific reports
The presence of toxic chemicals in water, including heavy metals like mercury and lead, organic pollutants such as pesticides, and industrial chemicals from runoff and discharges, poses critical public health and environmental risks leading to severe...

Detecting the interaction between microparticles and biomass in biological wastewater treatment process with Deep Learning method.

The Science of the total environment
Investigating the interaction between influent particles and biomass is basic and important for the biological wastewater treatment. The micro-level methods allow for this, such as the microscope image analysis method with the conventional ImageJ pro...

Artificial Neural Network and Remote Sensing combined to predict the Aboveground Biomass in the Cerrado biome.

Anais da Academia Brasileira de Ciencias
Cerrado is the second largest biome in Brazil, and it is responsible for providing us several ecosystem services, including the functions of storing Carbon and biodiversity conservation. In this study, we developed a modeling approach to predict the ...

Production of high calorific value hydrogen-rich combustible gas by supercritical water gasification of straw assisted by machine learning.

Bioresource technology
This article reveals the basic laws of straw supercritical water gasification (SCWG) and provides basic experimental data for the effective utilization of straw. The paper studied the impact of three operational conditions on the production of high-c...

Low-carbon wastewater treatment and resource recovery of recirculating aquaculture system by immobilized chlorella vulgaris based on machine learning optimization.

Bioresource technology
Immobilized microalgae biotechnologies can conserve water and space by low-carbon wastewater treatment and resource recovery in a recirculating aquaculture system (RAS). However, technical process parameters have been unoptimized considering the mutu...

Accounting for minimum data required to train a machine learning model to accurately monitor Australian dairy pastures using remote sensing.

Scientific reports
Precision in grazing management is highly dependent on accurate pasture monitoring. Typically, this is often overlooked because existing approaches are labour-intensive, need calibration, and are commonly perceived as inaccurate. Machine-learning pro...

Application of triple-branch artificial neural network system for catalytic pellets combustion.

Journal of environmental management
On the international level, it is common to act on reducing emissions from energy systems. However, in addition to industrial emissions, low-stack emissions also make a significant contribution. A good step in reducing its environmental impact, is to...

Assessing global carbon sequestration and bioenergy potential from microalgae cultivation on marginal lands leveraging machine learning.

The Science of the total environment
This comprehensive study unveils the vast global potential of microalgae as a sustainable bioenergy source, focusing on the utilization of marginal lands and employing advanced machine learning techniques to predict biomass productivity. By identifyi...