AIMC Topic: Biomass

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Machine learning and statistical physics modeling of tetracycline adsorption using activated carbon derived from Cynometra ramiflora fruit biomass.

Environmental research
The current investigation reports the usage of adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN), the two recognized machine learning techniques in modelling tetracycline (TC) adsorption onto Cynometra ramiflora fruit ...

Machine learning application for predicting key properties of activated carbon produced from lignocellulosic biomass waste with chemical activation.

Bioresource technology
The successful application of gradient boosting regression (GBR) in machine learning to forecast surface area, pore volume, and yield in biomass-derived activated carbon (AC) production underscores its potential for enhancing manufacturing processes....

Improvement of pasture biomass modelling using high-resolution satellite imagery and machine learning.

Journal of environmental management
Robust quantification of vegetative biomass using satellite imagery using one or more forms of machine learning (ML) has hitherto been hindered by the extent and quality of training data. Here, we showcase how ML predictive demonstrably improves when...

Machine learning models for predicting biochar properties from lignocellulosic biomass torrefaction.

Bioresource technology
This study developed six machine learning models to predict the biochar properties from the dry torrefaction of lignocellulosic biomass by using biomass characteristics and torrefaction conditions as input variables. After optimization, gradient boos...

Artificial intelligence methods for modeling gasification of waste biomass: a review.

Environmental monitoring and assessment
Gasification is a highly promising thermochemical process that shows considerable potential for the efficient conversion of waste biomass into syngas. The assessment of the feasibility and comparative advantages of different biomass and waste gasific...

Effects of CO concentration and time on algal biomass film, NO3-N concentration, and pH in the membrane bioreactor: Simulation-based ANN, RSM and NSGA-II.

Journal of environmental management
The practice of aquaculture is associated with the generation of a substantial quantity of effluent. Microalgae must effectively assimilate nitrogen and phosphorus from their surrounding environment for growth. This study modeled the algal biomass fi...

Artificial intelligence to explain the variables that favor the cyanobacteria steady-state in tropical ecosystems: A Bayeasian network approach.

Anais da Academia Brasileira de Ciencias
The steady-state is a situation of little variability of species dominance and total biomass over time. Maintenance of cyanobacteria are often observed in tropical and eutrophic ecosystems and can cause imbalances in aquatic ecosystem. Bayeasian netw...

Applying feature selection and machine learning techniques to estimate the biomass higher heating value.

Scientific reports
The biomass higher heating value (HHV) is an important thermal property that determines the amount of recoverable energy from agriculture byproducts. Precise laboratory measurement or accurate prediction of the HHV is essential for designing biomass ...

Optimization of biogas production from straw wastes by different pretreatments: Progress, challenges, and prospects.

The Science of the total environment
Lignocellulosic biomass (LCB) presents a promising feedstock for carbon management due to enormous potential for achieving carbon neutrality and delivering substantial environmental and economic benefit. Bioenergy derived from LCB accounts for about ...

Photothermal Conversion of Hydrogel-Based Biomaterial.

Chemical record (New York, N.Y.)
Traditional energy from fossil fuels like petroleum and coal is limited and contributes to global environmental pollution and climate change. Developing sustainable and eco-friendly energy is crucial for addressing significant challenges such as clim...