AIMC Topic: Ammonia

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Machine learning methods for anomaly classification in wastewater treatment plants.

Journal of environmental management
Modern wastewater treatment plants base their biological processes on advanced control systems which ensure compliance with discharge limits and minimize energy consumption responding to information from on-line probes. The correct readings of probes...

Optimization of a near-zero-emission energy system for the production of desalinated water and cooling using waste energy of fuel cells.

Chemosphere
In the present study, a biomass-based multi-purpose energy system that can generate power, desalinated water, hydrogen, and ammonia is presented. The gasification cycle, gas turbine, Rankine cycle, PEM electrolyzer, ammonia production cycle using the...

Predicting ammonia nitrogen in surface water by a new attention-based deep learning hybrid model.

Environmental research
Ammonia nitrogen (NH-N) is closely related to the occurrence of cyanobacterial blooms and destruction of surface water ecosystems, and thus it is of great significance to develop predictive models for NH-N. However, traditional models cannot fully co...

Chemical looping based ammonia production-A promising pathway for production of the noncarbon fuel.

Science bulletin
Ammonia, primarily made with Haber-Bosch process developed in 1909 and winning two Nobel prizes, is a promising noncarbon fuel for preventing global warming of 1.5 °C above pre-industrial levels. However, the undesired characteristics of the process,...

Machine learning for manually-measured water quality prediction in fish farming.

PloS one
Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of high-quality fish farming. Machine learning (ML) techniques have been proposed to model the dynamics of such variables to improve the fish farmer's decision-ma...

Analysis of Behavior Trajectory Based on Deep Learning in Ammonia Environment for Fish.

Sensors (Basel, Switzerland)
Ammonia can be produced by the respiration and excretion of fish during the farming process, which can affect the life of fish. In this paper, to research the behavior of fish under different ammonia concentration and make the corresponding judgment ...

Using artificial neural networks to predict pH, ammonia, and volatile fatty acid concentrations in the rumen.

Journal of dairy science
The objectives of this study were (1) to predict ruminal pH and ruminal ammonia and volatile fatty acid (VFA) concentrations by developing artificial neural networks (ANN) using dietary nutrient compositions, dry matter intake, and body weight as inp...

In vitro colonic fermentation of Mexican "taco" from corn-tortilla and black beans in a Simulator of Human Microbial Ecosystem (SHIME®) system.

Food research international (Ottawa, Ont.)
A Mexican staple food prepared with corn "tortilla" (Zea mays L.) and common beans (Phaseolus vulgaris L.) is named as "taco". It was fermented in an in vitro colonic Simulator of Human Microbial Ecosystem (SHIME®) to evaluate the effect in short cha...

Effluent composition prediction of a two-stage anaerobic digestion process: machine learning and stoichiometry techniques.

Environmental science and pollution research international
Computational self-adapting methods (Support Vector Machines, SVM) are compared with an analytical method in effluent composition prediction of a two-stage anaerobic digestion (AD) process. Experimental data for the AD of poultry manure were used. Th...

A fuzzy logic urea dosage controller design for two-cell selective catalytic reduction systems.

ISA transactions
Diesel engines have dominated in the heavy-duty vehicular and marine power source. However, the induced air pollution is a big problem. As people's awareness of environmental protection increasing, the emission regulations of diesel-engine are becomi...