Methane concentration forward prediction using machine …
Studies are reported for predicting methane concentration variations inside underground mines using a long-short-term memory (LSTM) artificial recurrent neural network. Results will be compared to a simple time-series regression predictor (time-series filter).
RDC : la mine d'or Kibali a enregistré une production record …
(Agence Ecofin) - En RDC, la mine Kibali a largement dépassé les prévisions pour 2019 (750 000 onces) avec une production record de 814 027 onces d'or. C'est ce …
Sensors | Free Full-Text | Early Warning of Gas Concentration …
Gas explosion has always been an important factor restricting coal mine production safety. The application of machine learning techniques in coal mine gas concentration prediction and early warning can effectively prevent gas explosion accidents. Nearly all traditional prediction models use a regression technique to predict gas …
Concentration in Machine Learning | Duke Electrical and …
The Concentration in ML does not require additional courses. ECE majors can declare this concentration by selecting this option on the Pratt Declaration of Major form. Completion of the Concentration in Machine Learning requires a minimum of 5 courses. These requirements can be met within the general requirements of the ECE major and do not ...
High Spatiotemporal Resolution PM2.5 Concentration …
As an aggregate of suspended particulate matter in the air, atmospheric aerosols can affect the regional climate. With the help of satellite remote sensing technology to retrieve AOD (aerosol optical depth) on a global or regional scale, accurate estimation of PM2.5 concentration has become an important task to quantify the spatiotemporal …
Extreme learning machines: a new approach for
Overall, the results suggest that the ELM is more effective than the MLPNN and MLR for modelling DO concentration in river ecosystems. In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis …
Machine Learning-Based Prediction of the CO2 Concentration …
Monitoring the CO2 concentration in flue gas (CO2_G) is crucial to accurately calculate the direct carbon emissions associated with waste incineration. In this study, random forest (RF) and extreme gradient boosting (XGBoost) algorithms were used to predict CO2_G, using 21 operating variables from a municipal solid waste (MSW) …
Modelling daily dissolved oxygen concentration using least …
More recently, a new type of models called optimally pruned extreme learning machine (OP-ELM) has been proposed and applied for forecasting DO concentration (Heddam, 2016b). According to the results obtained, the proposed OP-ELM outperformed the MLPNN for forecasting DO for a period greater than 168 h (7 days) in advance, with …
Improving the stability of electrostatic induction dust concentration …
When the dust concentration is about 300 mg/m 3, the time required to stabilize is relatively small, less than 0.5 s, due to the small fluctuation of the standard deviation of the signal generated by the dust concentration. It is proven that the median filter algorithm and KalmanNet have a good processing result of the standard deviation of ...
Identifying the dominant driver of elevated surface ozone concentration …
Changes in anthropogenic emission increased MDA8 O 3 by 2.2–36.2 μg/m 3 in 2012–2017.. Changes in industrial and transport emission dominated the elevated O 3 concentration.. MDA8 O 3 increased by −13.5–25.8 μg/m 3 due to the meteorological condition variation.. Indirect effect of meteorological field change increased MDA8 O 3 by …
Development of Machine Learning-Based Energy …
In this chapter, we have developed a system model within the framework of the Markov Decision Process (MDP) to create an optimal policy for the energy management agent using reinforcement learning, building upon prior research [15, 17].We have considered both PM2.5 and PM10 fine dust concentrations, which represent the levels of …
Photonics | Free Full-Text | Photonic Crystal-Based Water Concentration …
Human blood is made up primarily of water. Water is significantly involved in balancing the human body. It affects the component of blood like mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and mean platelets volume (MPV). The water concentration varies from 80 to 90% in blood. The change in water …
Estimating ground-level high-resolution ozone concentration …
1. Introduction. Ambient ozone is a hazardous air pollutant, primarily produced by nonlinear photochemical reactions associating volatile organic compounds (VOCs) and nitrogen oxides (NOx) with sunlight (Li et al., 2020; Pu et al., 2017).Exposure to ambient ozone has been associated with several adverse health outcomes (Wang et al., 2020; …
Predicting water quality through daily concentration of
As an important hydrological parameter, dissolved oxygen (DO) concentration is a well-accepted indicator of water quality. This study deals with …
LES STATISTIQUES MINIÈRES EXERCICES 2022 : LA …
La République Démocratique du Congo (RDC) a produit, au cours de l'exercice sous revue 29 498,09 Kg d'or dont : 28 492,68 Kg d'or d'exploitation …
Continuous monitoring of suspended sediment …
Introduction. Monitoring Suspended Sediment Concentration (SSC) in open channels is explored in this paper towards the goal of developing an innovative …
Determination of Trace Organic Contaminant Concentration via Machine
Surface-enhanced Raman spectroscopy (SERS) has been well explored as a highly effective characterization technique that is capable of chemical pollutant detection and identification at very low concentrations. Machine learning has been previously used to identify compounds based on SERS spectral data. However, utilization of SERS to …
Machine learning-based modeling of surface sediment concentration …
Thus, the objective of this study was to use machine learning-based models to predict the surface sediment concentration (SSC) in the Doce river basin. The cross-sectional averages of measurements from seven sediment monitoring stations of the Agência Nacional de Águas e Saneamento Básico located in the Doce riverbed were …
Machine learning-based modeling of surface sediment concentration …
Semantic Scholar extracted view of "Machine learning-based modeling of surface sediment concentration in Doce river basin" by Uilson Ricardo Venâncio Aires et al. ... Fernandes Filho and Lineu Neiva Rodrigues and Eduardo Morgan Uliana and Ricardo Santos Silva Amorim and Celso Bandeira de Melo Ribeiro and Jasmine Alves Campos}, …
An efficient strategy for predicting river dissolved oxygen
Dissolved oxygen (DO) concentration in water is one of the key parameters for assessing river water quality. Artificial intelligence (AI) methods have previously …
Modelling daily dissolved oxygen concentration using least …
Semantic Scholar extracted view of "Modelling daily dissolved oxygen concentration using least square support vector machine, multivariate adaptive regression splines and M5 model tree" by S. Heddam et al. ... 2012; AbstractThe aim of this study is to examine the accuracy of two different artificial neural network ...
Estimation of dust concentration by a novel machine vision …
In the present research, a novel algorithm has been developed based on image processing to estimate dust concentration. An experimental setup was implemented to create airborne dust with different concentration values from 0 to 2750 µg.m -3. The images of the different dust concentration values were acquired and analyzed by image …
Improving machine-learned surface NO2 concentration
In contrast, recent endeavors have given to machine learning and/or deep learning-based air quality mapping by learning complex nonlinear relationships between ground-level air pollutants concentration measurements and versatile proxy variables (Bai et al., 2019a, Bai et al., 2019b, Bai et al., 2023), providing us an unparallel opportunity to ...
machine de concentration d or 2012
Saisissez ces copper concentration machine à bas prix. ... 100 200 500 Tpd, concentrateur de flottation de minerai d'or et de cuivre, Machine de flottation XJK/SF. 1 ... Oxygen Concentrator Machine The oxygen concentrator machine is a device that separates nitrogen and oxygen in the air through physical technology to obtain high …
l'évapoconcentration des produits alimentaires
L'évapo-concentration est une opération unitaire de déshydratation ; à la différence du séchage, l'évapo-concentration ne concerne que les produits fluides et va laisser une quantité d'eau finale non négligeable dans le produit fini concentré. Cette opération unitaire a plusieurs objectifs dont celui de stabilisation microbiologique (conservation) si elle est …
Dissolved oxygen concentration predictions for running
Water is one of the most essential elements in nature that forms the basis of human life and contributes to the economic growth and development of societies. Safe water is closely related to environmental health and activities. The lives of all the animals on our planet depend on water and oxygen. Moreover, sufficient dissolved oxygen (DO) is …
Concentration Inequalities
Concentration Inequalities 219 Theorem 3. bernstein's inequality. Under the conditions of the previous theorem, for any >0, (1 n Xn i=1 Xi> exp n 2 2(˙2 + =3) Bernstein's inequality points out an interesting phenomenon: if ˙2 <, then the upper bound behaves like e n instead of the e n 2 guaranteed by Hoe ding's inequality.
machine de concentration d or 2012
The concentration for Machine Learning and Artificial Intelligence is ideal for students who desire to learn how to program computer systems to 'learn' from data and perform …
Minimum Alveolar Concentration
In 1965, Eger et al. introduced the concept of minimum alveolar concentration (MAC), and it has since been used as the standard measure of potency for volatile anesthetic agents (see Graph. MAC Dose Response). Previous attempts to create a measure to determine the adequacy of anesthetic dosing, such as the Guedel stages of …
Ozone Concentration Forecasting Based on Artificial …
The main contribution of this paper review is to present the recent machine learning techniques, including SVM, ANN, decision tree and hybrid models, for predicting …
Review A critical review on odor measurement and prediction
In recent years, machine learning and the combination of chemical concentrations and other parameters have been applied to odor concentration …
Shigley's Mechanical Engineering Design Tutorial 3-13 …
localized effect of each stress concentration separately. 2. Compute the actual stress in the shoulder by taking into account the stress concentration caused by a fillet radius in a rectangular bar in tension. 3. Compute the actual stress in the region immediately adjacent to the hole by applying the stress-concentration factor associated for a ...
Predicting crop root concentration factors of organic contaminants …
As shown in Fig. 4, f om, f lipid, V and E were consistently selected as the top four most important features for the GBRT and FCNN models, despite slight differences in their relative rank.Specifically, the impurity-based feature importance analysis for the GBRT model revealed that f om and f lipid ranked as the first and second most important …
Ozone Concentration Forecasting Based on Artificial Intelligence
The prediction of tropospheric ozone concentrations is vital due to ozone's passive impacts on atmosphere, people's health, flora and fauna. However, ozone prediction is a complex process and the wide range of traditional models is incapable to obtain an accurate prediction. "Artificial intelligence", "machine learning" and "ozone …
Forecasting the concentration of NO2 using statistical and machine …
Forecasting the concentration of NO2 using statistical and machine learning methods: A case study in the UAE ... 2011 and extending to August 31, 2012. The data were used to predict the measurements three days ahead. Factor analyses, such as principal component analysis (PCA), Promax rotation, multicollinearity between the six …
Automated individualization of dialysate sodium concentration …
Decline in plasma glucose concentration in diabetic patients with poor control of blood glucose, being dialyzed against a fixed dialysate glucose concentration of 1 g/L, might have influenced plasma sodium measurement.27, 28 Plasma glucose levels were not measured in our study. However, intradialytic plasma sodium changes during …
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