This report presents the results of an exploratory machine learningbased analysis of green stormwater infrastructure asset data across five cities in the United States. Within each city, authors evaluated the location of installed green stormwater infrastructure based on the demographic and land use characteristics of the surrounding area.
WhatsApp: +86 18838072829The underground coal mines (UCM) exhibit many lifethreatening hazards for mining workers. In contrast, gas hazards are among the most critical challenges to handle. This study presents a comparative study of the sensor fusion methodologies related to UCM gas hazard prediction and classification. The study provides a brief theoretical background of the existing methodologies and their usage to ...
WhatsApp: +86 18838072829At present, coal gangue sorting technology based on machine learning is widely used . Liu C et al. established a comprehensive identification model of different ores and a support vector machine model through the texture characteristics of an image and completed the identification of different ores, thereby improving the efficiency of coal and ...
WhatsApp: +86 18838072829In this study, we developed an automatic Ppick quality control model based on machine learning to identify useable/unusable Ppicks. We used five waveform parameters, including signaltonoise ratio (SNR), signaltonoise variance ratio (SNVR), Pphase startingup slope ( K p ), shorttime zerocrossing rate (ZCR) and peak amplitude ( P a ) to ...
WhatsApp: +86 18838072829DOI: / Corpus ID: ; Rapid detection of coal ash based on machine learning and Xray fluorescence article{Huang2022RapidDO, title={Rapid detection of coal ash based on machine learning and Xray fluorescence}, author={Jinzhan Huang and Zhiqiang Li and Biao Chen and Sen Cui and Zhaolin Lu and Wei Dai and Yuemin Zhao and Chenlong Duan and Liang Dong}, journal ...
WhatsApp: +86 18838072829Muscle stem cells (MuSCs) reside in a niche, which generates various signals essential for regeneration of skeletal muscle. In this manuscript, Togninalli, Ho, and Madl developed a dual fluorescence imaging time lapse (DualFLIT) microscopy approach that leverages machine learning to track single cell fate, their analysis revealed that the lipid metabolite, prostaglandin ...
WhatsApp: +86 18838072829Spontaneous combustion of coal leading to mine fire is a major problem in most of the coal mining countries in the world. It causes major loss to the Indian economy. The liability of coal to spontaneous combustion varies from place to place and mainly depends on the coal intrinsic properties and other geomining factors. Hence, the prediction of spontaneous combustion susceptibility of coal is ...
WhatsApp: +86 18838072829The aim of this study was to predict the high risk of nodular thyroid disease in coal miners based on five different Machine learning (ML) is a retrospective clinical study in which 1,708 coal miners who were examined at the Huaihe Energy Occupational Disease Control Hospital in Anhui Province in April 2021 were selected and ...
WhatsApp: +86 18838072829DOI: / Corpus ID: ; Multiinformation online detection of coal quality based on machine vision article{Zhang2020MultiinformationOD, title={Multiinformation online detection of coal quality based on machine vision}, author={Zelin Zhang and Yang Liu and Qingli Hu and Zhiwei Zhang and Lei Wang and Xiang Liu and Xuhui Xia}, journal={Powder Technology}, year ...
WhatsApp: +86 18838072829Research on Multistep Mixed Predictiom Model of Coal Gasifier Furnace Temperature Based on Machine Learning February 2022 Journal of Physics Conference Series 2187(1):012070
WhatsApp: +86 18838072829Honeycomb Coal Briquette Machine. Honeycomb coal briquette machine can compress small granular coal and dust into coal blocks with holes. Its mold can be changed easily to produce cylindrical shapes and square shape briquettes. The coal briquette diameter range is 90250mm with different hole quantities.
WhatsApp: +86 18838072829IoTenabled sensor devices and machine learning methods have played an essential role in monitoring and forecasting mine hazards. In this paper, a prediction model has been proposed for improving the safety and productivity of underground coal mines using a hybrid CNNLSTM model and IoTenabled sensors. The hybrid CNNLSTM model can extract ...
WhatsApp: +86 18838072829Coal has been one of the most important sources of primary energy, together with oil and natural gas, for many decades now. Approximately onethird of the world's energy and 40% of electricity is generated from coal, which will remain an important part of the global energy mix in the medium to long term [1,2].During the early extraction of coal resources, the roomandpillar mining method ...
WhatsApp: +86 18838072829Online estimation of ash content in coal based on machine vision has been paid more attention to by academia and industry. Existing research has mainly focused on feature extraction and model design for estimating ash content, but the exploration of the feature's contribution to the model is rarely reported.
WhatsApp: +86 18838072829Coal Classification Method Based on Improved Local Receptive FieldBased Extreme Learning Machine Algorithm and VisibleInfrared Spectroscopy PMC Journal List ACS Omega (40); 2020 Oct 13 PMC As a library, NLM provides access to scientific literature.
WhatsApp: +86 18838072829sieving machine sor ts raw coal into coal equal to or greate r than 100 mm and less than 100 mm; a transp ortation syste m is used to transport the coa l from underground to grou nd; and
WhatsApp: +86 18838072829There exist many works where machine learning has been used for both simulated and physical optimization of combustion systems. Zheng et al. combine a support vector machine (SVM) with ant colony optimization (ACO) to optimize a 300 MW plant based on predicted NO x values (Zheng et al., 2008). Zheng et al. also compare the performance of ACO to ...
WhatsApp: +86 18838072829Accordingly, eigenvectors of coal and rock images are computed based on thermal imaging cloud images from coal and rock cutting trials. The traditional recognition technology of coal and rock mainly adjusts the height of the drum of the coal winning machine by manually observing the state of coal and rock and listening to the sound.
WhatsApp: +86 18838072829India aims to add 17 gigawatts of coalbased power generation capacity in the next 16 months, its fastest pace in recent years, to avert outages due to a record rise in power demand, according to ...
WhatsApp: +86 18838072829In our previous work, an approach based on image analysis and particle swarm optimizationsupport vector machine was presented (Wang et al. 2021) to detect the coalcarrying rate in gangue ...
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