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Evaluation of the impact of explanatory variables on the accuracy of prediction of daily inflow to the sewage treatment plant by selected models nonlinear

Bartosz Szeląg, Lidia Bartkiewicz, Jan Studziński, Krzysztof Barbusiński
2017 Archives of Environmental Protection  
The aim of the study was to evaluate the possibility of applying different methods of data mining to model the inflow of sewage into the municipal sewage treatment plant.  ...  Prediction models were elaborated using methods of support vector machines (SVM), random forests (RF), k-nearest neighbour (k-NN) and of Kernel regression (K).  ...  neighbour (k-NN) and of random forest (RF) have not been yet used although their application to model the biological sewage treatment reactors was successfully confi rmed.  ... 
doi:10.1515/aep-2017-0030 fatcat:gfbbehmnbjedfmzput7knupbwi

Determining the effectiveness of soil treatment on plant stress using smart-phone cameras

Anurag Panwar, Mariam Al-Lami, Pratool Bharti, Sriram Chellappan, Joel Burken
2016 2016 International Conference on Selected Topics in Mobile & Wireless Networking (MoWNeT)  
She always wanted to see me succeed. She sacrificed a lot of her personal interest and ambitions to provide all the necessary resources needed for my success. Mom, this is for you!  ...  I want to give special note of appreciation to my late mother Madhu Panwar for her sacrifice and hard work which she put in to teach me the importance of hardwork and being good human.  ...  Learning Algorithms based on Random Forests We designed a classification algorithm based on Random Forests [12] [13] [14] for classifying plant stress.  ... 
doi:10.1109/mownet.2016.7496612 dblp:conf/mownet/PanwarABCB16 fatcat:4plghgreh5a7ba66h4sl5wtxki

SAM9718.pdf [article]

Ahsan Al Zaki Khan
2020 Figshare  
A set of new features were formulated using the original features from the dataset to help in the classification task.  ...  Integration of Supervisory Control and Data Acquisition (SCADA) systems with internet and recent high profile attacks has exposed critical vulnerabilities and led to significant increase for research on  ...  Random forest is a decision tree-based ensemble classifier [16] . It combines the predictions made by multiple decision trees, where each tree is based on randomly selected samples.  ... 
doi:10.6084/m9.figshare.11690475 fatcat:k5gftdnx4fdz5kfvq62xnwwa3u

Growth Curves for Diameter and Height Using Mixed Models: An Application in Eucalyptus Seedling

Giovana Fumes, Clarice Garcia Borges Demétrio, Cristian Villegas, José Eduardo Corrente, Juliane Fumes Bazzo
2017 Open Journal of Forestry  
The methodology was carried in a mixed longitudinal model using a new approach based on Box-Cox Normal (BCN) distribution, and comparisons with this model were made assuming normality of the data.  ...  The experiment's design was completely randomized with eight treatments and four replications.  ...  In this context, the height/diameter relation is one of the features used to evaluate the forest seedling quality, because it reflects the reserve accumulation, a greater resistance and better fixation  ... 
doi:10.4236/ojf.2017.74024 fatcat:m444hnfbrngwreqhvzyku4o7hi

Machine learning-aided analyses of thousands of draft genomes reveal specific features of activated sludge processes

Lin Ye, Ran Mei, Wen-Tso Liu, Hongqiang Ren, Xu-Xiang Zhang
2020 Microbiome  
Further, we developed a novel machine learning approach that can distinguish between AS MAGs and MAGs from other environments based on the clusters of orthologous groups of proteins with an accuracy of  ...  Here, we present 2045 archaeal and bacterial metagenome-assembled genomes (MAGs) recovered from 1.35 Tb of metagenomic data generated from 114 AS samples of 23 full-scale wastewater treatment plants (WWTPs  ...  in the sludge sampling and sample treatment.  ... 
doi:10.1186/s40168-020-0794-3 pmid:32046778 pmcid:PMC7014675 fatcat:5nsbl4js7zet7it3c3vza4p2eu

Identifying and Estimating the Location of Sources of Industrial Pollution in the Sewage Network

Magdalena Paulina Buras, Fernando Solano Donado
2021 Sensors  
., through leakages leading to groundwater reservoirs—and may also impair the correct operation of wastewater treatment plants.  ...  This problem is solved using random forest classifiers.  ...  We would also like to thank Steffen Krause and Christoph Wöllgens from the H2020 SYSTEM project for providing the input simulation data of the wastewater network used in the Results section.  ... 
doi:10.3390/s21103426 pmid:34069087 fatcat:vwrlhmayjbaurkkchx3qtohf2q

Biological Engineering Analysis of Vermicompost Based on Image Features and Machine Learning

Hongyan Wang, Ling Wang, Jiabin Liu, Ying Nie, Daqing Wang, Sang-Bing Tsai
2022 Mobile Information Systems  
Researchers began researching appropriate assessment methods in order to assure the influence of earthworm excrement and to precisely and effectively measure changes in image quality.  ...  Earthworm manure is a soil enhancement product that is homogeneous, permeable, ecological, and organic. It has a particle structure that is substantially greater than the soil's surface area.  ...  Its production characteristic is to randomly select a few characteristics, which fully guarantees the randomness of its characteristics. e training courses and the randomly selected forest decision trees  ... 
doi:10.1155/2022/7347142 fatcat:ymb4en72t5cyroxbyqzxorqwby

Vulnerability Assessment of Asphalt Plant through Machine Learning Techniques

Abid Haider, Sarmadullah Khan, Abdullah Mohamed, Shahbaz Khan, Razaullah Khan, Hafiz Tayyab Rauf
2022 Mobile Information Systems  
., SVM, KNN, and random forest, are tested to cover the anomaly detection along with security protection for SCADA systems.  ...  Amongst the above-mentioned algorithms, KNN outperformed with an accuracy rate of 89% for anomaly detection and any kind of external attack can be detected and notified to the control room for on-time  ...  Based on the decision trees' predictions, the (random forest) method decides on a final result. Using the average of different trees output, it makes predictions.  ... 
doi:10.1155/2022/9496123 fatcat:jbmho2t5qnf7dopqh23xpfedn4

Plasmid Permissiveness of Wastewater Microbiomes can be Predicted from 16S rDNA sequences by Machine Learning [article]

Danesh Moradigaravand, Liguan Li, Arnaud Dechesne, Joseph Nesme, Huda Ahmad, Manuel Banzhaf, Soren Sorensen, Barth Smets, Jan Kreft
2022 bioRxiv   pre-print
Our results indicate that the predicted permissiveness from the best performing model (random forest) showed a moderate-to-strong average correlation of 0.45 for pB10 (95% CI: 0.42-0.52), 0.42 for pKJK5  ...  Wastewater Treatment Plants (WWTPs) contain a diverse microbial community with high cell density.  ...  The models comprised a baseline regularized lasso regression model, a random forest and a gradient boosted regressor, which were trained on predictor features, i.e., the counts of kmers with different  ... 
doi:10.1101/2022.07.09.499415 fatcat:rgjzvkdjbfcnxcx3xyclirxnbm

Survival, Growth And Mineral Accumulation In Ash Fraxinus Excelsior L. Seedlings Irrigated With Water Treatment Effluent

Bahareh Selahvarzi, Seyed Mohsen Hosseini
2012 Zenodo  
A pot experiment was carried out to study the effect of irrigation with water treatment effluent on the growth and chemical constituents of ash seedlings Fraxinus excelsior L. according as soil chemical  ...  (height, collar diameter and biomass dry weight) as well as it brought about the highest concentration of N, P, K and Mg in plant parts, when compared with mix water and well water treatments.  ...  It can be concluded, based on the results obtained that proper management of water treatment effluent irrigation and periodic monitoring of soil fertility and quality parameters are required to ensure  ... 
doi:10.5281/zenodo.30841 fatcat:fsajxubdxjdubaa4sywb3hzjzy

A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system

Andres Robles-Durazno, Naghmeh Moradpoor, James McWhinnie, Gordon Russell
2018 2018 International Conference on Cyber Security and Protection of Digital Services (Cyber Security)  
For the time taken to build the model, KNN presents the best performance. However, its difference with Random Forest is smaller than with SVM.  ...  The results show that Random Forest achieves 5% better performance over KNN and SVM with small datasets and 4% regarding large datasets.  ...  ACKNOWLEDGMENT This research is supported by the School of Computing and the School of Engineering and the Built Environment of Edinburgh Napier University.  ... 
doi:10.1109/cybersecpods.2018.8560683 dblp:conf/cybersecpods/Robles-DuraznoM18 fatcat:irswu5lg5vafpmqfdibzlenmge

Machine learning aided analyses of thousands of draft genomes reveal plant- and environment-specific features of activated sludge process [article]

Lin Ye, Ran Mei, Wen-Tso Liu, Hongqiang Ren, Xuxiang Zhang
2019 bioRxiv   pre-print
approach, and based on these traits, AS MAGs could be differentiated from MAGs of other environments with an accuracy of 96.6%.  ...  Our work provides valuable genome resources for future investigation of the AS microbiome and also introduces a novel approach to understand the microbial ecology in different ecosystems.  ...  Furthermore, the COGs significantly contributed to the machine-471 learning-based prediction were analyzed based on the feature importance provided by 472 the random forest model.  ... 
doi:10.1101/710368 fatcat:ouifbzczyfginisfcu4msq57hm

Spatial Quantification of Non-Point Source Pollution in a Meso-Scale Catchment for an Assessment of Buffer Zones Efficiency

Mikołaj Piniewski, Paweł Marcinkowski, Ignacy Kardel, Marek Giełczewski, Katarzyna Izydorczyk, Wojciech Frątczak
2015 Water  
The objective of this paper was to spatially quantify diffuse pollution sources and estimate the potential efficiency of applying riparian buffer zones as a conservation practice for mitigating chemical  ...  On average, reductions of 56% and 76% were observed, respectively. An improved simulation of buffer zones in SWAT was achieved through empirical upscaling of the measurement results.  ...  This paper is an outcome of the EKOROB project: Ecotones for reducing diffuse pollution (LIFE08 ENV/PL/000519). This project was supported by the LIFE+ Environment Policy and  ... 
doi:10.3390/w7051889 fatcat:2zcrbbbypfbfnngr6ok5sxo5hu

Machine learning for microalgae detection and utilization

Hongwei Ning, Rui Li, Teng Zhou
2022 Frontiers in Marine Science  
However, microalgae are too tiny, and there are many different kinds of microalgae in a single drop of seawater. It is challenging to identify microalgae species and monitor microalgae changes.  ...  The paper summarizes recent advances based on various machine learning algorithms in microalgae applications, such as microalgae classification, bioenergy generation from microalgae, environment purification  ...  (C) A decision tree for identification based on iris. (reproduced from an open access article). FIGURE 3 (A) Training steps of random forest. (B) Classification application of random forest.  ... 
doi:10.3389/fmars.2022.947394 fatcat:ix7ib3al45ev3hxfz2xr5xkkai

The Willingness to Pay of Industrial Water Users for Reclaimed Water in Taiwan [chapter]

Yawen Chiueh, Hsiao-Hua Chen, Chung-Feng Ding
2011 Current Issues of Water Management  
Agency, Ministry of Economic Affairs, Taiwan (project code: Moeawra0980052) and "A game theory approach to evaluation the irrigation water transfer" that sponsored by the National Science Council, Taiwan  ...  The authors would like to thank the anonymous reviewers and all the participants of this project for their efforts.  ...  for reuse, the environmental assessment requires that wastewater or sewerage within a building to be reclaimed by the building, or a wastewater/sewage treatment plant reclaims a portion of its own effluent  ... 
doi:10.5772/27448 fatcat:wbuxdraedbdtbg5weywleq6a7y
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