BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

174 related articles for article (PubMed ID: 33360819)

  • 1. Forecasting of municipal solid waste generation using non-linear autoregressive (NAR) neural models.
    Sunayana ; Kumar S; Kumar R
    Waste Manag; 2021 Feb; 121():206-214. PubMed ID: 33360819
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Application of system dynamics model for municipal solid waste management in Khulna city of Bangladesh.
    Rafew SM; Rafizul IM
    Waste Manag; 2021 Jun; 129():1-19. PubMed ID: 34010802
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Forecasting municipal solid waste generation using artificial intelligence modelling approaches.
    Abbasi M; El Hanandeh A
    Waste Manag; 2016 Oct; 56():13-22. PubMed ID: 27297046
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Electricity Generation Forecast of Shanghai Municipal Solid Waste Based on Bidirectional Long Short-Term Memory Model.
    Liu B; Zhang N; Wang L; Zhang X
    Int J Environ Res Public Health; 2022 May; 19(11):. PubMed ID: 35682200
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Long short-term memory neural network and improved particle swarm optimization-based modeling and scenario analysis for municipal solid waste generation in Shanghai, China.
    Wang D; Yuan YA; Ben Y; Luo H; Guo H
    Environ Sci Pollut Res Int; 2022 Oct; 29(46):69472-69490. PubMed ID: 35567684
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Analysis and forecasting of municipal solid waste in Nankana City using geo-spatial techniques.
    Mahmood S; Sharif F; Rahman AU; Khan AU
    Environ Monit Assess; 2018 Apr; 190(5):275. PubMed ID: 29644486
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis.
    Adamović VM; Antanasijević DZ; Ristić MĐ; Perić-Grujić AA; Pocajt VV
    Environ Sci Pollut Res Int; 2017 Jan; 24(1):299-311. PubMed ID: 27718111
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Application and evaluation of forecasting methods for municipal solid waste generation in an Eastern-European city.
    Rimaityte I; Ruzgas T; Denafas G; Racys V; Martuzevicius D
    Waste Manag Res; 2012 Jan; 30(1):89-98. PubMed ID: 21382880
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China.
    Xu L; Gao P; Cui S; Liu C
    Waste Manag; 2013 Jun; 33(6):1324-31. PubMed ID: 23490364
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An empirical model for prediction of household solid waste generation rate - A case study of Dhanbad, India.
    Kumar A; Samadder SR
    Waste Manag; 2017 Oct; 68():3-15. PubMed ID: 28757221
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Forecasting municipal solid waste in Lithuania by incorporating socioeconomic and geographical factors.
    Paulauskaite-Taraseviciene A; Raudonis V; Sutiene K
    Waste Manag; 2022 Mar; 140():31-39. PubMed ID: 35033802
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A multi-model forecasting approach for solid waste generation by integrating demographic and socioeconomic factors: a case study of Prayagraj, India.
    Srivastava A; Jha PK
    Environ Monit Assess; 2023 May; 195(6):768. PubMed ID: 37249687
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Hybrid model for the prediction of municipal solid waste generation in Hangzhou, China.
    Zhang Z; Zhang Y; Wu D
    Waste Manag Res; 2019 Aug; 37(8):781-792. PubMed ID: 31264528
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Alternatives for solid waste management in Isfahan, Iran: a case study.
    Abduli MA; Tavakolli H; Azari A
    Waste Manag Res; 2013 May; 31(5):532-7. PubMed ID: 23444149
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Assessment of the Municipal Solid Waste & Status of Implementation of Municipal Solid Waste (Management & Handling), Rules, 2000 in the State of Madhya Pradesh, 2008 - a case study.
    Lal Patel M; Jain R; Saxena A
    Waste Manag Res; 2011 May; 29(5):558-62. PubMed ID: 20558496
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Forecasting municipal solid waste generation using prognostic tools and regression analysis.
    Ghinea C; Drăgoi EN; Comăniţă ED; Gavrilescu M; Câmpean T; Curteanu S; Gavrilescu M
    J Environ Manage; 2016 Nov; 182():80-93. PubMed ID: 27454099
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Waste generation and management status in the fast-expanding Indian cities: A review.
    Dutta A; Jinsart W
    J Air Waste Manag Assoc; 2020 May; 70(5):491-503. PubMed ID: 32150518
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Yard waste prediction from estimated municipal solid waste using the grey theory to achieve a zero-waste strategy.
    Islam MR; Kabir G; Ng KTW; Ali SM
    Environ Sci Pollut Res Int; 2022 Jul; 29(31):46859-46874. PubMed ID: 35171430
    [TBL] [Abstract][Full Text] [Related]  

  • 19. New insights into regional differences of the predictions of municipal solid waste generation rates using artificial neural networks.
    Wu F; Niu D; Dai S; Wu B
    Waste Manag; 2020 Apr; 107():182-190. PubMed ID: 32299033
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Effects of the opening of the Qinghai-Tibet Railway on municipal solid waste management generation in Lhasa.
    Ding XT; Wang JH
    Waste Manag Res; 2018 Mar; 36(3):300-306. PubMed ID: 29378499
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.