BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

335 related articles for article (PubMed ID: 32629264)

  • 1. Introducing a novel multi-layer perceptron network based on stochastic gradient descent optimized by a meta-heuristic algorithm for landslide susceptibility mapping.
    Hong H; Tsangaratos P; Ilia I; Loupasakis C; Wang Y
    Sci Total Environ; 2020 Nov; 742():140549. PubMed ID: 32629264
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Spatial Landslide Susceptibility Assessment Based on Novel Neural-Metaheuristic Geographic Information System Based Ensembles.
    Moayedi H; Osouli A; Tien Bui D; Foong LK
    Sensors (Basel); 2019 Oct; 19(21):. PubMed ID: 31671801
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China.
    Wang Y; Wu X; Chen Z; Ren F; Feng L; Du Q
    Int J Environ Res Public Health; 2019 Jan; 16(3):. PubMed ID: 30696105
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Zonation of Landslide Susceptibility in Ruijin, Jiangxi, China.
    Zhou X; Wu W; Lin Z; Zhang G; Chen R; Song Y; Wang Z; Lang T; Qin Y; Ou P; Huangfu W; Zhang Y; Xie L; Huang X; Fu X; Li J; Jiang J; Zhang M; Liu Y; Peng S; Shao C; Bai Y; Zhang X; Liu X; Liu W
    Int J Environ Res Public Health; 2021 May; 18(11):. PubMed ID: 34072874
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Groundwater spring potential mapping using population-based evolutionary algorithms and data mining methods.
    Chen W; Tsangaratos P; Ilia I; Duan Z; Chen X
    Sci Total Environ; 2019 Sep; 684():31-49. PubMed ID: 31150874
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Applying genetic algorithms to set the optimal combination of forest fire related variables and model forest fire susceptibility based on data mining models. The case of Dayu County, China.
    Hong H; Tsangaratos P; Ilia I; Liu J; Zhu AX; Xu C
    Sci Total Environ; 2018 Jul; 630():1044-1056. PubMed ID: 29554726
    [TBL] [Abstract][Full Text] [Related]  

  • 7. The Influence of Different Knowledge-Driven Methods on Landslide Susceptibility Mapping: A Case Study in the Changbai Mountain Area, Northeast China.
    Ma Z; Qin S; Cao C; Lv J; Li G; Qiao S; Hu X
    Entropy (Basel); 2019 Apr; 21(4):. PubMed ID: 33267086
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China.
    Hong H; Tsangaratos P; Ilia I; Liu J; Zhu AX; Chen W
    Sci Total Environ; 2018 Jun; 625():575-588. PubMed ID: 29291572
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparing probabilistic and statistical methods in landslide susceptibility modeling in Rwanda/Centre-Eastern Africa.
    Nsengiyumva JB; Luo G; Amanambu AC; Mind'je R; Habiyaremye G; Karamage F; Ochege FU; Mupenzi C
    Sci Total Environ; 2019 Apr; 659():1457-1472. PubMed ID: 31096356
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comparison of Random Forest Model and Frequency Ratio Model for Landslide Susceptibility Mapping (LSM) in Yunyang County (Chongqing, China).
    Wang Y; Sun D; Wen H; Zhang H; Zhang F
    Int J Environ Res Public Health; 2020 Jun; 17(12):. PubMed ID: 32545618
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A Novel Swarm Intelligence-Harris Hawks Optimization for Spatial Assessment of Landslide Susceptibility.
    Bui DT; Moayedi H; Kalantar B; Osouli A; Pradhan B; Nguyen H; Rashid ASA
    Sensors (Basel); 2019 Aug; 19(16):. PubMed ID: 31426552
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Hybrid Integration Approach of Entropy with Logistic Regression and Support Vector Machine for Landslide Susceptibility Modeling.
    Zhang T; Han L; Chen W; Shahabi H
    Entropy (Basel); 2018 Nov; 20(11):. PubMed ID: 33266608
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Landslide Susceptibility Evaluation of Machine Learning Based on Information Volume and Frequency Ratio: A Case Study of Weixin County, China.
    He W; Chen G; Zhao J; Lin Y; Qin B; Yao W; Cao Q
    Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904752
    [TBL] [Abstract][Full Text] [Related]  

  • 14. GIS-based landslide susceptibility mapping using heuristic and bivariate statistical methods for Iva Valley and environs Southeast Nigeria.
    Ozioko OH; Igwe O
    Environ Monit Assess; 2020 Jan; 192(2):119. PubMed ID: 31950278
    [TBL] [Abstract][Full Text] [Related]  

  • 15. GIS-based landslide susceptibility zonation mapping using the analytic hierarchy process (AHP) method in parts of Kalimpong Region of Darjeeling Himalaya.
    Das S; Sarkar S; Kanungo DP
    Environ Monit Assess; 2022 Mar; 194(3):234. PubMed ID: 35229227
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan.
    Dou J; Yunus AP; Tien Bui D; Merghadi A; Sahana M; Zhu Z; Chen CW; Khosravi K; Yang Y; Pham BT
    Sci Total Environ; 2019 Apr; 662():332-346. PubMed ID: 30690368
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A new combined approach of neural-metaheuristic algorithms for predicting and appraisal of landslide susceptibility mapping.
    Moayedi H; Dehrashid AA
    Environ Sci Pollut Res Int; 2023 Jul; 30(34):82964-82989. PubMed ID: 37336850
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automated Landslide-Risk Prediction Using Web GIS and Machine Learning Models.
    Tengtrairat N; Woo WL; Parathai P; Aryupong C; Jitsangiam P; Rinchumphu D
    Sensors (Basel); 2021 Jul; 21(13):. PubMed ID: 34283153
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment.
    Nhu VH; Mohammadi A; Shahabi H; Ahmad BB; Al-Ansari N; Shirzadi A; Clague JJ; Jaafari A; Chen W; Nguyen H
    Int J Environ Res Public Health; 2020 Jul; 17(14):. PubMed ID: 32650595
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Exploring machine learning and statistical approach techniques for landslide susceptibility mapping in Siwalik Himalayan Region using geospatial technology.
    Saha A; Tripathi L; Villuri VGK; Bhardwaj A
    Environ Sci Pollut Res Int; 2024 Feb; 31(7):10443-10459. PubMed ID: 38198087
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.