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Showing 161 - 180 results of 303 for search '(( binary based smart optimization algorithm ) OR ( lines based method optimization algorithm ))*', query time: 0.51s Refine Results
  1. 161
    The results of the sum of the squared error in 20 implementation of ANN-BTA network in three ranges of [0.1, 0.4], [0.4, 0.7], [0.7, 1].

    The results of the sum of the squared error in 20 implementation of ANN-BTA network in three ranges of [0.1, 0.4], [0.4, 0.7], [0.7, 1]. by Mouhamad Bodaghie (14838511)

    Published 2023
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  2. 162
    Fig 12 -

    Fig 12 - by Mouhamad Bodaghie (14838511)

    Published 2023
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  3. 163
    Fig 7 -

    Fig 7 - by Mouhamad Bodaghie (14838511)

    Published 2023
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  4. 164
    The MSE value of ANN-PSO network after interval limiting [1,1.2] and obtaining the lowest error rate in estimating mortality rate.

    The MSE value of ANN-PSO network after interval limiting [1,1.2] and obtaining the lowest error rate in estimating mortality rate. by Mouhamad Bodaghie (14838511)

    Published 2023
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  5. 165
    The MSE value of ANN-PSO network after interval limiting [1,1.2] and obtaining the lowest error rate in estimating basic reproduction numberand.

    The MSE value of ANN-PSO network after interval limiting [1,1.2] and obtaining the lowest error rate in estimating basic reproduction numberand. by Mouhamad Bodaghie (14838511)

    Published 2023
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  6. 166
    S1 Data -

    S1 Data - by Mouhamad Bodaghie (14838511)

    Published 2023
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  7. 167
    Fig 5 -

    Fig 5 - by Mouhamad Bodaghie (14838511)

    Published 2023
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  8. 168
    Fig 3 -

    Fig 3 - by Mouhamad Bodaghie (14838511)

    Published 2023
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  9. 169
    An epidemiological learning model.

    An epidemiological learning model. by Mouhamad Bodaghie (14838511)

    Published 2023
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  10. 170
    Fig 4 -

    Fig 4 - by Mouhamad Bodaghie (14838511)

    Published 2023
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  11. 171
    Total mean square error (MSE) of training and testing data in the best implementation of the ANN-PSO network for estimating the mortality rate of COVID-19 patients in the ranges of [0.1,0.4], [0.4,0.7], [0.7, 1], [1.1.3], [1.3,1.7] and [1.7,2].

    Total mean square error (MSE) of training and testing data in the best implementation of the ANN-PSO network for estimating the mortality rate of COVID-19 patients in the ranges of... by Mouhamad Bodaghie (14838511)

    Published 2023
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  12. 172
    Total mean square error (MSE) of training and experimental data in the best implementation of ANN-BTA network for estimating basic reproduction number related to COVID-19 patients in the ranges of [0.8,1], [1,1.2], [1.2,1.4] And [1.4,1.6].

    Total mean square error (MSE) of training and experimental data in the best implementation of ANN-BTA network for estimating basic reproduction number related to COVID-19 patients... by Mouhamad Bodaghie (14838511)

    Published 2023
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  13. 173
    The MSE value of ANN-BTA network after interval limiting [1,1.2] and obtaining the lowest error rate in estimating basic reproduction numberand.

    The MSE value of ANN-BTA network after interval limiting [1,1.2] and obtaining the lowest error rate in estimating basic reproduction numberand. by Mouhamad Bodaghie (14838511)

    Published 2023
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  14. 174
    Fig 8 -

    Fig 8 - by Mouhamad Bodaghie (14838511)

    Published 2023
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  15. 175
    Examples of model selection methods for the PHMM.

    Examples of model selection methods for the PHMM. by Tianshu Li (1527088)

    Published 2025
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  16. 176
    Manhattan plot of the univariate <i>p</i>-values for body mass index.

    Manhattan plot of the univariate <i>p</i>-values for body mass index. by Junyang Qian (9558026)

    Published 2020
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  17. 177
    Manhattan plot of the univariate <i>p</i>-values for asthma.

    Manhattan plot of the univariate <i>p</i>-values for asthma. by Junyang Qian (9558026)

    Published 2020
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  18. 178
    Manhattan plot of the univariate <i>p</i>-values for height.

    Manhattan plot of the univariate <i>p</i>-values for height. by Junyang Qian (9558026)

    Published 2020
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  19. 179
    Manhattan plot of the univariate <i>p</i>-values for high cholesterol.

    Manhattan plot of the univariate <i>p</i>-values for high cholesterol. by Junyang Qian (9558026)

    Published 2020
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  20. 180
    Supplementary file 1_Dynamic and static integrated classification model of gas well based on XGBoost algorithm—an example from block S of Sulige tight sandstone gas field.pdf

    Supplementary file 1_Dynamic and static integrated classification model of gas well based on XGBoost algorithm—an example from block S of Sulige tight sandstone gas field.pdf by Shuangshuang Zhang (701020)

    Published 2025
    “…Aiming at this problem, this paper establishes a set of dynamic and static integrated classification model of tight sandstone gas wells in Sulige based on XGBoost algorithm. After comparison and verification, it is proved to be accurate and reliable. …”
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