بدائل البحث:
based optimization » whale optimization (توسيع البحث)
d optimization » _ optimization (توسيع البحث), b optimization (توسيع البحث), led optimization (توسيع البحث)
binary years » binary pairs (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data d » data de (توسيع البحث), data _ (توسيع البحث), data 1 (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
d optimization » _ optimization (توسيع البحث), b optimization (توسيع البحث), led optimization (توسيع البحث)
binary years » binary pairs (توسيع البحث)
binary data » primary data (توسيع البحث), dietary data (توسيع البحث)
data d » data de (توسيع البحث), data _ (توسيع البحث), data 1 (توسيع البحث)
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MSE for ILSTM algorithm in binary classification.
منشور في 2023"…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"
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<i>hi</i>PRS algorithm process flow.
منشور في 2023"…<p><b>(A)</b> Input data is a list of genotype-level SNPs. <b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …"
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Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures
منشور في 2021"…The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. …"
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Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
منشور في 2021"…EVAL1: The correlation between input features <i>x</i>∈<i>X</i> and output features y∈<i>Y</i>, <i>R</i>[<i>x,y</i>] or <i>R</i>[<i>y,x</i>]; EVAL2: The correlation between input features <i>x</i>∈<i>X</i> and labeled features v∈<i>L</i>, <i>R</i>[<i>x,v</i>] or <i>R</i>[<i>v,x</i>]; Subset: The optimal input feature subset. (D). The MCDM algorithm-Stage 4. …"