بدائل البحث:
models optimization » model optimization (توسيع البحث), process optimization (توسيع البحث), wolf optimization (توسيع البحث)
halide optimization » whale optimization (توسيع البحث), acid optimization (توسيع البحث), quality optimization (توسيع البحث)
three models » three months (توسيع البحث), three levels (توسيع البحث)
based halide » based solid (توسيع البحث)
lines based » lens based (توسيع البحث), genes based (توسيع البحث), lines used (توسيع البحث)
models optimization » model optimization (توسيع البحث), process optimization (توسيع البحث), wolf optimization (توسيع البحث)
halide optimization » whale optimization (توسيع البحث), acid optimization (توسيع البحث), quality optimization (توسيع البحث)
three models » three months (توسيع البحث), three levels (توسيع البحث)
based halide » based solid (توسيع البحث)
lines based » lens based (توسيع البحث), genes based (توسيع البحث), lines used (توسيع البحث)
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
منشور في 2025"…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …"
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ROC curve for binary classification.
منشور في 2024"…Subsequently, a convolutional neural network model comprising four convolutional layers and two hidden layers was devised for classifying Alzheimer’s disease into three (3) distinct categories, namely mild cognitive impairment, Alzheimer’s disease, and normal controls. …"
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Confusion matrix for binary classification.
منشور في 2024"…Subsequently, a convolutional neural network model comprising four convolutional layers and two hidden layers was devised for classifying Alzheimer’s disease into three (3) distinct categories, namely mild cognitive impairment, Alzheimer’s disease, and normal controls. …"
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Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data
منشور في 2022"…An assay matrix based on CI and DS was prepared for 335 assays with biologically intended target information, and 28 CI assays and 3 DS assays were selected. Thirty models established by combining five molecular fingerprints (i.e., Morgan, MACCS, RDKit, Pattern, and Layered) and six algorithms [i.e., gradient boosting tree, random forest (RF), multi-layered perceptron, <i>k</i>-nearest neighbor, logistic regression, and naive Bayes] were trained using the selected assay data set. …"
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Flow diagram of the proposed model.
منشور في 2025"…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. …"
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Summary of existing CNN models.
منشور في 2024"…Subsequently, a convolutional neural network model comprising four convolutional layers and two hidden layers was devised for classifying Alzheimer’s disease into three (3) distinct categories, namely mild cognitive impairment, Alzheimer’s disease, and normal controls. …"
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Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf
منشور في 2024"…A support vector machine (SVM) is attractive because binary classification can be represented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization (QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing—classical, quantum, and hybrid—an attractive approach to explore. …"
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