Search alternatives:
models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
acid optimization » based optimization (Expand Search), lead optimization (Expand Search), art optimization (Expand Search)
binary using » injury using (Expand Search)
using acid » using ai (Expand Search), using air (Expand Search), using cfd (Expand Search)
models optimization » model optimization (Expand Search), process optimization (Expand Search), wolf optimization (Expand Search)
acid optimization » based optimization (Expand Search), lead optimization (Expand Search), art optimization (Expand Search)
binary using » injury using (Expand Search)
using acid » using ai (Expand Search), using air (Expand Search), using cfd (Expand Search)
-
1
-
2
Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025“…The algorithm was applied to aqueous, binary mixture systems composed of 37 common biochemical substances such as amino acids, organic acids, and sugars. …”
-
3
The comparison of the accuracy score of the benchmark and the proposed models.
Published 2025Subjects: -
4
-
5
-
6
Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).
Published 2025Subjects: -
7
-
8
-
9
Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
10
ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
11
The statistical description of the original data set of the patients (<i>n</i> = 162).
Published 2025Subjects: -
12
-
13
The list of parameters of the modified data set for machine learning (<i>n</i> = 162).
Published 2025Subjects: -
14
-
15
Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model
Published 2019“…The methodology incorporates key features of the symmetric eNRTL-SAC model structure to reduce the number of parameters and uses a hybrid of global search algorithms for parameter estimation. …”
-
16
Descriptive analysis of the outcomes by the optimized LSTM using several optimization algorithms.
Published 2025Subjects: -
17
MSE for ILSTM algorithm in binary classification.
Published 2023“…The proposed algorithm has two phases: phase one involves training a conventional LSTM network to get initial weights, and phase two involves using the hybrid swarm algorithms, CBOA and PSO, to optimize the weights of LSTM to improve the accuracy. …”
-
18
-
19
DE algorithm flow.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”
-
20
Test results of different algorithms.
Published 2025“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”