بدائل البحث:
based optimization » whale optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary base » binary mask (توسيع البحث), ciliary base (توسيع البحث), binary image (توسيع البحث)
base global » based global (توسيع البحث), yale global (توسيع البحث)
based based » based case (توسيع البحث), based basis (توسيع البحث), ranked based (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
binary based » library based (توسيع البحث), linac based (توسيع البحث), binary mask (توسيع البحث)
binary base » binary mask (توسيع البحث), ciliary base (توسيع البحث), binary image (توسيع البحث)
base global » based global (توسيع البحث), yale global (توسيع البحث)
based based » based case (توسيع البحث), based basis (توسيع البحث), ranked based (توسيع البحث)
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61
Schematic of iteration process of IDE-IIGA.
منشور في 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. …"
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62
Schematic diagram of IGA chromosome coding.
منشور في 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. …"
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63
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64
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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65
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66
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67
Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
منشور في 2025الموضوعات: -
68
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69
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70
QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm
منشور في 2020"…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …"
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71
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72
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73
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74
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75
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"…Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"
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76
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77
Proposed Algorithm.
منشور في 2025"…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …"
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78
Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things
منشور في 2025"…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …"
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79
Pseudo Code of RBMO.
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"
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80
P-value on CEC-2017(Dim = 30).
منشور في 2025"…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …"