Comparison between ILSTM and machine learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

Comparison between ILSTM and deep learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

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One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

“…The ILSTM was then used to build an efficient intrusion detection system for binary and multi-class classification cases. 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. …”

Demographic, clinical, diagnostic and laboratory characteristics of patients at admission. by Hanh Thi Duc Tran (12501284)

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Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple... by Yangyang Liu (807797)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

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Regression tree for scrub typhus using the entire data set. by Hanh Thi Duc Tran (12501284)

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Model validation: Accuracy of Scrub typhus Prediction Models derived by Multivariate Logistic Regression vs. by Hanh Thi Duc Tran (12501284)

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Results from multivariate logistic regression with the most relevant predictors for the presence of scrub typhus (training part)^#. by Hanh Thi Duc Tran (12501284)

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Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses by Meichen Liu (8168148)

Fig 2 - by Olaide N. Oyelade (14047002)

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The most relevant predictors of scrub typhus selected by CART (using R) and by the multivariate logistic regression (M-LR) approach (using STATA). by Hanh Thi Duc Tran (12501284)

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Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

“…Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”

An optimization process of the proposed hybrid BEOSA (HBEOSA) combining both SA and FFA methods into BEOSA. by Olaide N. Oyelade (14047002)

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The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

The geographic distribution in Khanh Hoa of all scrub typhus (n = 221) and dengue fever (n = 387) confirmed cases in this study is depicted in these maps. by Hanh Thi Duc Tran (12501284)

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ROC curves-performance of prediction models for scrub typhus as opposed to dengue fever, using M-LR. by Hanh Thi Duc Tran (12501284)

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Full dataset in XCEL format. by Hanh Thi Duc Tran (12501284)

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