Statistical tests of ACC on the random network. by Ruochen Zhang (3434996)

“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”

Parameters in the experiment. by Ruochen Zhang (3434996)

“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”

Statistical tests of APL on the random network. by Ruochen Zhang (3434996)

“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”

Statistical tests of ACC on the regular network. by Ruochen Zhang (3434996)

“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”

Statistical tests of APL on the regular network. by Ruochen Zhang (3434996)

“…A novel method for optimizing small-world property is then proposed based on the multiobjective evolutionary algorithm with decomposition. …”

Snake niche modeling score (SNMS). by Carlos Bravo-Vega (12328684)

Control of Mutual Coupling in Microstrip Antenna Design Based on Bio-inspired Algorithms by Israel Leal (16525460)

Proposed architecture of our research. by Md Junayed Hossain (22615268)

Subjects:

A summary of the dataset containing information on each cattle’s weight, breed, and height. by Md Junayed Hossain (22615268)

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Error case analysis using LIME visualization on cattle’s weight prediction. by Md Junayed Hossain (22615268)

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Height-Weight correlation and breed distribution of cattle in the dataset. by Md Junayed Hossain (22615268)

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Image processing steps applied in our research. by Md Junayed Hossain (22615268)

Subjects:

This figure illustrates the four distinct custom Convolutional Neural Network (CNN) architectures evaluated in this study. by Md Junayed Hossain (22615268)

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An integrated cloud system based serverless android app for generalised tractor drawbar pull prediction model using machine learning by Harsh Nagar (19276855)

“…The present study proposes a novel approach for tractor drawbar pull prediction by utilising the tractor's geometric parameters and forward speed to develop a cloud-infused, server-less, machine learning-based real-time generalised tractor drawbar pull prediction model for any tractor between the 6-58 kW power range. …”

Risk element category diagram. by Yao Hu (3479972)

“…The outcome indicates that the standard error of the LSTM algorithm model training is less than 0.18, and the decision coefficients were all greater than 0.9. …”

S1 Data - by Yao Hu (3479972)

“…The outcome indicates that the standard error of the LSTM algorithm model training is less than 0.18, and the decision coefficients were all greater than 0.9. …”

Airport risk levels. by Yao Hu (3479972)

“…The outcome indicates that the standard error of the LSTM algorithm model training is less than 0.18, and the decision coefficients were all greater than 0.9. …”

Comparison results with other literature. by Yao Hu (3479972)

“…The outcome indicates that the standard error of the LSTM algorithm model training is less than 0.18, and the decision coefficients were all greater than 0.9. …”

Flight failure factors. by Yao Hu (3479972)

“…The outcome indicates that the standard error of the LSTM algorithm model training is less than 0.18, and the decision coefficients were all greater than 0.9. …”

R flight failure list. by Yao Hu (3479972)

“…The outcome indicates that the standard error of the LSTM algorithm model training is less than 0.18, and the decision coefficients were all greater than 0.9. …”